Data & AI
Beyond POCs: We put data architectures and AI agents to work.
AI is more than a tool. It changes the rules of the game.
Artificial intelligence is a cross-cutting technology that spans the entire organization. The question is no longer whether companies will use AI, but how.
In practice, many organizations never move beyond the proof-of-concept stage. They build pilots, but fail when it comes to integrating them into existing systems or addressing open security and architecture questions.
That is where INNOQ comes in: we combine architecture expertise with hands-on AI experience and support you from strategic assessment to production-ready systems. Along the way, we keep seeing the same kinds of challenges:
Automating Business Processes
Are your business processes too complex for rule-based automation – too many edge cases, too many handoffs across channels? We work with you to identify where AI-driven automation makes sense. To do that, we analyze the process, its cost, and the value it can create. We factor in compliance requirements and keep humans in the loop wherever necessary.
Turning Data into Innovation
Is your data trapped in silos, with every new analysis requiring extensive coordination with IT? Using agentic infrastructure, we build a system that brings together three things: MCP as a standardized interface to your data sources and systems, Agent Skills that equip agents with your company's domain knowledge and rules, and a scripting layer that lets agents generate analyses, reports, or visualizations on their own. The result is cross-functional analysis and data-driven decision-making without unnecessary friction.
Running AI Models on your own Terms
Do you operate in a highly regulated industry and need to keep sensitive data away from external AI providers? We advise you on operating models, hardware, and real-world costs – from TCO analysis to implementation in local data centers or on-premises environments.
Our Services
INNOQ helps you use data as a strategic asset for the future of your business – from building decentralized data architectures to putting agentic AI into practice – in ways that create value and stand up to scrutiny.
Agentic Software Modernization
Software modernization is complex and time-consuming. Legacy systems – whether COBOL, mainframes, or organically grown Java monoliths – are often poorly documented. On top of that, the number of people who truly understand these systems is shrinking. Agentic AI changes what is possible: it can work through millions of lines of legacy code, detect dependencies, and extract domain knowledge.
The Agentic Modernization Workbench
That is exactly why we developed the Agentic Modernization Workbench: a curated set of Agent Skills, tools, and modernization expertise shaped by senior consultants. It assesses the starting point, designs a plan, and gives your teams the guardrails they need for a successful modernization initiative.
The workbench supports you through four phases:
- Discovery: the analysis phase
- Decide: what should the new solution look like?
- Transform: the implementation phase
- Validate: have we met all requirements?
The workbench primarily accelerates the analysis and decision phases while making transformation activities transparent and measurable. It is not a magic wand. Critical decisions remain in human hands.
From a technical perspective, the workbench relies on a transparent skill architecture rather than a black box. The solution is modular and model-agnostic – there is no vendor lock-in.
Our goal is to enable your teams. They understand the workbench, adapt it, and use it independently.
Who is the workbench for?
Mid-size companies and enterprises with modernization initiatives – whether AS/400, mainframe, or monolithic Java systems.
What does the workbench include?
Licensing and setup, including a kick-off workshop and workbench integration; guidance from senior consultants on modernization and enablement; and maintenance packages for the ongoing evolution of skills and integrations.
AI Systems and AI Features
We build AI systems that fit seamlessly into your existing landscape and perform reliably in production. We support you from analysis and architecture to implementation – for example with RAG architectures that unlock your company data intelligently, chatbots that go beyond canned answers, or intelligent document processing.
In many cases, there is no need for a complete rebuild. We extend your existing systems with targeted AI features, from intelligent search and automated classification to recommendation systems. We take an incremental approach, with a clear focus on the use cases that promise the highest ROI.
Designing software architectures for AI and ML systems
INNOQ is an iSAQB®-accredited training provider and co-authored the curriculum for the CPSA Advanced Level module Software Architecture for AI (SWARC4AI). This official certification is designed for software architects and developers who want to design and implement AI systems professionally.
Build AI Agents
AI agents handle complex tasks. They make decisions autonomously and interact with your existing systems. We support you in integrating AI agents into your workflows – from simple assistants that handle repetitive tasks to multi-agent systems in which several specialized agents collaborate. To do this, we rely on open standards such as the Model Context Protocol (MCP), which allows us to give agents secure access to your data and tools.
