Jaggle.eu participated in the 21st IT Directors Forum, held on October 5, 2026, at the Athens Concert Hall, bringing AI-powered Low-code development, Jaggle.Apps and a real-world Jaggle.Signage use case into the discussion around the evolving priorities of IT organizations.

The event brought together IT leaders and technology professionals to exchange perspectives on application modernization, Artificial Intelligence, operational efficiency and the need for technology that can adapt as business requirements evolve.

From Low-code development to ready-to-adapt applications

Throughout the event, the Jaggle.eu team had the opportunity to discuss how organizations can approach application development with greater flexibility while maintaining alignment with their existing processes, systems and technology environments.

A key part of these conversations was Jaggle.Apps, a growing portfolio of applications built on the Jaggle.eu Low-code platform.

The portfolio includes Jaggle.CRM, Jaggle.HR, Jaggle.Conversational AI, Jaggle.RAG, Jaggle.XL2App and Jaggle.Signage, addressing different business requirements while sharing a common technology foundation.

Rather than starting from a blank page, Jaggle.Apps provide organizations with applications that can be introduced quickly and then adapted as processes, requirements and operational needs change.

Jaggle.Signage in a real business environment

One of the highlights of the forum was the presentation by Manthos Dardamanis, CEO of Mindsys, who shared a real-world case study based on Jaggle.Signage.

The session presented how digital signage operations can be managed through a centralized environment, bringing together screen organization, content, scheduling and campaign management across multiple devices and locations.

The case study provided a practical example of how an application built on Jaggle.eu can support specific business and operational requirements while remaining adaptable over time.

Supporting the changing priorities of IT teams

The discussions at the IT Directors Forum reflected many of the challenges technology teams are addressing today: modernizing existing applications, introducing AI into business processes, improving visibility across operations and responding to new requirements without creating additional complexity.

Jaggle.eu combines AI-powered capabilities with Low-code development to support internal teams in building and evolving applications around their own requirements and technology strategy.

Through both the core platform and Jaggle.Apps, organizations can approach development with a common foundation while maintaining the flexibility to adapt individual applications to the way they operate.

Thank you to everyone who visited us, attended the session and shared their perspectives throughout the day, and to BOUSSIAS Events for bringing together the IT community for another successful IT Directors Forum.

The Prototype Is Not the Product

There is a moment every technology leader recognizes. A developer — or sometimes a product manager with access to the right AI tool — demos a working application they built over a weekend. It looks impressive. It does most of what the business asked for. And it was built in a fraction of the time a traditional development cycle would have required.

That moment is real, and the tools behind it are genuinely powerful. AI coding assistants like Claude Code, Cursor, GitHub Copilot, and Replit Agent have fundamentally changed what is possible for individual builders. The speed is not hype. The productivity gains are measurable.

But there is a question that rarely gets asked in that demo meeting: who is going to run this in production, maintain it, secure it, and adapt it when the business changes next quarter?

That question is where the conversation about vibe coding ends and the conversation about low-code begins. And for most organizations, that question has a clear answer.

What Vibe Coding Actually Is

The term was coined by Andrej Karpathy in February 2025 to describe a mode of development where you describe what you want in natural language and let an AI generate the code — without necessarily reviewing or fully understanding what was produced. Collins English Dictionary named it Word of the Year for 2025. The speed is the point. The code is almost secondary. [1]

In practice, vibe coding sits on a spectrum. At one end is pure prompt-and-accept development. At the other is what thoughtful practitioners call augmented coding — using AI to accelerate work while reviewing, testing, and genuinely owning the output. The distinction matters enormously in an enterprise context, and it is one that most vibe coding conversations conveniently skip over.

The tools — Claude Code, Cursor, GitHub Copilot Agents, Replit Agent, v0, Lovable — generate real, portable source code in standard languages. You own what is produced. That is a legitimate advantage. The question is whether ownership alone is sufficient for what your organization actually needs.

The Problem Vibe Coding Does Not Solve

Speed of creation is only one dimension of enterprise software. The others — security, governance, compliance, maintainability, integration, lifecycle management — are where vibe coding consistently falls short, and where the gap between a promising prototype and a production-ready system becomes expensive.

The security picture alone should give enterprise leaders pause. Independent studies now consistently find that 68–73% of AI-generated code contains security vulnerabilities. Veracode's 2025 GenAI Code Security Report found AI tools failed to protect against cross-site scripting 86% of the time. Stanford's analysis found vibe-coded commits introduce security findings at ten times the rate of human-written code. [2] These are not edge cases — they are the baseline behavior of current AI code generation when left ungoverned.

Beyond security, there is what researchers call comprehension debt. When a function is generated in seconds, the developer sees the output but does not necessarily internalize the logic, edge cases, or dependencies. That debt compounds quietly — slowing incident response, making maintenance harder, and gradually eroding the productivity gains that motivated AI adoption in the first place.

Vibe coding optimizes for the moment of creation. Enterprise software needs to survive far beyond that moment.

None of this is an argument against AI-assisted development. It is an argument for being clear-eyed about what problem you are actually trying to solve. Vibe coding is a powerful tool for individual developers, technical prototyping, and exploring ideas. It is not an organizational development strategy.

What Low-Code Actually Delivers

Low-code platforms — OutSystems, Mendix, ServiceNow App Engine, Salesforce Platform, and enterprise-grade platforms like Jaggle — are development environments built around a fundamentally different set of priorities. Not just speed of creation, but reliability of operation.

