Deploy the stack
Our internal agent stack, deployed on your infrastructure
Autonomous agents that plan multi-step work and act across your systems: filing records, processing documents, running onboarding flows end to end. Set up by one senior engineer who runs this stack every day, inside guardrails that hold.
Free 30-min call · You leave with a policy and deployment plan, not a sales deck
Teams we ship for
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
Agents that can act are agents that must be contained.
The agent tooling everyone is installing ships with single-user defaults: full file access, open network, no audit trail. Powerful, and unshippable in a company that handles customer data, financial records or anything a regulator cares about.
Unconstrained actions
Left on defaults, an autonomous agent can read any file on the host, call any endpoint and spawn any process. One bad prompt or one misconfigured agent is enough to exfiltrate data or fire real actions into your production systems.
Compliance gaps
Default setups route every prompt, plus whatever context rides along with it, through external APIs with no record of what left the network. Under GDPR or any serious internal governance, that is exposure nobody can sign off on.
Deny-by-default policies
Our setup blocks everything not explicitly whitelisted: network egress, filesystem paths, command execution. Sandboxed runs, approval gates on risky actions, and a log of every move, so autonomy never turns into chaos.
Agent autonomy without agent chaos.
Agents that can act on your systems need a security layer around them. We install the guardrails first, then let the agents work.
A hosted assistant keeps your data on someone else's servers. The stack runs on infrastructure you own, where agents plan multi-step tasks and take real action across your systems: filing a CRM record, processing an invoice, running an onboarding flow start to finish.
Four phases from zero to a production agent fleet
A structured, four-phase engagement designed to take your team from zero to production-grade agents with full security controls.
Discovery and audit
We map your infrastructure, compliance requirements, existing workflows and the highest-impact automation candidates.
Architecture and policy
We design the stack for your environment, write the permission policies as code, and plan what may run where, including what never leaves your perimeter.
Deploy and integrate
We install the stack, connect agents to your CRM, ERP and internal tools, and run a controlled pilot on a single use case.
Harden and scale
Production hardening, monitoring dashboards, team training, and support as the fleet extends to new workflows.
The use cases we deploy most often
Each one starts as a scoped pilot on a single workflow, then scales once the guardrails have proven themselves.
Email triage and response. The inbox read, sorted and answered in draft: hours of manual processing become a short review of prioritised responses, with send always behind a human.
Invoice and document processing. PDFs parsed, amounts and line items extracted and routed into the accounting system, with an approval gate wherever the amount justifies a human look.
CRM automation. Calls logged, records updated and follow-up sequences fired in HubSpot, Salesforce or whatever you already run, through endpoints the policy explicitly whitelists.
Client onboarding flows. A multi-step checklist compressed into one automated sequence: accounts provisioned, documents requested, status visible, a human pinged only where a decision is needed.
DevOps and code automation. CI monitored, incidents triaged and routine infrastructure chores executed by agents whose shell access stops at the commands on the allowlist.
Compliance reporting. Data gathered across systems into audit-ready reports on schedule, sources attached, by an agent that can read those systems but not alter them.
What we deploy, end to end.
We do not hand you a manual and walk away. One engagement covers the whole lifecycle, from the first audit to a hardened fleet your team operates in its own accounts.
Full-stack deployment
- Infrastructure and compliance audit: compute, network, data flows and regulatory constraints mapped before a single agent runs
- Stack installation on your infrastructure: orchestration, sandboxed runtime and policy engine, in your accounts
- Policy writing against your framework: permission rules drafted as versioned config for GDPR or your internal governance, reviewed with your team
- Agent workflow design: each use case specified, built and tested against real cases before it touches production
Production hardening
- Network egress on whitelist only: an agent cannot call an endpoint nobody approved
- Filesystem isolation: each agent sees the directories its job requires and nothing else
- Inference routing by sensitivity: regulated data stays inside your perimeter, the rest follows your cost and privacy policy
- Monitoring dashboards and alerting: every action logged, every policy violation surfaced to a human
DIY setup vs deployed with us.
You can have an open-source agent running on a laptop this afternoon. Getting it to production, with enforcement, isolation and an audit trail, is the infrastructure work we deliver.
| Aspect | DIY install | Deployed with us |
|---|---|---|
| Time to production | Running in an afternoon, safe for real data much later, if ever | Two weeks to a live pilot already running behind enforced policies |
| Permissions | Defaults: every file, every endpoint, every command the process can reach | Deny-by-default: each permission whitelisted per agent in versioned policy |
| Secrets and data | Credentials in environment variables, context free to leave with every prompt | Scoped secrets, controlled egress, sensitive data kept inside your perimeter |
| When something breaks | You reconstruct what the agent did from whatever logs happen to exist | Violations blocked at runtime, alerts fire, and the playbook says who does what |
The stack behind every deployment 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]
Get your questions answered
Get answers to common questions about our automation process, pricing, and results.
The same stack we run internally: Claude-based agents orchestrated through MCP and n8n, running on your infrastructure, with sandboxed execution and explicit permissions for every tool they touch.
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.
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