Repetitive tasks
Data entry, follow-ups, reporting, product listings, answering the same questions. Each takes ten minutes; together they eat hours every week — yours, or those of someone you pay.
AI automation studio. We remove your repetitive tasks, cut human errors and give you back hours every week — with custom agents and systems, shipped to production. Not promises.
Data entry, follow-ups, reporting, product listings, answering the same questions. Each takes ten minutes; together they eat hours every week — yours, or those of someone you pay.
Your customer history, documents and processes exist — scattered across files, inboxes and one person's memory. That data is an asset. Without a system that makes it usable, it sits idle.
Store, till, spreadsheet, WhatsApp, email: the information exists somewhere, but a human copies it from one tool to the next. Every copy costs time and opens the door to an error.
Store, catalog, product listings, support, content: an autonomous agent can run part of that work 24/7, under your approval.
Stock, orders, reporting, follow-ups: the tasks that hinge on one person become a reliable system that runs on its own.
A pipeline turns your expertise into multi-format publications — post, carousel, video — without eating your evenings, and nothing ships without your go-ahead.
Sales funnel, payment, onboarding, back office: we build the complete system, with AI placed exactly where it actually adds something.
Four progressive tiers — each with a written definition of done.
Manual copying between tools, missed follow-ups, hand-built reports.
An audit of your triggers, n8n workflows in production, handover documentation.
Done = the agreed workflows run in production without intervention, and the metric defined at the audit is being measured.
Tasks that require reading, sorting, writing or deciding — beyond what a pure workflow can do.
An agent in production on your channels (email, WhatsApp/Telegram, back office), powered by our Hermes framework, with explicit guardrails and a written "what stays human" document.
Done = the agent handles the cases defined at scoping on its own; anything outside that scope is routed to a human.
Your company knowledge is buried in documents and history nobody can query.
A structured corpus and a question-answering system — with an open-source-model, self-hosted option for sensitive data.
Done = the test questions defined at scoping get correct, sourced answers.
You need a complete business tool — inventory, booking, back office — that generic SaaS doesn't cover.
A web and/or mobile application in production, with automation built in (crons, notifications, invoicing) and a full handover.
Done = the application is in production, the team uses it daily, handover documentation is delivered.
The right tier is the simplest one that fixes your pain — not the most expensive one.
Offer details and methodNo grey areas. At every step you know what we're doing, what you receive, and what stays under your control.
We analyse your current processes and pinpoint the bottlenecks: the tasks that cost the most time and the places where automation actually moves the needle.
You leave with a clear read on what's automatable — even if you don't work with us.
We listen to your business, your tools and your real constraints. Together we lock the scope, the success metric and the definition of "done".
A written spec and a fixed-scope quote — no open-ended hourly billing that drifts.
We design the automation architecture that fits your existing tools — a deterministic workflow when it's enough, an AI agent when it's needed, never AI for AI's sake.
A solution built for your stack, with guardrails and "what stays human" defined up front.
We ship your workflows to production, test them on real cases, and train your team to run them on their own.
A production system, documented, that your team owns — plus a monitoring plan if you want one.
No commitment · 30 min · remote
Most providers just call an API and paste the answer back. We design agent systems — directed, guardrailed, shipped to production.
Claude Code: we build entire systems by directing agents (brainstorm → design → plan → implementation → tests), not by pasting code.
Most providers just wire n8n workflows. We built Hermes: our own open-source autonomous-agent framework. Anything n8n orchestrates, a Hermes agent does too — and it can also read, decide and adapt. A full cycle run on its own, on a schedule. Already in production.
Generation is constrained to a knowledge base and validated against a schema — traceable sources, zero hallucination.
The MCP protocol connects tools cleanly (publishing, video, database) — a controlled integration layer, not brittle scripts.
Nothing reaches production without explicit human approval. A design choice, not a limitation.
A deterministic workflow when possible, an autonomous agent when needed — from n8n to our own Hermes framework, we're tied to no single tool. And sometimes the right answer is even: you don't need AI.
Every system we ship applies these principles — verifiable in our work.
Every project shown here is a real system — delivered and documented.
Every project starts with a free scoping call, followed by a quote on a defined scope — the success metric and the definition of done are written into the quote. No open-ended hourly billing: scope is closed before the first line of code. Tier 1 (audit + essential workflows) is the lowest-cost entry point.
Timelines are set in writing at scoping, tier by tier. A simple n8n workflow is measured in days; an autonomous agent or an application, in weeks. Because scope is closed up front, so is the delivery date.
Every delivery includes operating documentation and a handover. After that, two options: your team runs the system on its own, or a monitoring-and-evolution retainer is defined case by case.
We build with Claude Code (agent-driven systems), operate with Hermes — our own open-source autonomous-agent framework —, ground generation with an in-house RAG, connect tools via MCP, and orchestrate the deterministic parts with n8n. We're tied to no single tool: we pick the right one for the need — not one model applied to everything. When a local model is enough, we use it; when the best reasoning model is required, we use that too.
The answer is architectural, not rhetorical. Deterministic workflows first, wherever possible — a workflow doesn't hallucinate. Where an AI agent is needed, it runs inside guardrails: immutable rules, logging, human approval for any sensitive action. Generation is grounded in a knowledge base and validated against a schema. Every case study documents "what stays human".
Your data never passes through a service that isn't under contract with you. For sensitive data, there is an option: open-source models and processing hosted on your own infrastructure. This is not theoretical — one of our agents in production computes its semantic memory on its own server, with a local model: no data sent to an embeddings cloud.
You do. Delivered code is yours, with its documentation. The stack is standard (n8n, Supabase, Next.js, Python, Node.js): any developer can take the system over without us. Part of our work is public, under the MIT license — so you can judge the transparency before signing.
Yes. Our systems are designed and delivered remotely, fully remote. Working languages are French and Arabic; documentation, code and specifications are written in English when the project calls for it.
A free 30-minute audit — including if the conclusion is that you don't need AI.