Data & AI Products
Data & AI products, shipped end-to-end
Cross-functional teams of product, design, ML and engineering — building data and AI products from first prototype to production scale.
DiscoveryMVPML engineeringProduct designMLOpsScaling
Data & AI Products
Why Liplyn Information Group for your sector
Product discovery
Validate value, feasibility and viability before you build.
MVP in weeks
Ship a working prototype that real users can test.
Cross-functional team
Product, design, ML, data and engineering in one squad.
Outcome-driven
Adoption, retention and revenue — not just shipped features.
How we work
One squad accountable for the product — from problem framing to live users, with weekly demos and clear outcomes.
Opportunity assessment and product framing
Rapid prototyping with real data and users
ML model development, evaluation and monitoring
Product design system and UX research
Production engineering and MLOps
Scale-up, adoption and continuous discovery
Pitch your product
Share the problem you want to solve. We'll propose a squad and a path from prototype to production.
Trusted by leading brands
Frequently asked questions
When you need a working product in users' hands — not a slide deck. We bring product, design, ML and engineering together so the same squad goes from problem framing to production, with clear ownership of outcomes.
Most engagements ship a usable MVP in 6–10 weeks. We start with a focused slice that proves value with real users, then expand based on adoption signals — not assumptions.
A senior product lead, a designer, one or two ML/data engineers and a full-stack engineer — sized to the problem. We scale up or down as the product evolves, and we hand over to your team when you're ready.
On outcomes that matter to the business: adoption, retention, revenue impact or operational savings — depending on the product. Vanity metrics like 'features shipped' don't make it onto our scorecards.
Yes. You own all code, models, designs and IP from day one. We deliver clean, documented codebases with knowledge transfer so your team can keep evolving the product.
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Stop shipping models nobody uses. Build products with adoption baked in from day one.
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