The operational advantages are structural, not incidental:

• Governance by design — role-based access controls, audit trails, approval workflows, and data governance are built into the platform, not bolted on afterwards
• Compliance infrastructure — leading platforms ship with modules covering HIPAA, GDPR, SOX, and SOC 2. For regulated industries, this alone removes months of engineering work
• Enterprise integration — pre-built connectors to SAP, Salesforce, ServiceNow, Microsoft 365, and hundreds of other systems turn what would otherwise be complex middleware projects into configuration exercises
• Maintainability by non-developers — visual interfaces mean that the business owner of an application can modify it without raising a ticket. This changes the economics of maintenance entirely
• Application lifecycle management — versioning, rollback, testing environments, and deployment controls that enterprises expect from production software

The scale of adoption reflects this. Gartner estimates the low-code market will reach $44.5 billion in 2026, growing at 19% annually, with 75% of large enterprises already using at least four different low-code tools. [3] These organizations are not experimenting. They are standardizing.

Low-code does have real constraints — platform ceilings for highly specialized logic, vendor lock-in considerations that warrant careful TCO modelling, and licensing costs that scale with usage. These deserve scrutiny before any platform commitment. But they are manageable challenges, not fundamental limitations — and as the next section makes clear, the most significant constraint that critics have historically raised against low-code has already been addressed.

The Game Changer: When Low-Code Gains AI

The most important development in this space is not vibe coding. It is what happens when AI is embedded directly inside a low-code platform.

Leading platforms are no longer purely visual drag-and-drop environments. They have integrated AI assistants, generative features, and natural language interfaces into the core development experience — enabling builders to describe what they want and have the platform generate flows, interfaces, business logic, and components automatically. The output lands inside a governed, structured, enterprise-ready environment from the moment it is created.

This is the answer to the false choice between speed and governance. AI-powered low-code delivers both — and it does so within an operational framework that enterprises can actually trust.

Jaggle, Comsys's enterprise low-code application generation platform, is built on exactly this model. A user describes what they need — a business application, a customer-facing portal, an internal workflow tool — and Jaggle generates it, including React-based interfaces and web pages, directly from natural language input. The platform handles the structure, governance, and lifecycle management automatically.

What makes this genuinely different from vibe coding is the layer underneath. The generated application does not exist in isolation — it inherits enterprise integration, access controls, and deployment infrastructure from the platform. And for teams with the technical capability to go deeper, the generated code is accessible and modifiable. You get the speed of AI generation and the control of traditional development, without having to choose between them.

This directly answers the oldest criticism of low-code: that it is limiting for complex or custom requirements. When AI can generate custom logic and interfaces from a prompt — within a governed platform — the ceiling that once defined low-code's boundaries moves significantly higher. The argument that vibe coding wins on flexibility becomes much harder to sustain.

Choosing the Right Tool for the Right Problem

The question is not which approach is better in the abstract. It is which one is appropriate for what you are actually trying to build.

Vibe coding makes sense when:

• An individual developer or technical user needs to build a personal tool, script, or data pipeline quickly
• A team is validating a product hypothesis before investing in architecture
• The requirement involves genuinely custom algorithms or AI-native capabilities that no platform currently accommodates
• The output will be reviewed, tested, and owned by an experienced engineer

Low-code — and specifically AI-powered low-code — is the right choice when:

• The application will be used by multiple teams or business units
• Compliance, audit trails, or data governance are requirements — not optional
• Non-technical users need to build, maintain, or modify applications without IT dependency
• The system needs to integrate reliably with enterprise platforms over time
• Operational continuity matters — the application must function regardless of who built it or whether they are still in the organization
• You want the speed of AI generation without exposing the organization to ungoverned code in production

For most enterprise software — internal tools, business process applications, customer-facing portals, workflow automation, compliance-critical systems — the second list describes the reality. Vibe coding is a developer's instrument. Low-code is an organizational capability.

The Distinction That Matters

Vibe coding helps developers build software faster. Low-code helps organizations build software they can run, govern, maintain, and continuously improve — at scale, with confidence.

These are not the same problem. The enterprise software graveyard is full of things that were fast to build and expensive to operate. The productivity gains of AI coding tools are real — but productivity in creation is only one part of a software lifecycle that includes deployment, security, maintenance, compliance, and organizational ownership.

The organizations getting the most durable value from technology investment right now are not the ones choosing between vibe coding and low-code. They are the ones who understand which layer each one belongs to — and who are building their development strategy accordingly.

The Operationally Intelligent Choice

Vibe coding will continue to evolve, and it will remain a genuinely valuable capability for developers and technical builders. No serious technology leader should dismiss it.

But for organizations that need to deliver applications their teams can depend on — that are secure by design, compliant by default, maintainable without specialist intervention, and integrated with the systems the business already runs on — low-code is not a compromise. It is the more mature, more operationally intelligent choice.

And with AI now embedded directly into platforms like Jaggle, the historical trade-off between low-code's governance and vibe coding's speed no longer holds. The question for most organizations is not whether to choose one over the other. It is whether they are ready to build on a platform that gives them both.

References

About the Author 

Comsys and Jaggle.eu participated as sponsors at the AI in Financial Services Conference, organized by BOUSSIAS Events on July 8, 2026, at the Ethniki Asfalistiki Conference Center.

The conference brought together executives, technology leaders, and professionals from the financial services sector for a full day focused on Artificial Intelligence, automation, governance, and digital transformation.

During the event, the Comsys and Jaggle.eu team met with industry professionals and discussed how financial organizations can develop and improve business applications while maintaining the security, control, and regulatory compliance required by the sector.

AI and Low-code in Financial Services

Financial organizations are continuing to update their systems and operations. The challenge is not only to develop new applications, but also to do so without adding unnecessary complexity or reducing control.

AI and Low-code technologies can support this process by providing a structured way to develop applications, automate processes, and manage knowledge.

For regulated organizations, technology alone is not enough. Data protection, auditability, human oversight, and compliance must be part of every solution from the beginning.

