[Use Cases]

Monitor, generate, analyze,
all with complete context

Every answer uses your complete Product Context Graph, not search, not guessing.

[Product Health]

Catch problems before anyone complains

Manual Process
5-10 hours/weekProblems found too late
Check dashboards

Mixpanel, Intercom, Jira, 5+ tools daily

Read support tickets

Manually spot patterns across channels

Wait for escalations

Issues found by executives or customers

With Recursive
30 secondsIssues caught in hours

Asking:“What’s broken today?”

3 issues detected today:

UrgentExport feature

- Usage dropped 30% (3 days)

- 12 support tickets about timeouts

→ Recommend: Revert timeout change

WatchMobile app

- 8 customers mentioned “slow performance”

→ Recommend: Investigate Android 13

HealthyNew search feature

- 80% adoption in week 2

- Positive feedback across segments

What we're seeing so far

90%

issues caught before customers

3x

faster issue resolution time

24/7

automated health monitoring

[Product Assets]

Generate PRDs, tickets, and docs in minutes

Manual Process
4-6 hours per PRDLosing product velocity
Research context

Similar features, feedback, competitors (1-2 hrs)

Interview engineers

Technical constraints and estimates (30-60 min)

Write and revise

First draft through final version (3-4 hrs)

With Recursive
2 minutesComplete context included

Asking:“Write a PRD for scheduled exports”

# PRD: Scheduled Exports

Problem Statement:

Real-time exports (Q3 2024), enterprise requests, compliance gap

User Requirements:

Daily 6am exports, Friday board decks

3 enterprise customers requested this quarter

Technical Approach:

3-4 sprints (based on similar work)

Depends on: Queue service, notification system

→ Review in 15 min vs writing 4 hours

What we're seeing so far

90%

approval rate for AI-generated PRDs

70%

more accurate engineering estimates

12 hrs

saved per PM per week

[Impact Analysis]

Know exactly what breaks before you ship

Manual Process
2-4 days per decision$100K-500K mistakes
Ask around in Slack

“Who uses Feature X?”, partial answers

Check analytics

See UI usage, miss API and integration usage

Talk to engineers

Map dependencies manually (takes days)

With Recursive
Complete analysis in secondsNo blind spots

Asking:“Should we deprecate CSV export?”

🔴 HIGH RISK

Risk: HIGH, 840 daily active users

Hidden: Enterprise API usage across 47 orgs

Deps: MonthlyReporting, AuditCompliance

Revenue: $2.2M ARR tied to this feature

→ Recommendation: DO NOT DEPRECATE

Instead: Build Excel export, migrate users

Timeline: 2 sprints to build, 1 sprint to migrate

What we're seeing so far

90%

dependency coverage guaranteed

15 sec

to complete impact analysis

85%

breaking changes caught early

[Get Started]

Ready to ship 5x faster?

See how Recursive eliminates context switching in a 15-minute demo.

Launching March 2026