Custom AI Systems
We embed with your team and build AI systems for your workflows. It starts with a five-day AI Roadmap, then a working prototype on your real data, then production.
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From roadmap to production
AI Roadmap
The best ways to automate and improve your product with AI: what to build, in what order, at what cost.
Prototype
We take roadmap item #1 and build a working prototype on your real data, inside your team. 50% of the Roadmap is credited here.
Production & handover
Shipped to production with evaluation, monitoring, and documentation. Your team keeps the keys; we stay as long as needed.
Multi-agent systems, RAG, and workflow automation
Scoped to your workflow and your data, built to run in production.
Multi-agent systems
Specialized agents that plan, retrieve, calculate, and validate, coordinated into workflows too complex for a single prompt.
Assistants on your data
Retrieval systems (RAG) that answer from your own documents and databases, with citations and controlled responses.
Workflow automation
AI wired into your CRM, ERP, and internal tools, so structured work happens without manual entry.
AI products end to end
Full applications with AI at the core: backend, pipeline, guardrails, observability, and the app around it.
Built and shipped
A sample of public projects. Much of our work runs under NDA.
Multi-agent systemFinancial analysis agents for an enterprise planning platform
Pigment’s users needed to run complex, multi-step financial analyses that a single-agent chatbot couldn’t handle reliably. We designed and shipped a production multi-agent system where planning, retrieval, calculation, and validation agents coordinate each analysis, so enterprise teams reason over financial data reliably at scale.
Healthcare appA secure medical speech-analysis app for a national research institute
For the CNRS TALanT research program, we built and maintain the full mobile app and its processing pipeline: secure audio capture, automatic speech recognition, speaker diarization, and OCR for structured forms, through to automatic transcription and report generation. Deployed end to end on HDS-certified, GDPR-compliant infrastructure for sensitive research data.
An end-to-end AI pipeline inside a consumer app
A consumer app needed its first production AI service, from safety to generation. We shipped a four-block pipeline: guardrail classification, vision analysis of user-submitted images, user-context compilation, and structured content generation. It runs with async orchestration, tracing, and prompt management, plus a back office where the team tests and debugs every block.
RAG & SEOAI-powered SEO for machine translation at scale
Automated translation had to stay accurate on technical terms without hurting search rankings. We prototyped and validated AI-driven SEO features: keyword extraction, SEO-aware translation that preserves domain terminology, and vision-generated alt text, with tracing on every LLM output.
NLP in productionThe RAG architecture behind a writing assistant
Generic grammar checking couldn’t cover the product’s needs. We designed the full RAG architecture for MerciApp’s conversational writing features: chunking strategies, embeddings, PGVector retrieval, reranking, and observability. The team shipped this blueprint into the live product.
A natural-language CRM interface for an investment team
Deal data entry into the CRM was manual and easy to skip. We built a natural-language interface connected to the CRM through Telegram: the team updates records from where they already work, and structured data lands automatically, with no new tool to learn.
AI Roadmap
5 daysFive days to a concrete plan: the best ways to automate and improve your product with AI.
For
Founders and CTOs of SaaS & scale-ups who know AI must enter the product or ops, but have no roadmap. Already know what you want to build? The same five days validate it, scope it, and price it.
Not included
Production code and vendor negotiation. That's what keeps the price fixed.
You get
- → A 90-day plan: what to build, in what order, at what cost
- → The target architecture to build it on
- → Everything in writing, walked through in a 1-hour readout
€7,900 fixed (US: $9,900)
50% credited if you launch roadmap item #1 with us within 60 days. The roadmap is yours either way.
Forward-deployed engineering
We work inside your team, your tools, and your stack, not from the other side of a spec document.
We work inside your team
Your repos, your tickets, your standups. Decisions get made in days because the people building are in the room where the workflow lives.
We build in your infrastructure
Under your security and data constraints, so what we ship is something your team can run, audit, and extend after we leave.
We deliver in production
A demo is not the deliverable. We stay until the system runs in production, with evaluation, monitoring, and a clean handover.
Questions from teams
Do we have to start with the AI Roadmap?
Yes, every build starts there. If you already have a scoped use case, the same five days validate it, scope it, and price it. And 50% of the Roadmap is credited when we launch roadmap item #1 together within 60 days.
What does “forward-deployed” actually mean?
We work inside your team for the length of the build: your repos, your tools, your meetings. You are not sending specs to a dev shop; the people building sit where the workflow lives.
How fast do we see something working?
A working prototype on your real data typically lands within 2 to 4 weeks. Production timelines depend on integrations and compliance, and we set them together at the scoping call.
Which stack and models do you use?
Yours first. We build in your infrastructure and pick models per task, cost, and data constraints: commercial APIs or self-hosted. We are not tied to any vendor.
Who owns the code and the system?
You do. Everything ships with documentation, evaluation, and handover. Nothing depends on us staying.
Can you work under strict data constraints?
Yes. We have shipped under French healthcare-data rules (HDS-certified hosting) and GDPR: encryption, audit logging, data residency, and deletion procedures are part of the build, not an afterthought.
What happens after delivery?
Your call. Some teams take the keys and run; others keep us on support and maintenance, or move straight to the next workflow.
Start with one workflow
A 30-minute build call: your workflow, your data, and what we would ship first. No obligation.
- 30 minutes
- You leave knowing what to build
You'll talk directly to Augustin or Robin, the co-founders.
Let's talk about your project
Pick a slot below. 30 minutes with a founder, no obligation.
Rather write than talk?
Send us a message. It lands in our inbox and we answer personally.