Jaggle.eu supports this approach through an AI-powered Low-code environment. It allows organizations to design, develop, and improve business applications while keeping control over their data, processes, and application logic.

Presenting the HDB AI-Enabled Helpdesk Case Study

A key part of the conference was the session “Jaggle.eu: AI-Enabled Helpdesk for the Hellenic Development Bank.”

During the session, Vangelis Hadgigeorgiou, CEO of Comsys, was joined by Panos Keramitzis, CIO of HDB – Hellenic Development Bank, to present the needs behind the project and the solution developed with Jaggle.eu.

The Hellenic Development Bank supports access to financing programs by connecting public policy, the banking system, and businesses.

The organization manages 20 financing programs and receives around 20,000 to 25,000 emails every year. This creates a strong need for clear, accurate, and consistent communication.

The AI-enabled Helpdesk solution is designed to support this process through the following steps:

The full process is managed through an integrated case management system. This keeps requests, information, and user actions organized and traceable.

Human Oversight, Security, and Regulatory Alignment

Human approval remains an important part of the process.

The system supports employees by preparing a documented suggested response, while the final decision always remains with the responsible user.

The goal is to reduce the processing time of incoming requests from days to hours, while maintaining the accuracy, consistency, and control required in a regulated environment.

Supporting the Evolution of Financial Operations

The HDB case study shows how AI, RAG, Low-code application development, and case management can work together within a single controlled process.

It also shows the value of a platform that can continue to evolve.

Through Jaggle.eu, organizations can improve existing applications, add new automations, and support new operational needs over time.

At the Comsys and Jaggle.eu booth, conference participants had the opportunity to learn more about the platform and discuss how secure and controlled application development can support financial operations, internal processes, and customer service.

Thank You

We would like to thank Panos Keramitzis and HDB – Hellenic Development Bank for joining us and sharing their experience during the conference session.

We would also like to thank everyone who visited our booth and spoke with our team, as well as BOUSSIAS Events for the excellent organization of the AI in Financial Services Conference.

Learn more about how Jaggle.eu supports secure, controlled, and AI-powered Low-code application development for regulated organizations.

New Digital Signage App – One Platform, Every Screen

Jaggle now ships a native Digital Signage App that turns commercial displays and low-cost edge devices into fully managed, Jaggle-driven endpoints. It brings digital signage into the Jaggle platform as a first-class application – no proprietary media players, no separate CMS, no parallel toolchain. The same environment your teams already use to build pages, workflows, and conversational experiences now drives what appears on every screen in the building.

Runs natively where your screens already live

The app is built to run directly on the hardware organizations actually deploy: Samsung Tizen OS and LG webOS professional displays, and Raspberry Pi mini-PCs for everything else – from a single reception screen to a wall of departure boards. One app, one management model, across a mixed fleet. Registering a new screen is a matter of pointing the device at your Jaggle instance; from that moment it's a managed endpoint like any other.

Centrally authored, centrally controlled

Content, layouts, and playlists are authored and scheduled centrally in Jaggle and pushed to any screen or group of screens. Device grouping lets you target by location, department, or campaign; scheduling handles dayparting and time-boxed content; and remote monitoring reports playback status, device health, and connectivity so you know at a glance which screens are live and which need attention. Updates propagate over the air – there's no need to touch the hardware to change what's on it.

Resilient by design

Local caching keeps playback running through network interruptions. If a screen loses connectivity, it continues showing its scheduled content and re-syncs automatically once the connection returns – so a flaky branch network never leaves a display blank or frozen.

Live, data-driven content – not just slideshows

This is where the Digital Signage App separates itself from conventional signage tools. Because each screen is a Jaggle application, it can surface live, data-driven content straight from the same data model that powers the rest of the platform: queue counters and wait times, real-time KPIs and dashboards, branch-specific offers, wayfinding, and event information. Signage stops being a static loop of images and becomes a live window into your operational data.

Where it fits

Retail floors and store windows, banking and public-sector branch lobbies, transport hubs and departure halls, hospital and campus wayfinding, corporate lobbies and internal comms walls – anywhere a screen needs to show the right thing at the right time, driven by real data, managed from one place.

By folding signage into Jaggle, the app collapses the long-standing gap between "an app" and "a screen on the wall" into a single toolchain – one platform, every screen.

Jaggle Workflow AI Companion – Describe the Process, Get the Flow

Complementing the Page Development Helper on the UI side, the new Workflow AI Companion brings the same AI-assisted approach to business process design. Users describe a process in plain language – approvals, escalations, parallel branches, participants – and the Companion scaffolds the corresponding workflow, proposing steps, swim lanes, conditions, and actions that the designer can accept, refine, or extend.

Beyond first-draft generation, the Companion helps with the parts of complex workflows that usually slow teams down: suggesting decision logic, wiring in REST Web Service and Stored Procedure calls, recommending the right built-in actions (including Send Report), and flagging gaps or unreachable paths. What used to be an expert-only modelling exercise becomes an interactive, guided conversation – dramatically lowering the barrier to building sophisticated, production-grade processes.

Enhanced AI Page Builder – External REST APIs and Steering File

The AI Page Builder gets two significant upgrades that make its output both more capable and more consistent with each organization's standards: pages can now consume External REST APIs, and generation can be governed by a Steering File. Together they turn the builder from a fast scaffolder into a connected, standards-aware development partner.

External REST APIs

Until now, AI-generated pages worked primarily against the application's own Jaggle data model. With this release, the Page Builder can connect pages directly to external REST API endpoints – third-party services, partner systems, internal microservices, or any addressable API outside the current application.

