InterAI
agents

Motivation
Business goal
Enable teams to load company knowledge into AI agents quickly and safely—at enterprise scale.
Impact target
Increase engagement, retention, and renewals by speeding activation, driving multi-source adoption, improving answer quality, and reducing support load.
Product strategy
Ship an MVP Add Source Wizard as the primary onboarding path—adaptive for tech and non-tech users, with smart defaults, pre-flight checks, and real-time status.
Category
AI / RAG
MVP
UX • UI
SaaS B2B
Product Strategy
Process
Competitor analysis
We ran a structured comparison of several platforms using three lenses—connection flows, persona accommodation, status & errors—to inform our direction and differentiation.
CDS matrix
Our team separated facts, bets, and unknowns—confirming no adaptive flows and weak error status, defining hypotheses (simple-first, pre-flight checks, real-time status), and flagging gaps (non-tech depth, expertise detection, scale) to validate next.
Information architecture
By giving users one obvious place to start and a short, guided path, the IA removes guesswork, speeds activation, and enables the broader Knowledge Base to grow without complexity.
Wireframes
We produced annotated, clickable wireframes—mapping key interactions and adding validation notes directly on the screens so stakeholders could test, discuss trade-offs, and document decisions as we iterated.
Bring company knowledge into AI, smoothly and safely.
MVP interface
We designed for engineers and business users alike. The UI is clean and minimal, with clear steps and smart defaults. Features like pre-flight checks and real-time status cut guesswork so teams finish setup fast.
Outcomes
Evidence thresholds we use to measure success.
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