Deploy automation
AI agent development, built by one engineer commanding a fleet of AI agents
Most AI agents die in the demo. Ours run inside real operations: connected to your tools, supervised by your team, and monitored like any other system you depend on.
Free 30-min call · You leave with an agent architecture map, not a sales deck
Agents shipped for teams at
logos à fournir : clients citables
The new AI software engineering
Coding changed. Engineers stopped being the bottleneck.
The bottleneck moved to orchestration. Claude Code is the brain, MCP plugs into your stack, and one senior engineer reviews every line the agents ship. See how we build, automate and ship on every engagement.
- 01Claude Codethe brain · subagents · MCP
- 02Anthropicmanaged agents · runtime
- 03CursorIDE pair-programming
- 04n8ncron · webhooks · glue
- 05Supabasedata · memory · retrieval
Why generic AI tools fail B2B teams.
Handing your team a public AI model is not a strategy. Generic tools were not built to understand how your business actually operates.
Hallucinations and data breaches
Public models train on what you feed them: running sensitive client data or financial reports through them is a security risk, not a convenience. And without your company's context they guess, and a confident wrong answer costs more than a slow right one.
Read-only AI does not run your business
Most commercial AI tools only answer prompts. They cannot log into your CRM, update a record or trigger a billing sequence. They offer an opinion. They do not do the work.
Beyond chatbots: agents that take action.
A co-pilot that only answers questions will not move your numbers. What moves them is a system that takes the action itself. One senior engineer directs a fleet of AI agents that plug directly into your software stack, talk to each other, and execute multi-step processes on their own.
From architecture audit to a system your team runs on
Every engagement follows a fixed sequence, not a template. Each step exists because skipping it is where most agent projects fail in production.
Architecture audit
We map the real process, the tools it touches and where the hours go. Free, and yours to keep.
Agent design
We define what the agent decides, what it never decides, and what the interface looks like for the people supervising it.
Build and integrate
We build it on your stack and connect it to your CRM, inbox, database and messaging, in your accounts.
Deploy with guardrails
Permissions, error handling, alerts and a human checkpoint wherever a mistake would be expensive.
Handoff and iterate
Documentation, training, and monthly iterations as your operations change. Nothing depends on us to keep running.
Where B2B teams put custom agents to work
Support triage. Incoming tickets read, sorted and routed before anyone opens the inbox.
CRM enrichment. Records completed and deduplicated from the sources you already pay for.
Lead qualification. Inbound scored against your real criteria, not a generic template.
Reporting and analysis. The recurring report assembled from live data, in your format.
Document processing. Quotes, invoices and contracts read, extracted and filed.
Internal operations. The small steps between two tools, handled without a human in between.
The stack behind every agent we ship
We do not reinvent the stack for every project. Every engagement runs on the same proven set of tools, swapped only where your systems require it.
Claude Code
The reasoning model behind agent decisions and tool calls
Anthropic
Managed agent runtime for long-running, autonomous tasks
MCP
The protocol that connects agents to your APIs and tools
Cursor
IDE pair-programming where the engineer reviews every diff
n8n
Workflow orchestration for cron jobs, webhooks and handoffs
Supabase
The data layer for agent memory, logs and private retrieval
Vercel
Deployment and hosting for agent-facing apps and dashboards
GitHub
Version control and review for every agent we ship
Everything runs in your accounts and your repositories. Self-hosted where data control matters. [Engagements précis à valider]
Scoped to what the agent actually needs to do.
We do not sell a fixed package sight unseen. The honest number depends on the workflows, the systems we integrate with, and your security requirements.
Single narrow workflow
Scoped after the audit
One agent, one workflow, one or two tool integrations. Ships in days once scoped.
Multi-agent system
Scoped after the audit
Several specialised agents collaborating across deeper integrations, evals and guardrails. Weeks, not months.
Enterprise program
Scoped after the audit
Sandboxed environments, permission and audit controls, agents running across several departments.
Every tier starts with the same free architecture audit. If simpler automation is enough, we say so there.
Built for some teams, honestly wrong for others.
Custom agent development is a serious build, not a subscription. Two minutes here can save you a call.
When custom agent development fits
- The workflow needs to take real actions in your systems, not just answer questions.
- Your data and integrations are specific enough that a generic tool will not fit without heavy workarounds.
- You want a real number after an audit, not a package sold sight unseen.
When it does not
- You need a fixed FAQ chatbot with no actions: a managed platform template already covers that for less.
- You are still scoping whether an agent is warranted at all: start with the free audit instead.
- You are not ready to give the agent access to the systems it needs to act on.
Get your questions answered
Get answers to common questions about our automation process, pricing, and results.
A chatbot responds to prompts. An agent can use tools, follow business logic, update systems, and complete workflows with guardrails, then escalate to a human when it should.
See what your team
can hand to AI
A free 30-minute call. We map one workflow together and you leave with a plan you can use, with or without us. Meeting us at the AI Summit Barcelona on September 22? Grab your slot here.
Book a Free Strategy Call