Know what to build next.
EvidentPM is the AI decision engine for product managers. It reads every customer conversation, ticket and metric, tells your team what to build and why, writes the spec, and measures whether it worked.
Ingests evidence from the tools your team already lives in
Roadmaps are still built on vibes gut feel.
Product teams have more customer signal than ever, and less time to read it. Tools help you track what you decided to build. Nothing tells you whether it was the right call.
Evidence is scattered
Interviews live in Gong, complaints in Zendesk, requests in Canny, behaviour in PostHog. No human can hold it all in their head — so nobody does.
The loudest voice wins
Roadmaps bend toward the last enterprise call, the angriest Slack thread, or the HiPPO. Quiet, widespread pain goes unseen until it shows up as churn.
Nobody checks if it worked
Features ship, the team moves on. Predictions are never compared with results, so prioritization never gets smarter.
One loop. From raw evidence
to measured outcome.
EvidentPM runs the entire product discovery loop continuously — not once a quarter in a spreadsheet.
Aggregate
Transcripts, tickets, boards, analytics, NPS and replays normalized into structured evidence.
Identify
Cluster recurring pain, weigh severity and frequency, flag unmet needs by segment.
Prioritize
Score every opportunity on revenue, retention, effort and confidence — with your weights.
Propose
Recommend specific product changes with cited reasoning, risks and alternatives.
Specify
Generate PRDs, stories, API contracts and tickets ready for engineers or coding agents.
Measure
Track adoption, compare predicted vs actual impact, and recalibrate the model.
Every customer, heard at once.
EvidentPM clusters thousands of conversations into ranked opportunity areas — with the frequency, severity, revenue at risk and the exact quotes behind each one.
- Automatic clustering of recurring pain points
- Severity and frequency signals across segments
- Representative quotes as citable evidence
- Contradictions and conflicting signals flagged
- Pain patterns tracked over time
Sample workspace: Ledgerly, a fictional B2B invoicing product. 312 accounts shown in the selected cluster.
Ask the question every PM is asked.
Get a specific recommendation, the evidence behind it, the impact it should have, and what would have to be true — in seconds, not a two-week synthesis sprint.
Build a Sync Health Center for accounting integrations
- 1,284 mentions across 312 accounts in the last 90 days; mentions are up 38% month-over-month.
- 41% of churned accounts in Q3 cited reconciliation or sync errors as a primary reason.
- Accounts that hit ≥1 silent sync failure have 2.3× higher 90-day churn (PostHog cohort).
- Enterprise controllers describe month-end close failures as a trust problem, not a bug.
- · Failure visibility, not failure rate, is the main driver of churn (validate with 5 churned-account calls).
- · QuickBooks API rate limits allow auto-retry within a 15-minute window.
- · Surfacing every failure may increase perceived unreliability before fixes land.
- · Xero customers report few issues — scope may be QBO-specific.
Higher revenue ceiling ($1.6M pipeline) but only 64 accounts and 2× the effort.
Best activation lever (+9 pts), lower revenue impact; good parallel bet for growth team.
Your strategy, as a formula.
Every initiative is scored on frequency, revenue, retention, strategic fit, effort and confidence. Tune the weights to match this quarter's goals and watch the roadmap re-rank.
Decision to handoff in one click.
Select an opportunity and EvidentPM writes the full implementation package — structured, versioned, and clean enough to hand to engineers or coding agents.
Clear workflows. Clear accountability.
Workspaces, roles, threaded comments, mentions, approvals and status workflows — every action written to an immutable audit log.
Roles & permissions
Comments, mentions & approvals
@Priya should retry be idempotent per attempt or per invoice?
Full audit log
Predicted vs. actual. Every time.
After a feature ships, EvidentPM tracks adoption, compares forecast to reality, surfaces unexpected side effects, and feeds the results back into scoring. Your prioritization gets measurably sharper every quarter.
Figures from the Ledgerly sample workspace.
Enterprise-grade from the first commit.
Customer conversations are your most sensitive data. EvidentPM is API-first, multi-tenant and built to pass a security review.
curl https://api.evidentpm.com/v1/evidence \
-H "Authorization: Bearer $EVIDENTPM_KEY" \
-d '{
"project": "core-billing",
"source": "custom:sales-notes",
"account": { "id": "acc_982", "arr": 84000,
"segment": "enterprise" },
"text": "We found out QuickBooks had stopped
syncing three days after close...",
"occurred_at": "2026-10-09T15:02:00Z"
}'SOC 2-ready by design
Controls mapped to SOC 2 Type II from day one: access reviews, change management, encryption, incident response.
Strict tenant isolation
Every row scoped by organization with Postgres row-level security. Per-tenant encryption keys on Enterprise.
Immutable audit log
Every read of sensitive evidence, every edit, approval and AI action — timestamped, attributed, exportable.
Deterministic automation
Rules run the same way every time. AI proposes; your workflows and approvers decide. No silent changes.
SSO, SCIM & RBAC
SAML/OIDC single sign-on, SCIM provisioning and role-based access across workspaces.
Your data stays yours
Customer data is never used to train shared models. PII redaction runs before any model call.
Simple pricing. Free for reviewers.
Pay for the people who make product decisions. Everyone else who reads, comments and approves is free.
- 1 project
- 3 data sources
- 2,000 evidence items / mo
- Insight clustering
- “What to build next” — 10 / mo
- Unlimited projects & sources
- 50,000 evidence items / mo
- Custom scoring formulas
- Spec generator + readiness scoring
- Approvals, comments & audit log
- Outcome tracking
- Viewers & reviewers free
- Everything in Team
- SSO / SAML + SCIM
- Per-tenant encryption keys
- Data residency (US / EU)
- SOC 2 report & DPA
- Custom model & BYO-LLM
- Dedicated success engineer
Questions, answered.
Those tools organize feedback and roadmaps that humans curate. EvidentPM does the synthesis and the decision support: it clusters evidence automatically, scores opportunities against your strategy, recommends what to build with citations, writes the implementation spec, and then checks whether the prediction came true.
Every claim links to the underlying transcript, ticket or metric. Confidence scores reflect evidence volume and source diversity, assumptions and risks are listed explicitly, and alternative hypotheses are always shown. AI proposes; your team approves.
Most teams connect their first three sources in under ten minutes. Initial clustering of historical data completes within an hour for up to 100k evidence items.
Evidence is stored in an isolated, encrypted tenant. PII is redacted before model calls, and your data is never used to train shared models. Enterprise plans support data residency and bring-your-own LLM.
Yes. Specs export as structured Markdown and JSON with stable IDs for stories, acceptance criteria and tickets — designed to be consumed by engineers, Linear/Jira, or coding agents directly.
Stop guessing.
Build what's evident.
We're onboarding a small group of design-partner teams. Get a working analysis of your own customer data in your first week.