Point the builder at an endpoint and it does the heavy lifting: it reads the request and response contract, maps fields to page components, and generates the controls, grids, and forms needed to display and interact with that data – already wired to the API. Parameters, headers, and authentication are configured once and reused, so a page that pulls live data from an external CRM, logistics tracker, pricing service, or open-data source can be stood up in minutes rather than hand-coded. Because the connection is a proper REST integration and not a static import, the page stays live: it reflects whatever the external service returns at runtime.

This closes a common gap in low-code tooling – the moment a page needs data that doesn't live in the platform, teams usually drop out to custom code. Now that same step is part of the guided, AI-assisted flow.

Steering File – generation that follows your rules

The second upgrade addresses consistency at scale. A new Steering File lets teams codify the conventions the AI must follow, and the builder reads it on every generation. Instead of producing generically "correct" output that then needs manual rework, the Page Builder produces pages that already match house style from the first draft.

A Steering File can capture preferred controls and component libraries, naming standards, layout and spacing conventions, data-binding patterns, accessibility requirements, and any organization-specific rules a lead developer would otherwise enforce in review. It acts as a single, reusable source of truth for "how we build pages here" – so a team of ten produces work that looks and behaves as if it came from one hand, and new contributors inherit the standards automatically.

Better together

The two features reinforce each other. External REST API connectivity widens what the builder can reach; the Steering File governs how it builds against it. A page that consumes a partner API arrives not only wired and functional, but already conformant to your controls, naming, and accessibility rules – ready for review rather than rework.

New Recommender ML Model – Built-In Personalization

Building on the AutoML engine introduced in 2026.1, Jaggle adds a dedicated recommender model for recommendation and next-best-action scenarios. Teams can now train and deploy recommendations directly inside the platform – product and content suggestions, cross-sell and up-sell, next-best-offer, and personalized routing – without stitching together an external ML stack.

The model supports collaborative and content-based approaches, learns from the application's own data model, and exposes recommendations to any Jaggle page, workflow, or conversational dialogue through the same AI layer as the rest of the platform. For retail, banking, telecom, and media use cases, it puts personalization within reach of business teams, not just data-science specialists.

Over the past few years, sitting across the table from business owners, Chief Information Officers, and operations leaders, I have noticed a recurring pattern.

The industry changes. The company size changes. The level of technology maturity changes. But the core challenge often sounds the same.

Organizations want to automate approval workflows, create customer portals, modernize internal applications, improve reporting, connect scattered systems, and give teams better tools for daily work.

But they have a serious problem with execution.

As one Chief Information Officer recently put it to me: “We don’t lack good ideas. We have lots of them; but we have a problem executing them.”

That sentence captures one of the most important technology challenges I see in the market today.

The Hidden Cost of Waiting

When the distance between identifying an operational need and delivering a working application becomes too long, the backlog stops being only an IT issue. It becomes a business constraint.

We see it in everyday workarounds.

Departments run business-critical processes through spreadsheets because the reporting tool they need is still waiting for development capacity. Customer service teams manage requests through manual email threads. Operations teams duplicate information across systems because the proper integration has not been prioritised. Managers wait for visibility that should already be available.

None of these examples may look dramatic on their own. But together, they slow the organization down.

Data becomes fragmented. Teams lose time. Processes become harder to control. Customers and employees feel the impact. And IT teams are asked to do more with resources that are already stretched.

It is easy, and unfair, to treat IT as the bottleneck. Most internal technology teams are not blocking progress. They are overloaded.

They have to maintain core systems, protect security, support users, manage integrations, respond to incidents, and deliver new business requests at the same time. The demand for applications has grown faster than the traditional delivery model can realistically absorb.

AI Raises the Pressure Further

This pressure is now amplified by the growing expectation that artificial intelligence should deliver practical value across operations.

But experienced technology leaders know the reality: AI cannot create meaningful business impact when workflows are still manual, data is fragmented, and processes depend on informal workarounds.

Before an organization can become truly AI-ready, it must first understand and structure the way work actually happens.

That means digitizing workflows, connecting data, reducing manual steps, and creating applications that reflect real operational needs.

In other words, application delivery and AI readiness are now closely connected. Clearing the backlog is about moving faster. It is also about building the digital foundation that allows intelligence, automation, and better decision-making to work in practice.

Business Teams Are Becoming More Precise

One of the most interesting changes I see in client conversations is that business teams are no longer bringing only abstract problems.

This changes the discussion. The question is no longer only, “How do we build this single project?” It becomes, “How do we deliver this kind of application repeatedly, faster, with the right governance, and without creating more technical debt?”

This is where Low-code becomes strategically relevant. Not as a shortcut. Not as a way to bypass IT. And certainly not as a free-for-all.

Low-code matters because it changes the delivery model. It helps bring business knowledge closer to execution, while keeping technical teams in control of architecture, integration, security, and long-term maintainability.

The Real Value Is Sustainable Application Generation

The strongest value of Low-code is not “easy development.”

Serious business applications are never trivial. They need clear requirements, secure architecture, reliable integrations, testing, user adoption, and support after go-live.

The real value is sustainable application generation.

A mature Low-code approach reduces repetitive development effort, shortens delivery cycles, and gives organizations a more structured way to turn business requirements into working applications.

It also addresses what happens after launch.

Building an application is only part of the challenge. The real test comes later: when requirements change, systems evolve, integrations need to be maintained, and security or compliance expectations increase.

A governed application generation model helps applications scale and evolve with less risk, less rework, and stronger long-term control.

Speed Without Governance Creates New Problems

Of course, speed alone is not enough.

If Low-code is introduced without clear use cases, architectural rules, ownership, and governance, it can create a new form of fragmentation. Organizations may end up with disconnected applications, duplicated data, unmanaged workflows, and shadow systems that are difficult to secure or maintain.

