For AI Startups · Trust, Adoption & Retention

Your AI product is smart. Is it trusted enough for users to stick around?

A structured AI Experience Review that uncovers the onboarding gaps, prompting friction, and trust signals quietly capping your adoption — delivered as a scorecard, a recorded walkthrough, and a prioritized list of fixes your team can ship.

JayasriLed by Jayasri, Senior Product Designer at Microsoft · 15+ years in enterprise & AI product design

What you'll receive

A complete AI Experience review.

Designed to help your team improve trust, adoption, and retention.

01

AI Product Experience Review

What I evaluate: AI onboarding, prompt experience, trust signals, agent workflows, human–AI collaboration, and workflow integration.

02

AI Experience Scorecard

Structured assessment across key dimensions. Includes scores, findings, and risk areas.

03

Recorded Walkthrough

45-minute personalized video review. Share with your team and revisit anytime.

04

Executive Summary

Founder-friendly report highlighting biggest risks, biggest opportunities, and priority areas.

Most important
05

Prioritized Recommendations

Organized by Impact, Effort, and Business Value. The most important deliverable of the engagement.

06

Strategy Debrief Session

60-minute discussion to review findings and align on next steps.

Watch: Why AI products struggle with adoption

A note from Jayasri

Over the last few years, I've watched teams spend months improving models while ignoring the experience around those models.

The result? Better AI, but poor adoption.

Most users don't abandon AI because the model is wrong. They abandon it because they don't know when to trust it, what to do next, or how the AI fits into their workflow.

In this short video, I explain the patterns I repeatedly see in AI products and how an AI Experience Review helps uncover them.

— Jayasri

Senior Product Designer, Microsoft

A look inside

What a review looks like.

Expand each category to see the kind of scoring, findings, and recommendations your team will receive — based on patterns I see again and again in AI products.

Sample content. Your review will be specific to your product.

AI Experience Scorecard

Acme Copilot · v2.3

Adoption risk

Medium

Common findings

  • Confidence in AI output is unclear.
  • Missing trust signals around generated content.
  • Users can't see the AI's limitations.

Sample recommendations

  • Add confidence indicators to AI output.
  • Improve transparency around sources and reasoning.
  • Clearly communicate model limitations in-context.

The engagement

AI Product Experience Review

Designed for seed-stage to Series A AI startups.

Typical engagement includes

  • 4–6 hours of expert product review
  • AI Experience Scorecard
  • Recorded walkthrough video
  • Executive summary report
  • Prioritized recommendations
  • 60-minute strategy session

Investment

$900 USD

Limited to two engagements per month.

Request an AI Experience Review

Still exploring AI Experience?

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What I share

  • AI Experience patterns
  • Copilot design insights
  • Agent design lessons
  • Human–AI interaction ideas
  • Product adoption strategies

No spam. Practical lessons from building and studying AI products.

Let's talk

Building an AI product?Let's make sure users actually adopt it.

FAQ

Frequently asked questions