# AI development company in Brussels — Co-Labs > AI agents, LLM applications and automations that do real work, secure and ready for the EU AI Act. Source page: https://co-labs.be/#ai-development ## Content AI development company · Brussels AI development that does real work in your operations Co-Labs is an AI development company in Brussels. We design, build and run AI agents, LLM-powered applications and automations that take real work off your teams: secure, measurable and ready for the EU AI Act. Start your AI project How we work AI development services AI that ships, not AI that demos Four ways we put AI to work for your business. AI agents & automation Agents that take over one recurring job (triage, reporting, data entry, follow-ups) connected to your tools. LLM apps & copilots Assistants and copilots built on Claude, GPT, Gemini or open-source models, working on your own data. RAG & knowledge search Answers from your documents, wikis and databases, with sources cited, so every answer can be checked. AI product development New AI-native products from MVP to scale, the way we built Drimt and Kookia in our own studio. AI development What is AI development? AI development is the design and engineering of software that uses AI models, such as large language models (LLMs), to understand information, make decisions and take actions. In practice: agents that take over recurring work, copilots that answer from your own documents, and products with AI at their core. The hard part isn’t the model. It’s the data, the integrations, the guardrails and the follow-through that make AI reliable in production. - Use cases chosen for measurable value - Connected to your data and tools - Evaluated, monitored and cost-controlled Production AI Built for production from the first sprint Most AI projects stall between the demo and production. We close that gap with the engineering practices that make AI dependable at work. - Evaluation sets that measure quality before every release - Guardrails and human approval for high-impact actions - Logging and observability for every agent step - The right model per task to keep running costs down Built in our own studio Drimt: AI that reads risk continuously Drimt is the AI-powered digital risk platform we built in-house: an agentic AI, an MCP server and an on-premise copilot dashboard that bring ESG, governance, cyber and reputational risk into one view. It’s backed by an EU GenAI subsidy, and it’s how we prove we build what we advise. Read the Drimt story Secure & compliant Ready for the EU AI Act and GDPR AI in Europe has to be trustworthy by law. We classify each system under the EU AI Act, keep data where it belongs (EU cloud, private or on-premise) and document how it’s processed for GDPR. - Risk classification and documentation under the AI Act - EU hosting, private and on-premise options - Least-privilege access and full audit logs Security Audit & Compliance How we work Our AI development process From the first use case to an agent your team relies on every day. Think it Step 01 Find the use case A two-day Co-Thinking workshop to pick one recurring, measurable job where AI pays off. 01 Step 02 Write the spec Goals, data, guardrails and acceptance criteria agreed before any code: spec-driven development. 02 Build it Step 03 Prototype on real data A working prototype on your data, scored against an evaluation set so quality is measured. 03 Step 04 Ship to production Integrated with your tools, with guardrails, human approval, logging and cost control. 04 Grow it Step 05 Measure & improve Monitoring, evaluations and new capabilities as models and your needs evolve. 05 Compare Custom AI development vs off-the-shelf AI tools vs building in-house Off-the-shelf tools are great for generic tasks. Here’s when custom AI development makes the difference. Comparison of custom AI development with Co-Labs, off-the-shelf AI tools and building an in-house AI team Criteria Co-Labs custom AI Off-the-shelf AI tools Building in-house Best for Workflows specific to your business Generic tasks like writing and summarising Companies with an established AI team Works on your data & systems Connected through APIs and MCP Limited: copy-paste or plugins Yes, once the team is in place Time to first value Weeks for a narrow agent Immediate Months of hiring and ramp-up Data control & hosting EU cloud, private or on-premise The vendor's terms Full Quality measurement Evaluations built in None for your use case Needs to be built Up-front cost Medium Lowest: a subscription Highest Case studies & insights AI we’ve built and what we’ve learned Ventures Kookia : eat well, we take care of the rest Almost everyone knows they should eat better. Very few actually change. The gap between knowing and doing is where diet quietly turns into disease, and where most… Read the article Learnings AI Agents for the Day-to-Day: Build the Boring One First Everyone wants an autonomous coworker. The agents that actually earn their keep are small, narrow, and dull. Here's how to build one, and the tools worth using in 2026. Read the article Learnings Spec-Driven Development for AI: Write the Spec, Not the Prompt What changes when the specification, not the code, becomes the thing you build and maintain, the tools that make it work in 2026, and how we approach it as a studio. Read the article More insights FAQ AI development questions, answered Can’t find your answer here? Ask the team directly. Ask us a question What does an AI development company do? An AI development company designs, builds and runs software that uses AI models to understand, decide and act. At Co-Labs that means finding the use cases worth automating, building AI agents, LLM applications and RAG systems on your data, integrating them with your tools, and keeping them accurate, secure and cost-efficient in production. What is the difference between an AI agent and a chatbot? A chatbot answers questions; an AI agent gets work done. An agent combines a model that reasons, tools that let it act (email, calendar, CRM, files or your own APIs, often through the Model Context Protocol (MCP)) and a loop with memory, so it can complete a recurring job end to end, with a human approving the steps that matter. How long does it take to build an AI agent or AI application? A narrow agent that does one recurring job well can usually reach production in weeks, because the scope is small by design. Larger AI products, such as copilots on your company data or new AI-native platforms, take a few months. Every project starts with a two-day Co-Thinking workshop that sets the scope and the timeline. How much does AI development cost? Cost depends on the scope, the integrations and the model usage in production. We scope the project in a two-day Co-Thinking workshop and give you an estimate for both the build and the running costs. We keep running costs under control by matching each task to the right model: a small, fast model where it's enough, a stronger one only where judgment is needed. Which AI models and frameworks do you work with? We are model-agnostic. We work with Claude (Anthropic), GPT (OpenAI), Gemini (Google) and open-source models that can run on your own infrastructure, and we build mostly in TypeScript and Python with frameworks such as the Vercel AI SDK, Mastra and LangGraph. We pick per task, and design so you can switch models later. Is our data safe? Will it be used to train AI models? We design for data control. We use business API tiers that don't train on your data by default, host in the EU where needed, and offer private or on-premise deployments for sensitive data. Agents only get access to what their job requires, and every action is logged. Are your AI solutions compliant with the EU AI Act and GDPR? We build for it from the start. The EU AI Act entered into force in August 2024 and applies in phases: we classify each system's risk level, document data flows for GDPR, and build in human oversight, logging and transparency where they are required. Our Security Audit & Compliance service can also review AI systems you already run. Where should we start with AI? Start with the boring one. Pick a single recurring, measurable job (reporting, triage, data entry) and automate that first. It pays off fast, builds trust in the team, and gives you the foundations (data access, guardrails, monitoring) for the next use case. Our two-day Co-Thinking workshop is designed to find that first use case. More services Explore our other services Websites Web apps E-commerce Web Development Custom websites, web applications and e-commerce platforms, fast, secure and SEO-ready. Learn more Engineers Designers AI builders Seniors IT Recruitment & Staffing Senior engineers, designers and AI builders, hired or embedded, vetted by people who ship. Learn more GDPR NIS2 ISO 27001 AI Act Security Audit & Compliance A senior-led audit of code, cloud and data, mapped to GDPR, NIS2, ISO 27001 and the AI Act. Learn more Have an AI use case in mind? Let's find the one that pays off first Start your AI project Home / Services / AI Development