Adalabs AI Platform

Fintechs and financial-service providers needed one place to organize, retrieve, and act on a sprawling pile of client documentation. The product had to surface AI-generated insights without the user losing trust in where the data came from — every assertion the model made had to trace back to a source document the user could open.

Regulated industry meant compliance review on every UX pattern that handled client data. Tight launch window (a flagship customer onboarding was the forcing function). Next.js on Vercel as the deployment target, which constrained some architectural choices — incremental static regeneration patterns had to work around per-customer data isolation.

Built the document explorer + AI-summary panes as server components where the data fetch could be co-located with the render, and progressively-enhanced interactive bits (filters, multi-select, inline annotations) as client components. Every AI-generated claim links back to the source span in the original document via a side-by-side panel — no orphan assertions. Worked closely with the AI/ML team to align response schemas so the frontend could render confidence states (high / medium / unsupported) without re-shaping every payload.

Shipped to the flagship customer on schedule. The traceable-source pattern became a feature the sales team highlighted in pitches — no AI hallucination concerns because every claim had a clickable origin. Performance held under load testing at the rendering layer (server components moved the heavy fetch off the critical path) and the design system established here was reused on the next Qubika engagement.