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.
DJBRAUTOMATION
Systems that run.
Not promises.
Code in production.
AI automation studio: we design autonomous agents and custom systems with the most advanced AI tooling — Claude Code, multi-level agents, RAG, MCP — and ship them to production.
Built with the most advanced AI tools
- Claude Code
- Claude Design
- Claude Cowork
- Autonomous agents
- RAG
- MCP
- n8n
- Supabase
01 — THE PROBLEM
Your days go to tasks a machine would do better.
Data you can't use
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.
Tools that don't talk to each other
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.
02 — WHO IT'S FOR
Built for people who want systems, not slides.
01
You sell online
Store, catalog, product listings, support, content: an autonomous agent can run part of that work 24/7, under your approval.
02
You run a shop or a restaurant
Stock, orders, reporting, follow-ups: the tasks that hinge on one person become a reliable system that runs on its own.
03
You're a consultant or content creator
A pipeline turns your expertise into multi-format publications — post, carousel, video — without eating your evenings, and nothing ships without your go-ahead.
04
You're launching a digital product or service
Sales funnel, payment, onboarding, back office: we build the complete system, with AI placed exactly where it actually adds something.
03 — WHAT WE DO
Four tiers. Yours is the simplest one that fixes your pain.
Four progressive tiers — each with a written definition of done.
Audit & essential automations
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.
Custom AI agents
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), 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.
Knowledge systems (RAG)
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.
Automation-first web & mobile development
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 method04 — OUR AI EDGE
We operate at the frontier of AI tooling.
Most providers just call an API and paste the answer back. We design agent systems — directed, guardrailed, shipped to production.
Agent-driven development
Claude Code: we build entire systems by directing agents (brainstorm → design → plan → implementation → tests), not by pasting code.
Multi-agent orchestration
An autonomous agent runs a full cycle on its own, on a schedule: creation → review → publishing → follow-up. Two levels of AI, cleanly separated.
Grounded generation (in-house RAG)
Generation is constrained to a knowledge base and validated against a schema — traceable sources, zero hallucination.
Integrations via MCP
The MCP protocol connects tools cleanly (publishing, video, database) — a controlled integration layer, not brittle scripts.
Human in the loop
Nothing reaches production without explicit human approval. A design choice, not a limitation.
The right level of AI
A deterministic workflow when possible, an AI agent when necessary. Sometimes the right answer is: you don't need AI.
Every system we ship applies these principles — verifiable in our work.
05 — WORK
Three systems in production. Verifiable.
Every project shown here is a real system — delivered and documented.
06 — FAQ
Frequently asked questions
How much does it cost, and how do you bill?
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.
How long does it take?
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.
What happens after delivery?
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.
Which AI tools and models do you use?
We build with Claude Code (agent-driven systems), operate with in-house autonomous agents (a Hermes-style framework), ground generation with an in-house RAG, connect tools via MCP, and orchestrate the deterministic parts with n8n. We pick the right tool 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.
What if the AI gets it wrong?
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".
What about our data? GDPR, confidentiality?
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.
Who owns the code?
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.
Do you work remotely? In English?
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.
Let's talk about the task that costs you the most time.
30 minutes, free — including if the conclusion is that you don't need AI.