Customer signals in.
Agent-ready specs out.
Preloom ingests your support tickets, interviews, and survey data — then generates structured specs that coding agents like Cursor and Claude Code can execute directly.
Fix Evidence Board Performance,
Accessibility, and Dark Mode Contrast
The evidence board is a high-value feature for planning, but users encounter crashes when viewing large datasets, cannot navigate via keyboard, and experience dark mode contrast failures. This spec addresses three critical usability blockers.
As a Mid-Market product manager using evidence board for planning, I want to expand all themes and view the complete evidence board without the page crashing so that I can work with full dataset visibility.
- Board handles 500+ nodes without crashing or frame drops below 30fps
- Chromium DevTools shows no unresolved errors
As a Accessibility-focused user relying on keyboard navigation, I want to tab through evidence nodes, expand/collapse clusters, and reorder items using only keyboard.
- Tab key moves focus between all interactive nodes
- Enter/Space expands/collapses clusters
# Fix Evidence Board Perf...
## Priority: Critical
## Score: 83/100
### Acceptance Criteria
- [ ] 500+ nodes, no crash
- [ ] Full keyboard nav
- [ ] WCAG AA dark contrastSpec is ready for coding agents to execute.
Linked to opportunity via the analysis pipeline.
How Preloom works
Connect your feedback sources
Support tickets from Zendesk, Intercom conversations, sales call transcripts, NPS surveys, interview notes — Preloom ingests them all. Upload CSVs or connect integrations directly.
AI clusters signals into themes
The intelligence engine reads every piece of feedback, generates embeddings, and clusters them into actionable themes. It scores opportunities by severity, frequency, and segment impact — and surfaces contradictions.
Specs grounded in evidence, not guesswork
Select an opportunity and Preloom generates a full implementation spec — user stories, acceptance criteria, edge cases, technical notes — with every requirement traced back to specific customer quotes.
Fix Checkout Payment Failures
Export directly to your coding agent
One click to export as Cursor Rules, Claude Code AGENTS.md, or push tasks to Linear. The spec is structured for machines, not just humans — so your coding agent can execute without playing 20 questions.
Why teams choose Preloom
Evidence, not vibes
Every insight traces back to real customer quotes. When the AI says "users are frustrated with checkout," you see the 23 specific quotes, from which segments, over what time period. No hand-waving.
"Payment failed three times before it went through. Almost gave up."
"Why can't I save my card for next time? Every purchase is painful."
"The checkout error messages are completely unhelpful."
Ask your feedback anything
"What are enterprise users frustrated about?" "Show me contradictions between SMB and enterprise on the checkout flow." Get cited answers in seconds, not after hours of spreadsheet archaeology.
Based on 47 feedback items from enterprise users, the top frustrations are:
Specs for machines, not meetings
Traditional PM tools output documents designed for humans to read in meetings. Preloom outputs structured specs designed for coding agents to execute — acceptance criteria an AI can test, edge cases a machine can enumerate.
The AI-generated spec caught edge cases I would have missed. Saved us a full sprint of rework.
We went from a 2-week discovery cycle to same-day specs. The evidence trail is what sold our eng team.
Finally, a tool that speaks both PM and engineer. The Cursor export is a game-changer.
Stop translating. Start shipping.
Preloom turns your customer feedback into specs your coding agent can execute. Try it free.
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