The same risk is now appearing with unmanaged AI experimentation.

Without architecture, speed can simply make risk appear faster.

That is why the right starting point is not the platform conversation. It is the use case conversation.

A service request workflow. A contract approval process. A customer complaint management tool. A field operations interface. A reporting application for management teams.

These are the kinds of use cases that show where the backlog is hurting the business, and where a more repeatable delivery model can make a visible difference.

From Backlog to Business Execution

This is exactly the realization behind Jaggle.eu, our AI-powered, Low-code platform.

Jaggle.eu is designed to help organizations move from application backlog to business execution, allowing business teams to co-author workflows while giving IT centralized governance over security, data, integration, deployment, and long-term maintainability.

Traditional development will always have its place, especially for core systems and highly specialized requirements. But it cannot absorb the full volume of modern business demand on its own.

Organizations need a more repeatable way to deliver the applications that keep operations moving.

Because moving forward, the market leaders will not simply be the companies with the best ideas.

They will be the ones with the governed execution engine to deliver them.

About the Author 

Jaggle.eu participated as a One-to-One Meeting Sponsor at the 4th CIO Summit, held on May 12 and 13, 2026, at Grecotel La Riviera.

The summit brought together CIOs, technology leaders and decision makers for two days of focused one-to-one meetings, strategic discussions and high-level networking around the future of IT and digital transformation.

Strategic Conversations with Technology Leaders

Representing Comsys at the event were Vangelis Hadgigeorgiou, CEO of Comsys, and Kostas Bithimitris, Sales Manager at Comsys.

During the summit, they had the opportunity to connect with CIOs and technology decision makers, discussing the challenges organizations face as they modernize their application landscape, accelerate digital initiatives and maintain control over governance, security and compliance.

The Role of Jaggle.eu in Modern Application Development

A key focus of the discussions was how Jaggle.eu supports modern application development through AI-powered Low-code capabilities.

Jaggle.eu enables organizations to design, build and evolve business applications in a more structured and controlled way, while maintaining high standards of quality, security and compliance. Its Low-code approach helps reduce complexity, strengthen collaboration between business and IT teams, and support efficient development without compromising control.

Built for Modern IT Needs

The conversations at the 4th CIO Summit confirmed a common priority across IT teams: digital transformation must be scalable, structured and built on trusted technology foundations.

For CIOs and technology leaders, speed alone is not enough. Modern application development also requires governance, integration capabilities, security, compliance and the flexibility to support changing business needs. Through Jaggle.eu, Comsys helps organizations address these priorities with a platform designed for complex IT environments.

Connecting AI, Low-code and Governance

As AI becomes increasingly embedded in technology strategies, organizations need solutions that help them move from experimentation to practical implementation.

Jaggle.eu brings together AI-powered capabilities and Low-code development to support the creation of business applications with greater efficiency and control. This combination allows organizations to advance their digital transformation initiatives while keeping governance, compliance and operational reliability at the center.

Thank You

Our participation at the 4th CIO Summit was a valuable opportunity to exchange views with CIOs and technology leaders on the future of IT, application development and digital transformation.

We would like to thank BOUSSIAS Events for organizing a focused and valuable summit, as well as everyone who met with our team during the event.

Learn more about our solutions:
comsyscx.com | jaggle.eu

A packed release that raises the bar on AI, security, developer experience, and enterprise readiness across both platforms.

It has been an intense development cycle, and the teams have delivered. Jaggle 2026.1 and Jaggle.Conversational AI 2026.1 are now Generally Available, bringing dozens of new capabilities that touch virtually every area of the platform.

Here is a tour of the highlights.

Jaggle 2026.1 - The Headlines

Workflow & Business Process Enhancements

Data Model & Security

Page Designer & UX

Platform & Infrastructure

RAG (Retrieval-Augmented Generation)

Jaggle.Conversational AI 2026.1 - The Headlines

The Jaggle.Conversational AI platform receives significant upgrades, focused on NLU depth, voice channel readiness, and operational independence.

Voice Channel - Barge-In and Advanced Voice Settings:

One of the most anticipated features in this release is full barge-in support. Users can now interrupt the system mid-utterance - just as they would in a natural phone conversation - and the platform will immediately stop playback, capture the new input, and route the dialogue accordingly. This is a game-changer for voice IVR deployments where callers know what they want and shouldn't have to wait for a menu to finish playing.

Barge-in is fully configurable at multiple levels: a global default can be set per dialogue, and then overridden on a per-response basis within the Dialogue Designer. The same applies to DTMF support, Speech-to-Text language, and Text-to-Speech language - all of which are now first-class settings in the voice tab of every response node. This granular control means a single dialogue can switch languages mid-conversation, enable or disable barge-in contextually (e.g., disable it during a critical confirmation step), and accept keypad input where appropriate.

The underlying integration with Asterisk + UniMRCP is now live, with the UniMRCP plugin supporting dynamic parameterization at node level. Combined with barge-in, platform is now a production-grade voice platform.

LLM-Based NLU - Multilingual Without Training Data

This release introduces a fundamentally new approach to Natural Language Understanding: an LLM-based NLU adapter that replaces traditional intent-classification models with LLM prompts. The practical impact is enormous - organizations can now deploy multilingual dialogues without building and maintaining separate training datasets for each language. The LLM interprets user input in any supported language, maps it to the correct intents and entities, and returns structured results that the dialogue engine processes as usual.

For clients operating across multiple geographies or serving multilingual customer bases, this eliminates one of the biggest bottlenecks in conversational AI deployment: the cost and time of curating training examples in every target language.

The adapter works alongside the existing NLU options (including the new NLP.js adapter for on-premises, cost-effective deployments), so teams can choose the right engine for each use case - LLM-based for rapid multilingual rollout, traditional NLU for high-volume low-latency scenarios, or a hybrid approach.

