Create a differentiated AI product that generates sustainable value (performance, quality, error reduction, new services), integrates into the customer's ecosystem without unmanageable technical debt, and accelerates learning until adoption by users and, where applicable, by the market.
Our approach
We work as a comprehensive product and AI team in close collaboration with your teams. We move forward in short cycles: scoping, formulating hypotheses, deployment, testing in real conditions, then measurement and iterations. As value and adoption are confirmed, we industrialise in order to empower the project owner, reduce risks and focus efforts on value generation.
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SHAPE
Framing and securing value
We clarify the target use, stakeholders and context using a prototype, formalise key assumptions and measurable success criteria, define the action plan (scope, test protocol, instrumentation and go/no-go decision) and convince 3 to 5 Design Partners, future customers.
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BUILD
Make, industrialise, ensure reliability
We develop the product in short cycles under real-world conditions, measure the impact and iterate (usage, performance, incidents, ROI), then industrialise the foundation (security, MLOps/LLMOps, observability, runbooks).
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RUN
Adopt, transfer, empower
We support adoption (onboarding, change management, support, demo rituals), transfer ownership (governance, roles, backlog, quality and decision criteria) and develop team skills through coaching, documentation and playbooks that promote autonomy.
Why will you love it?
Design, development, impact: we help you develop an AI product and launch it quickly on the market.
A product that finds its market and impact as quickly as possible. Not V-shaped cycles lasting months.
Lean Startup
Product approach (user research, prototyping, UI/UX) and continuous co-construction with business teams.
Assembly
Component selection and assembly (vendor-agnostic approach), business anchoring (data, workflows, constraints).
Production launch
Maintainable production deployment and robust AI/data architecture.
Industrialization
Industrialization (CI/CD, MLOps, supervision, usage/performance monitoring), and documentation for sustainability and transfer.
Apply our proven methods to design high-performance products
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Blacksmiths
Products Manager, Data Engineering, Artificial Intelligence
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Commitment to your Product
