AI Agents & Agentic Systems
Your team spends hours on tasks that should run on their own. But launching AI agents without understanding your operations is how companies waste budgets.
Most companies developing agentic AI systems will build you an agent for any process you point at. They demo it. It looks impressive. Then it hits your real data, your real workflows, your real edge cases - and it breaks.
We have seen this pattern across dozens of projects. A client comes to us after spending months with another vendor on an AI bot that looked great in a sandbox but failed in production. The reason is almost always the same: nobody studied the business process before writing the first line of code.
That is why our approach to AI agents development starts differently.
We research your business before we write a single prompt
Before we build any custom AI agents, our team maps your actual workflows. We sit with your people - the ones who do the work every day - and document what really happens. Not what the process chart says. Not what the manager assumes. What actually happens at 3pm on a Friday when the system is overloaded and the data is messy.
In our experience, this research phase is where we find the biggest wins. Sometimes we discover that the process a client wants to automate with agents for automation is actually broken at a more basic level. Wrong data flows. Duplicate steps. Manual workarounds that nobody documented. Fixing those first often delivers more value than any autonomous agent ever could.
Our CTO Pavel Janko often says: "An intelligent agent built on a broken process just breaks faster."
Where autonomous agents actually work - and where they don't
A pattern we notice across projects: companies hear "AI agents" and imagine a system that handles everything from customer emails to financial reporting to inventory management. The reality is more specific.
Custom AI agents deliver real results when your process has clear inputs and outputs, when decisions follow patterns your team can describe, and when the cost of errors is manageable. Think order processing, document review, data extraction from emails, customer support triage, or automated reporting across multiple systems.
AI-powered automation is the wrong answer when your process depends heavily on human judgment, when your data is inconsistent or incomplete, or when the stakes of a wrong decision are too high for autonomous action. We will tell you this directly. What most companies get wrong about agentic systems development is assuming every process needs autonomy. Some processes need better tools, not agents.
How we build agentic systems that stay in production
Once we confirm where intelligent agents will deliver measurable value, we build them to last. Not as a demo. Not as a proof of concept that lives in a slide deck. As a system your team uses every day.
Our engineers build each agent around your existing tools - your CRM, your ERP, your internal databases. We design custom AI solutions that fit into how your company already works, instead of forcing your team to change their workflow around a new tool.
What we have seen working with clients like JLL and Saint-Gobain is that the agents that survive in production are the ones built with full context of the business. When we were working on a similar project for a logistics company, our team mapped not just the process we were automating, but every system it touched - invoicing, accounting, warehouse management, compliance certificates. That depth is what separates an agent that works from an agent that creates new problems.
What you get from a custom AI agents company that says "no" first
Here is what we think is really going on in the AI agents market right now: most vendors are selling the technology, not the outcome. They will build you a multi-agent system because you asked for one, not because you need one.
We take a different approach. Our team of senior engineers and business consultants reviews your operations, identifies where AI-driven automation will deliver real ROI, and - just as importantly - tells you where it will not. We have turned down agent projects and recommended simpler solutions when that was the honest answer. Sometimes a well-built CRM integration saves more time than any autonomous bot.
This honesty is why 63% of our clients come back for more projects. They trust us to recommend what actually works.
Start with a process review, not a sales pitch
If you are considering agentic systems development for your business, here is what we suggest: book a 30-minute call with our team. We will ask about your operations, your pain points, and where you think an intelligent agent could help. Then we will give you an honest assessment - including whether AI-powered automation is the right solution at all.
No demos of pre-built bots. No generic pitch decks. Just a direct conversation with the engineers who will do the work.
Book a free 30-min process review call.
Frequently Asked Questions
Yes. Most of our clients are in the UK, USA, and across Europe. Our team works across time zones, and we regularly fly to meet clients in person - especially during the research and discovery phase.
Every agent we build operates within defined rules and escalation paths. Autonomous does not mean unsupervised. We set clear boundaries for what the agent can decide on its own and when it should involve a human. All decisions are logged and auditable.
We will tell you. In our experience, about 30% of the processes clients want to automate with intelligent agents are better served by simpler solutions - a custom integration, a workflow tool, or fixing the underlying data issue first. We would rather give you the right answer than sell you the most expensive one.
Yes. We build agents that integrate with your current CRM, ERP, databases, and internal tools. Our team has 14 years of experience connecting complex business systems, so we know how to work with legacy environments, messy data, and undocumented workflows.
It depends on complexity. A focused single-process agent typically takes 4-8 weeks from research to production. Multi-agent systems with complex integrations take 3-6 months. But the research phase - understanding your business and mapping the right processes - takes 1-2 weeks and is the most important part.
Jakub Bílý
Head of Business Development