Conversation Simulation - AI-Powered Dialogue Testing at Scale

Testing conversational flows has always been manual, slow, and prone to blind spots. The new Conversation Simulation feature leverages LLMs to generate realistic test conversations automatically, based on use-case descriptions and scenario parameters. It operates in two modes:

Non-Interactive Mode

The LLM generates complete conversations (both user turns and expected system responses), which are then used to automatically create new intents and training examples. This is a powerful bootstrapping tool for new dialogues - describe the use case, and the system produces dozens of realistic conversation paths that enrich the training data.

Interactive Mode

The LLM plays the role of the end user and interacts in real time with the platform backend. This is true automated regression testing: the simulated user probes the dialogue with varied phrasing, edge cases, and unexpected inputs, and the system records whether the dialogue responded correctly. When a dialogue is updated, teams can re-run simulations to catch regressions before they reach production.

Automated Testing - Record, Replay, Validate

Complementing conversation simulation is a new automated testing utility for deterministic regression testing. Administrators can "record" test cases using the existing Dialogue Tester, capturing input utterances and their expected outputs. When changes are made to a dialogue, the recorded test suite can be executed automatically: the platform backend simulates each test case, compares actual responses against expected ones, and marks each case as passed or failed.

This gives teams a lightweight but rigorous safety net for dialogue changes - no scripting required, no external testing tools, just record and replay within the platform.

Natural Language Understanding - Deeper and Broader

Expanded Entity Support: The Entities Module now supports four entity types - List, Regex, Built-In, and Trainable - each with a dedicated UI tab. Regex entities, previously limited to the Keyword Adapter, now work across all adapters. Trainable entities are a brand-new type for NLU vendors that support them.

Training Example Hygiene: Automatic trimming and lowercase normalisation prevent duplicate training examples and keep NLU models clean.

System Integration

NLP.js Adapter: A new cost-effective NLU adapter allows deployments without third-party NLU costs. NLP.js can run on-premises with no specialized hardware, making it ideal for GDPR-sensitive or budget-conscious installations.

Sensitive Data Masking: New settings on User Action nodes control masking of sensitive input phrases and output variables. When enabled, sensitive data is replaced by asterisks in the transcript - essential for PCI-DSS and GDPR compliance in voice and chat channels.

Reporting

Redesigned Built-In Reports: All three built-in reports have been rebuilt using the Visual Page Designer, enabling synchronized report updates across customer installations without manual intervention.

Looking Ahead in the Jaggle.Conversational AI Pipeline: The roadmap continues at full pace: dialogue transfer with reusable modules, GraphRAG for richer contextual retrieval, end-of-conversation surveys for multi-dimensional feedback, user-question analytics with topic clustering and knowledge-gap detection and research into next-generation voice technologies, including Diffusion LLMs and Gemini native audio models. Stay tuned.

By the Numbers

• 8 New or enhanced AI features
• 4 Workflow & business process improvements
• 5+ Page Designer & UX upgrades
• 5+ Platform & infrastructure hardening items
• 3 RAG enhancements
• 8 Jaggle.Conversational AI deliverables
• 33+ Total shipped features across both platforms

What This Means for Our Clients

With 2026.1, Jaggle is no longer just a low-code development platform - it is an AI-augmented enterprise application factory. From natural-language SQL queries to automated documentation, from multi-LLM orchestration to WCAG-compliant accessibility, this release positions Jaggle as a platform that enterprises can trust for their most demanding digital transformation programs.

For Jaggle.Conversational AI, the Asterisk integration and NLP.js adapter open up new deployment models - voice IVR without third-party lock-in, on-premises NLU for regulated environments, and a clear path toward LLM-native dialogue management.

Artificial intelligence is transforming how organizations design, build, and operate software. From automated workflows to AI-assisted development, modern platforms increasingly rely on intelligent systems to accelerate innovation and simplify complex processes. As AI adoption grows, organizations must ensure that these technologies are implemented responsibly, transparently, and securely. 

Jaggle, the AI-powered low-code platform developed by Comsys, has achieved ISO/IEC 42001 certification, the first international standard for Artificial Intelligence Management Systems (AIMS). This certification demonstrates Jaggle’s commitment to responsible AI governance and strengthens its position as a trusted platform for building intelligent enterprise applications. 

By aligning its AI capabilities with a globally recognized framework, Jaggle ensures that organizations using the platform can innovate with confidence while maintaining strong governance and risk management practices. 

What ISO 42001 Means for AI Platforms 

ISO 42001 establishes a comprehensive framework for organizations that design, develop, deploy, or use AI systems. The standard focuses on managing AI responsibly across its entire lifecycle, including design, development, deployment, monitoring, and continuous improvement. 

For technology platforms that integrate AI into their core functionality, ISO 42001 introduces structured processes that help ensure: 

For Jaggle, achieving ISO 42001 certification confirms that its AI capabilities operate within a robust governance framework that aligns with international best practices. 

Responsible AI in AI-Powered Application Development 

Jaggle combines low-code development with AI-powered automation, allowing organizations to create enterprise applications faster and more efficiently. The platform helps streamline application development through features such as automated data modeling, intelligent workflow design, and AI-assisted specification generation. 

With ISO 42001 certification in place, these AI-driven capabilities are supported by clearly defined governance policies and risk management processes. This ensures that AI-assisted development within Jaggle remains transparent, traceable, and accountable, giving organizations greater confidence when using AI to accelerate digital transformation. 

By embedding responsible AI governance into its development framework, Jaggle enables teams to build sophisticated applications while maintaining oversight and control. 

