01 / Assistants
GenAI assistant connected to your business
The studio builds a reliable assistant connected to your documents, internal knowledge bases and business tools — genuinely useful for teams that need it.
RAGCloudEvaluationMonitoring
[ 01 — SERVICES ]
Three ways to put GenAI to work
02 / Industrialisation
From GenAI POC to production-ready system
The studio takes an existing LLM prototype and makes it production-ready: observable, monitored, deployable, maintainable by your team.
LLMOpsCI/CDMonitoringEvaluation
03 / Agents
Business AI agents, supervised
The studio designs AI workflows connected to your tools — to automate high-friction tasks with guardrails and human oversight.
OrchestrationAPIsSupervisionEvaluation
GenAI is the studio's core, not its only expertise. It also takes on ML projects — custom models, production deployment — and full-stack developments (APIs, business applications, integrations), and works on a quoted basis for a targeted AI component or a smaller scope.
[ 02 — USE CASES ]
Engagements with a defined scope.
01
Internal assistant connected to product documentation
Sector · 4–6 weeks
RAG over Notion, Confluence and internal changelogs. Reduces time spent by support and product teams searching for existing information.
B2B SaaS vendor
02
Support copilot — prepared responses and triage
Sector · 3–5 weeks
Contextualised response suggestions on incoming tickets, automatic enrichment with relevant client history and context.
Services SMB
03
Agentic document processing workflow
Sector · 5–8 weeks
Structured extraction, classification and routing of incoming technical documents — with human validation on ambiguous cases.
Industry / quality
04
Industrialisation of an existing GenAI POC
Sector · 4–7 weeks
Taking a working LLM prototype that isn't production-ready: adding evaluation, observability, CI/CD, cost management and versioned prompts.
B2B startup
05
AI API integrated into a B2B product
Sector · variable by scope
Adding an AI component (generation, classification, extraction, augmented search) to an existing product — exposed via a clean, monitored, versioned API integrated into the release cycle.
Software vendor
These engagements are presented as scope examples. No confidential client information is published.
[ 03 — CASE STUDY ]
An AI agent shipped to production.
infotrackThe context
E-commerce teams spend hours each week handling repetitive emails — orders, returns, shipping questions — at the expense of genuinely complex cases.
The solution
The studio designed and deployed infotrack: an autonomous agent that reads, triages and responds to incoming emails every 15 minutes. Ambiguous cases are escalated to the business owner via Telegram and held until validation. Deployed as a multi-tenant SaaS on Cloud Run, with a real-time analytics dashboard.
Stack
LangGraphMCPGeminiCloud RunFirestoreNext.js
Live · production90-day window
2 480
emails processed
68%
handled without a human
14s
avg. response time
0%
error rate
after automatic retries
[ 04 — PROCESS ]
Five steps to deliver a production-ready system.
The studio's method across most projects. Each step produces a concrete deliverable and an explicit validation checkpoint.
- 01
Scoping
Understand the real business need, technical constraints and realistic scope for a V1.
- 02
Architecture
Choose the stack, design the data flows, identify guardrails and measurement points.
- 03
Build & integration
Develop the system, integrate with existing tools, wire in observability from the start.
- 04
Evaluation
Measure quality, stabilise under real load, adjust prompts, guardrails and thresholds.
- 05
Deployment
Deploy cleanly to production, hand over runbook and documentation, train the internal team.
[ 05 — THE STUDIO ]
Not another POC. GenAI systems built to last in production — measurable, supervised, and grounded in reality.
100%
Deployed on cloud · controlled
6–14 wks
From scoping to production
1 contact
Design · integration · LLMOps
[ 06 — FAQ ]
Frequently asked questions.
Seven questions that come up in early conversations. If yours isn't listed, write directly — it's faster.
Do you work with SMBs, or only with technical teams?
The studio works with both. SMBs without an AI team benefit just as much as tech teams from a well-built GenAI system — the condition is that there's a real business use case to address, not just the desire to 'have AI'.
Do you only work on GenAI?
No. GenAI is the studio's main expertise, but not the only one. It also takes on ML projects — training and deploying custom models — and full-stack developments, as it has done before: APIs, business applications, integrations. If your need sits at the boundary, the best move is to talk it through.
Do you work on existing POCs?
Yes. Taking an LLM prototype and making it production-ready is one of the studio's three packages (see GenAI / LLMOps Industrialisation). Audit, target architecture, evaluation, monitoring, CI/CD, clean deployment.
Can you also deploy and monitor?
Yes, that's the default posture. Every system delivered is deployed to a clean cloud environment — primarily on GCP / Vertex AI, but also AWS or Azure depending on your existing infrastructure — with its monitoring, guardrails and runbook. No POC delivered as a black box.
Do you work alone, or with partners?
The studio handles every engagement end-to-end. For scopes that require it, we bring in specialist partner providers — design, front-end, specific integrations — always at the same level of rigour and with clear accountability on the studio's side. No opaque subcontracting, no ghost team.
Can we start with a small scope?
Yes. The most effective format is often a short 1 to 2 week scoping engagement — it aligns business need with target architecture before any build, and gives a concrete basis for deciding on a realistic V1.
Do you take custom engagements?
Yes. Beyond the three main packages, the studio takes on specific AI components, APIs or targeted backend/cloud integrations on a quoted basis.
Let's talk
A project, a constraint, or a question?
Describe the context in a few lines — the studio replies with a personalised response within 24 to 48 business hours.