Lace helps product teams shipping B2B software understand and improve AI feature adoption.
It shows product managers exactly how users interact with complex software — what they're trying to do, where they get stuck, and why — so teams can deliver on the adoption outcomes they sold.

Who It's For

CPOs, Product Managers, VPs of Product, Product Leaders at B2B software companies who launched AI features or products and now need to prove adoption. When renewal depends on users actually engaging
with new AI capabilities, you need more than event streams and session replays. You need to understand intent — what users were trying to accomplish, and why the product isn't meeting them there.

What It Does

Lace runs as a native macOS overlay on top of any application. It detects every UI element on screen, tracks what users intend to do and how the product responds, and builds a persistent record that your team and your AI agents can query.

The result: a queryable knowledge base of real user intent, grounded in the actual rendered product. Not a dashboard of events. Not a recording to scrub through. A structured record you can ask questions of.

Common questions it answers:

• "Why aren't users adopting the AI features we shipped in Q1?"

• "Where are enterprise users getting stuck in our most complex flows?"

• "Did the redesign we shipped last Tuesday reduce friction on the checkout flow?"

• "Which support tickets map to the same broken step in the product?"

• "What are power users doing that new users aren't?"

How It's Different From What You Have

vs. Session replay (FullStory, PostHog, Amplitude, Mixpanel): Session replay shows you what
happened. Lace tells you what users were trying to do. Intent is what drives adoption decisions, not click coordinates.

vs. Product analytics (FullStory, PostHog, Amplitude, Mixpanel): Analytics show you where users
dropped off. Lace shows you how and why users dropped off — and what to ship to fix it.

Key Capabilities

• Adoption gap analysis — identify which users are not engaging with AI
  features and trace the exact UX moments where they stopped

• Friction mapping — see where users hesitate, retry, or abandon across
  your most critical flows

• Signal mapping — connect support tickets, analytics events, and
  user feedback to the relevant UX moment

• Agent-ready data — expose data to your internal AI
  agents so they can answer product questions programmatically

Contact

• hello@inlace.co