Strengthening Enterprise Trust and Security 

Many organizations rely on low-code platforms to build mission-critical applications that support key business operations. As AI becomes more integrated into these platforms, enterprises need assurance that the technology is managed responsibly. 

ISO 42001 certification provides independent verification that Jaggle’s AI systems follow internationally recognized governance practices. This helps strengthen trust among customers, partners, and stakeholders by demonstrating that AI risks are actively managed and monitored. 

For enterprises adopting Jaggle, this means they can take advantage of AI-driven development capabilities while knowing the underlying systems operate under structured governance and continuous oversight. 

Supporting Compliance with Emerging AI Regulations 

Regulation around artificial intelligence is rapidly evolving across the world, particularly in regions such as the European Union. Organizations implementing AI technologies are increasingly expected to demonstrate responsible governance, transparency, and accountability. 

ISO 42001 helps align Jaggle with these expectations by providing a framework that supports responsible AI practices and structured risk management. As regulatory environments continue to develop, platforms that already incorporate internationally recognized AI governance standards are better positioned to support compliant AI adoption. 

For organizations building AI-enabled applications with Jaggle, this certification adds an additional layer of assurance that the platform follows established best practices. 

A Competitive Advantage in the Low-code Market 

The low-code development market is expanding rapidly as organizations seek faster ways to build applications and modernize legacy systems. Jaggle differentiates itself by combining rapid application development with AI-driven automation, enabling teams to design, deploy, and scale solutions more efficiently. 

ISO 42001 certification further strengthens this value proposition. By demonstrating verified responsible AI practices, Jaggle stands out among low-code platforms that incorporate AI capabilities but may not yet operate under a recognized AI governance framework. 

For enterprises evaluating technology platforms, responsible AI governance is becoming an important factor in technology selection. ISO 42001 certification signals that Jaggle is committed to delivering AI-powered capabilities while maintaining the highest standards of transparency and accountability. 

Enabling Innovation with Responsible AI 

Jaggle was created to help organizations accelerate digital transformation through intelligent automation and low-code development. Achieving ISO 42001 certification reinforces this mission by ensuring that innovation is supported by responsible AI management. 

As AI continues to shape the future of software development, organizations need platforms that balance advanced capabilities with strong governance and trust. With ISO 42001 certification, Jaggle demonstrates its commitment to building AI technologies that are not only powerful, but also transparent, ethical, and responsibly managed. 

For businesses looking to harness AI-driven development while maintaining control and compliance, Jaggle provides a platform where innovation and responsible AI go hand in hand. 

About the Author 

Athens, March 12, 2026

Comsys announces its certification with ISO/IEC 42001:2023 for the Design, Development, Provision, Operation, Monitoring, and Support of Artificial Intelligence Functions within the Jaggle.eu low-code platform. ISO/IEC 42001 is the world’s first international standard for Artificial Intelligence Management Systems (AIMS), establishing a comprehensive framework of processes, control mechanisms, and continuous improvement to ensure the responsible utilization of artificial intelligence.

As an application development platform, Jaggle.eu is redefining how organizations modernize their systems. It leverages the agility of low-code and utilizes integrated AI functionalities to fully automate complex processes. Consequently, it supports enterprises in transforming intricate business needs into secure, scalable, and fully documented applications in significantly less time, depending on project complexity.

This certification confirms that Comsys implements a structured and documented AI governance framework. This framework aims to identify, assess, and mitigate relevant risks, such as issues regarding bias, transparency, and reliability, in accordance with internationally recognized best practices.

For clients, partners, and regulatory bodies, this certification serves as tangible proof of responsible and structured AI governance. It enhances transparency and trust in the use of AI, while the implemented management system aligns with the core principles and philosophy of the European Union's Artificial Intelligence Act (EU AI Act).

In the realm of low-code application development, the certification aligns an organization's teams to apply unified AI management practices. This is particularly crucial when AI assists in modeling automation, code generation, and documentation, ensuring that deliverables, such as data models, workflows, and user interface specifications, are produced with traceability and documented oversight.

Furthermore, Jaggle.eu supports Agentic AI functionalities, where AI evaluates and executes actions within workflows. Under the ISO/IEC 42001 framework, this automation is implemented with rigorous impact assessments, clear human-in-the-loop checkpoints, and robust safety mechanisms, ensuring that even the most autonomous operations remain fully controlled.

Spyros Karathanasis, Chief Product Technology Officer of Comsys, stated:

"At Jaggle.eu, artificial intelligence is not an add-on feature; it is a structural element of the platform. The ISO/IEC 42001 certification reinforces this approach in a concrete way: it establishes the framework for the transparency, reliability, and auditability of AI functions at every stage, both during their lifecycle as platform capabilities and during the development and operation of every application that utilizes them."

About Comsys

Comsys has been operating since 1989, providing innovative IT solutions and systems integration with projects across more than 20 countries. The company specializes in Contact Center and Digital CX solutions and offers a suite of next-generation products for low-code application development and omnichannel digital assistants.

About Jaggle.eu

Jaggle.eu is the Greek low-code solution with embedded artificial intelligence, enabling enterprises to rapidly develop secure applications of exceptional quality.

Contact Information:

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Η Comsys Πιστοποιήθηκε με ISO/IEC42001 για το Σύστημα Διαχείρισης Τεχνητής Νοημοσύνης του Jaggle.eu

Αθήνα, 12 Μαρτίου 2026

Η Comsys ανακοινώνει την πιστοποίησή της με το ISO/IEC 42001:2023 για τον Σχεδιασμό, Ανάπτυξη, Διάθεση, Λειτουργία, Παρακολούθηση και Υποστήριξη των Λειτουργιών Τεχνητής Νοημοσύνης της πλατφόρμας Low-code Jaggle.eu. Το ISO/IEC 42001 αποτελεί το πρώτο διεθνές πρότυπο για Συστήματα Διαχείρισης Τεχνητής Νοημοσύνης (AIMS) και θεσπίζει ένα ολοκληρωμένο πλαίσιο διαδικασιών, μηχανισμών ελέγχου και συνεχούς βελτίωσης, διασφαλίζοντας την υπεύθυνη αξιοποίηση της τεχνητής νοημοσύνης.

