Autonomous agents
They plan, act, and self-correct until the set goal is reached.
AI agents
AI agents that act, not just chat.
Beyond the chatbot: we build AI agents that reason toward a goal, use your tools through their APIs, and carry tasks to completion — with guardrails you control.
Reasoning + tool useGuardrails and bounded loopsClaude · APIs · function calling
The problem
A chatbot answers; an agent does the work
- Your assistant answers but can’t actually execute anything.
- Multi-step tasks stay stuck between your tools.
- Raw LLMs hallucinate and have no limits on what they’ll do.
- You’re wary of letting an AI act with no control or audit trail.
Our solution
We design agents with a bounded reasoning loop and a precise toolset: they pick an action, run it through your APIs, check the result, and stop when the goal is met — every step logged.
- Tools defined with explicit permissions — never unbounded access.
- Optional human approval before any sensitive action.
- Full logs of every decision and tool call.
What we deliver
Agents built for production
Not flashy demos that break — reliable, bounded, monitored agents.
Tool use (function calling)
The agent calls your APIs, databases, and services like a colleague would.
Multi-step workflows
Tasks that chain across several systems, from start to finish.
Bounded loops & reliability
A capped number of iterations, clean retries, and predictable behavior.
Guardrails & safety
Explicit permissions, human approval, and protection against injection.
Observability
Every reasoning step and tool call is traced, measured, and auditable.
Proof
AI systems already in service
Agents and assistants we designed and shipped.
CRM & automationConciergerie CRMFaster client replies and nothing slipping through.Next.js · Supabase · n8n · Claude
Data & AIAtlas RAGFaster information retrieval, sourced answers with no hallucination.RAG · Gemini · Supabase · n8n
AI & automationNanoAds90% reduction in ad-creation time.Next.js · Gemini · Stripe
Process
From goal to agent in production
01
Goal scoping
We define what the agent must accomplish — and its strict limits.
02
Tools & permissions
We expose the right tools with precise, revocable access.
03
Loop & guardrails
We tune the reasoning loop, approvals, and retries.
04
Launch & monitor
Deployment with logs, alerts, and continuous improvement.
FAQ
What clients ask
What’s the difference between an AI agent and a chatbot?
A chatbot answers questions. An agent pursues a goal: it reasons, uses your tools through their APIs, and completes a whole task — drafting a quote, updating a CRM, processing an order — instead of just describing what it would do.
How do you stop an agent from going off the rails?
By design: a bounded reasoning loop, a limited toolset with explicit permissions, human approval on sensitive actions, and full logs. The agent can only do what you explicitly allow it to do.
Which models do you use?
We work mainly with Claude for its reliability on tool use, and pick the model by task, cost, and latency. The architecture stays model-agnostic so you can swap models without a rewrite.
Can the agent connect to our existing systems?
Yes. The agent calls your tools through their APIs — CRM, ERP, database, email, internal services. If no connector exists, we build one.
How long to a first agent?
A first agent focused on a clear task usually ships in two to four weeks, depending on the number of tools to integrate and the level of guardrails required.
What happens if the agent gets it wrong?
Sensitive actions go through human approval, retries are clean, and every decision is logged. If something goes wrong, you see exactly what happened and we tighten the guardrails.
Hand the task to an agent.
A 30-minute call is enough to identify the first agent that will work for you.