Process Automation
Some business processes have long resisted automation – too many exceptions, too many breaks between systems and channels. Where rule-based systems hit their limits with endless if-else chains, AI opens up new possibilities. We automate processes that need to bridge disconnected channels and inputs: documents, scans, calls, emails, or external data sources – for example in document processing, customer service, or HR workflows. For regulated companies in particular: every automated step is transparently documented and meets regulatory requirements.
Agentic Software Engineering
Agentic AI is fundamentally changing how we build software. In practice, it now goes far beyond code completion – from requirements analysis and architecture to testing, deployment, and operations. Teams that master these tools build faster, improve quality, and reduce friction.
Agentic Software Engineering Training (3 days)
Three days of hands-on learning for developers and architects: how to use generative AI systematically across the entire software development lifecycle – from simple code completion to advanced agent-based workflows.
Agentic Engineering Accelerator (Coaching Program)
For teams that want to embed what they have learned into everyday work: an INNOQ consultant works directly with your team over several months – typically two to three days per week. Through pair programming, mob sessions, and live demos, agentic software engineering becomes part of daily practice. The outcome: after the program, your team can apply the new methods on its own.
Sovereign AI Infrastructure
Not every company can or should use models from OpenAI or Anthropic – whether for regulatory reasons, because of data protection requirements, or due to strategic considerations. In those cases, we support you in running open source models on your own infrastructure or in a private cloud. This is not just about technology; it is primarily about the economics. What does operating these models really cost? What hardware do you need? Does 24/7 operation make sense, or is a limited time window enough? We create TCO analyses and advise on hardware, infrastructure, and operating models – especially relevant for the public sector, highly regulated industries, and compliance-driven organizations.
AI and Data Strategy Consulting
The most common stumbling block in AI initiatives is a lack of focus. Where should you start? Which use cases promise the highest return on investment? And how do they align with your business strategy?
We help you develop an AI strategy that supports your business goals. A key part of that is data strategy. Without accessible, high-quality data, AI remains all promise and little impact. Together, we assess where make-or-buy makes sense, what role open source models should play, and how you can move step by step from your first use case to a scalable AI landscape.
A strong way to get started is our AI Opportunity Mapping Workshop: in six hours, we work with you to identify two or three prioritized AI use cases, including an assessment of impact, feasibility, and data availability.
Data Architecture and Data Mesh
Data is a key resource for business success – if people can access it and use it. In many companies, AI initiatives fail not because of the technology, but because of the data landscape. Data silos, unclear ownership, and missing quality standards get in the way.
Data Mesh offers an approach that solves these problems: a decentralized data architecture with clear domain ownership. Instead of relying on a central data platform that becomes a bottleneck, we focus on data products, data contracts, and self-service platforms – so the teams that know the data best can also take responsibility for it.
We advise you on data architecture as the foundation for your AI initiatives and support you with Data Mesh implementation.
Entropy Data
For the operational side of Data Mesh, Entropy Data is available – a data management platform for data products, data contracts, and data governance:
- Marketplace: the entry point for data users to find the right data products for their use case and request access.
- Studio: the workspace for owners and developers of data products to create, edit, and monitor them.
- Governance: for data stewards, managers, and platform teams to define organization-wide policies and maintain visibility across the platform.
Entropy Data is a spin-off that emerged from INNOQ's employee innovation program.
In practice, product and consulting are tightly connected:
Entropy Data develops and operates the data management platform, while INNOQ supports you with strategy, architecture, and implementation for your data landscape.
How We Have Supported Our Clients
For us, AI is never an end in itself. In our projects, we focus on responsible, cost-conscious strategies designed to deliver value – from the first assessment to implementation and knowledge transfer.
Not a sales pitch, but real lessons learned and hands-on experience that genuinely moved us forward in using AI across the software development lifecycle.
Tobias QuelleCIO, Brack Altron AG
Get Started Right Away
Our workshops and training courses offer a practical starting point for Data & AI topics. From hands-on training for your engineering teams to strategic workshops for decision-makers – you can get started right away.
