Artificial Intelligence Agents
A chatbot answers questions. An AI agent carries out tasks: it reads an email, decides what to do with it, updates a system, and only calls a person in when the decision needs human judgement.
We build autonomous agents with LangGraph and LangChain for companies that want the work to happen without someone supervising every step.
The problem this solves
Some work isn't conversational, but it isn't simple fixed-rule automation either. Qualifying a lead means weighing up context. Answering an email means grasping intent. Triaging a request means deciding where it should go next.
Traditionally this kind of work requires a person. A well-built agent can make the first pass on its own, and escalate only what genuinely needs a human decision.
How it works
Diagnosis
We define where simple automation ends and the need for judgement begins. Not everything needs an agent, and we say so when that's the case.
Implementation
We build the agent on a RAG architecture, connected to your company's documents and systems, so that decisions rest on your real context rather than generic assumptions.
Results
We monitor how the agent behaves in production and adjust the boundaries between what it decides alone and what it escalates.
Real proof
It isn't only what we sell, it's what we use. Our own commercial operation — prospecting, qualification, follow-up — runs on the same multi-agent architecture with LangGraph that we build for clients. If the technology weren't solid enough, we wouldn't trust it with our own business.
Who this makes sense for
It makes sense for workloads where most cases follow a predictable pattern but still call for some interpretation: lead qualification, request triage, first response to emails. It does not make sense for high-risk or low-volume decisions, where the cost of building the agent doesn't pay off.
Technology
LangGraph, LangChain, RAG, Claude AI, FastAPI.
- LangGraph
- LangChain
- RAG
- Claude AI
- FastAPI
Frequently asked questions
Can the agent act with no supervision at all?
We always set the limits of autonomous decision-making during the diagnosis phase. Higher-impact decisions go through a person.
How does the agent know about my company?
Through a RAG architecture, connected to your real documents, policies and systems.
Is this different from a chatbot?
Yes. A chatbot talks. An agent carries out tasks and takes decisions within defined limits.