Lab d'Implémentation
Sprint de Validation IA
Un engagement structuré de deux semaines qui établit la faisabilité technique et la valeur métier avant tout engagement en production.
Risk-managed
Defined scope and success criteria agreed before work begins. No open-ended commitments.
Evidence-based
A working prototype against your data — not a presentation or theoretical assessment.
Decision-ready
Structured readout with a clear recommendation on feasibility, risk, and next steps.
Structure du Sprint
Deux semaines, quatre phases.
Chaque sprint suit une méthodologie structurée conçue pour maximiser le signal de faisabilité dans un cadre délimité — avec l'accès aux données confirmé en amont, et une décision claire en sortie.
01
Discovery & Scoping
Structured stakeholder interviews to define the use case, success criteria, data requirements, and constraints. We conduct a preliminary data audit and confirm access logistics so that no time is lost when building starts.
02
Technical Design
Architecture selection, toolchain decisions, security and compliance review. We design the minimal system required to generate a meaningful signal on feasibility — and surface any blockers before a line of code is written.
03
Build & Validate
Focused engineering sprint producing a working prototype against your actual data and environment. Human-in-the-loop controls and audit logging are included by default. You are kept informed throughout.
04
Findings & Recommendation
A structured readout covering technical findings, business case assessment, risk profile, and a clear recommendation on whether and how to proceed. You leave with a decision — not a presentation.
Prerequisite
Data access must be confirmed before the sprint starts. We do not build against placeholder or synthetic data — the prototype must run against your real environment to generate a meaningful signal. This is typically agreed during the discovery call.
Domaines Applicables
Ce que nous validons.
La méthodologie sprint s'applique à un large éventail de cas d'usage IA en entreprise. Nous évaluons chaque opportunité pour sa faisabilité technique et son profil de risque réglementaire lors de la phase de cadrage.
- Intelligent document processing and extraction
- Conversational AI and enterprise knowledge assistants
- Computer vision for quality control and inspection
- Process automation with agentic workflows
- Predictive analytics and anomaly detection
- Custom LLM integration and RAG architectures
Lab d'Implémentation
Commencez par un appel de découverte de 30 minutes.
Nous évaluerons la pertinence de votre cas d'usage, estimerons la portée requise et présenterons ce qu'un engagement sprint peut délivrer.
Planifier un Appel de Découverte