Το Jaggle.eu, ως πλατφόρμα ανάπτυξης εφαρμογών, επαναπροσδιορίζει τον τρόπο με τον οποίο οι οργανισμοί εκσυγχρονίζουν τα συστήματά τους. Χρησιμοποιεί την ευελιξία του low-code και αξιοποιεί ενσωματωμένες λειτουργίες τεχνητής νοημοσύνης για την πλήρη αυτοματοποίηση σύνθετων διαδικασιών. Έτσι, υποστηρίζει τις επιχειρήσεις στην μετατροπή περίπλοκων επιχειρηματικών αναγκών σε ασφαλείς, επεκτάσιμες και πλήρως τεκμηριωμένες εφαρμογές σε σημαντικά συντομότερο χρόνο, ανάλογα με την πολυπλοκότητα του έργου.

Μέσω της πιστοποίησης αυτής, επιβεβαιώνεται ότι η Comsys εφαρμόζει δομημένο και τεκμηριωμένο πλαίσιο διακυβέρνησης τεχνητής νοημοσύνης, με στόχο τον εντοπισμό, την αξιολόγηση και τον μετριασμό σχετικών κινδύνων, όπως είναι ζητήματα μεροληψίας (bias), διαφάνειας και αξιοπιστίας, σύμφωνα με διεθνώς αναγνωρισμένες πρακτικές.

Για πελάτες, συνεργάτες και ρυθμιστικούς φορείς, η πιστοποίηση αυτή αποτελεί απτή ένδειξη υπεύθυνης και δομημένης διακυβέρνησης της τεχνητής νοημοσύνης. Ενισχύει τη διαφάνεια και την εμπιστοσύνη στη χρήση τεχνητής νοημοσύνης, ενώ το εφαρμοζόμενο σύστημα διαχείρισης ευθυγραμμίζεται με τις βασικές αρχές και τη φιλοσοφία του Ευρωπαϊκού Κανονισμού για την Τεχνητή Νοημοσύνη (EU AI Act).

Στην ανάπτυξη εφαρμογών με low-code, η πιστοποίηση ευθυγραμμίζει τις ομάδες ενός οργανισμού ώστε να εφαρμόζουν ενιαίες πρακτικές διαχείρισης τεχνητής νοημοσύνης. Αυτό αποκτά ιδιαίτερη σημασία όταν η τεχνητή νοημοσύνη υποστηρίζει αυτοματοποίηση μοντελοποίησης, δημιουργία κώδικα, τεκμηρίωση κ.λ.π., ώστε τα παραδοτέα μοντέλα δεδομένων, ροές εργασίας, προδιαγραφές διεπαφής χρήστη κλπ., να παράγονται με ιχνηλασιμότητα και τεκμηριωμένη εποπτεία.

Επιπλέον, το Jaggle.eu υποστηρίζει λειτουργίες Agentic AI, όπου η τεχνητή νοημοσύνη αξιολογεί και εκτελεί ενέργειες σε ροές εργασίας. Στο πλαίσιο του ISO/IEC 42001, η αυτοματοποίηση αυτή υλοποιείται με αυστηρές αξιολογήσεις αντίκτυπου (impact assessments), σαφή σημεία ανθρώπινης επίβλεψης (human-in-the-loop) και μηχανισμούς ασφαλείας, ώστε οι πιο αυτόνομες λειτουργίες να παραμένουν ελεγχόμενες.

Ο Σπύρος Καραθανάσης, Chief Product Technology Officer της Comsys, ανέφερε:
«Στο Jaggle.eu, η τεχνητή νοημοσύνη δεν αποτελεί πρόσθετο χαρακτηριστικό, είναι δομικό στοιχείο της πλατφόρμας. Η πιστοποίηση κατά ISO/IEC 42001 ενισχύει αυτή την προσέγγιση με συγκεκριμένο τρόπο: θέτει το πλαίσιο για διαφάνεια, αξιοπιστία και ελεγξιμότητα των λειτουργιών ΑΙ σε κάθε στάδιο, τόσο κατά τον κύκλο ζωής τους ως δυνατότητες της πλατφόρμας, όσο και κατά την ανάπτυξη και λειτουργία κάθε εφαρμογής που τις αξιοποιεί.»

Σχετικά με την Comsys

Η Comsys δραστηριοποιείται  από το 1989 στην παροχή καινοτόμων λύσεων πληροφορικής και ολοκλήρωσης συστημάτων με έργα σε περισσότερες από 20 χώρες. Η εταιρεία εξειδικεύεται σε λύσεις Contact Center και Digital CX και διαθέτει σειρά προϊόντων νέας γενιάς, για ανάπτυξη εφαρμογών με low-code και πολυκαναλικών ψηφιακών βοηθών. 

Σχετικά με το Jaggle.eu

Το Jaggle.eu είναι η ελληνική λύση, low-code με ενσωματωμένη τεχνητή νοημοσύνη, που επιτρέπει στις επιχειρήσεις να αναπτύσσουν με ταχύτητα ασφαλείς εφαρμογές μοναδικής ποιότητας.

Για πληροφορίες αναφορικά με το Jaggle.eu: [email protected]   

Επικοινωνία για τα ΜΜΕ - [email protected] | www.jaggle.eu/contact