Source-linked onboarding and feature adoption assistant

Guide users through product onboarding and feature adoption with one owned assistant instead of several rented subscriptions. For product marketing and customer success teams guiding users through onboarding and feature adoption, convert product knowledge, session context and account behavior into reviewed guidance and adoption actions linked to evidence. The benefit is a testable hypothesis, measured through adopted-feature rate per guided session and support contacts after guidance; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect product knowledge, session context and account behavior, then follow this sequence: 1. Provide real-time spoken guidance through tasks. 2. Read the user's screen to understand context. 3. Automate clicks and multi-step browser tasks. 4. Handle branching conversational support. 5. Keep agenda and context across a full session. 6. Deploy with zero-code embed or training materials. 7. Record sessions and surface struggle points. 8. Operate at any hour across time zones. 9. Assist in multiple languages with switching. 10. Enforce configurable guardrails and guide-only mode. 11. Accept custom knowledge bases and transcripts. 12. Update coverage from each session's edge cases. 13. Provide a stop button to halt agent actions. 14. Offer SDKs and pre-built UI templates. 15. Personalize journeys and segment audiences. 16. Build and deploy custom campaign agents. 17. Connect to marketing and analytics tools. 18. Combine warehouse and product analytics per account. 19. Draft contextual guidance from actual behavior. 20. Require human approval before sending messages. 21. Measure feature adoption after each nudge. Resolve uncertain cases with qualified reviewers, approve reviewed guidance and adoption actions linked to evidence, and measure adopted-feature rate per guided session and support contacts after guidance against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Guardrails, approval gates and the stop button remain under operator control; final adoption decisions and user messaging remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve user consent, source attribution, message accuracy and usage permissions. Operators approve substantive guidance and messaging scope. One product surface and one approved knowledge set; final adoption decisions and user messaging remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

What to build first

Pilot scope: One product surface and one approved knowledge set; final adoption decisions and user messaging remain human. Implement one approved input format, a bounded representative case set and the first two task modules: provide real-time spoken guidance through tasks; read the user's screen to understand context. Support the remaining modules with operator review: automate clicks and multi-step browser tasks; handle branching conversational support; keep agenda and context across a full session; deploy with zero-code embed or training materials; record sessions and surface struggle points; operate at any hour across time zones; assist in multiple languages with switching; enforce configurable guardrails and guide-only mode; accept custom knowledge bases and transcripts; update coverage from each session's edge cases; provide a stop button to halt agent actions; offer SDKs and pre-built UI templates; personalize journeys and segment audiences; build and deploy custom campaign agents; connect to marketing and analytics tools; combine warehouse and product analytics per account; draft contextual guidance from actual behavior; require human approval before sending messages; measure feature adoption after each nudge. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

What it can connect to

Product analytics, warehouse data, help-desk and marketing tools. Cloud asset storage, design-file import/export and publishing destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

The screens in detail

Primary screens: Knowledge and guardrail setup, Live session console, Adoption review and delivery. Use a session list for accounts, a large central live view of the user's screen and agent actions, and a right-hand panel for knowledge sources, guardrails and comments. Let users compare guided and unguided sessions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant session step. Make the task-specific outcome reviewed guidance and adoption actions linked to evidence visible beside its evidence, review state and value baseline.