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 act as co-producer of your AI products, with a results-oriented and evidence-based approach. We bring out high-value uses by capitalizing on what already exists rather than reinventing it. We formulate and evaluate value hypotheses, then design the first AI product cycles, prioritizing use, adoption, and scalability.
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Multidisciplinary team (product, design, data/AI, engineering, devops)
We build multidisciplinary squads bringing together product, design, data/AI, engineering, and devops to support entrepreneurs from start to finish. This integrated organization accelerates execution, reduces friction, and quickly transforms ideas into operational AI products.
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Product rituals (field discovery, cycle review, demo, roadmap decisions)
We establish structured product rituals: field discovery, cycle reviews, demonstrations, and roadmap decisions, to anchor teams in reality and user value. These key moments align vision, learning, and priorities throughout development.
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Systematic measurement of effects and integration of user feedback
We systematically measure the effects of our products and continuously incorporate user and customer feedback into product decisions. This short feedback loop ensures choices are based on real impact and accelerates continuous improvement.
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
