the evidence layer in your build loop · for heads of product

Every product decision, backed by your own evidence

Corroso wires into your tickets, feature requests, and codebase — then turns a raw idea into a cited scope that answers both questions that matter: should we build it, and can we, cheaply? Every claim links to its source. Then it drafts the tickets to put it in motion.

not a chatbot in a corner — the evidence layer your team's decisions run through
Northwind · idea analysis
live
PRD draft · problem & evidence

Add team collaboration

Team collaboration appears in 28% of support tickets1 and is the #2 most-requested feature2. Two enterprise accounts representing $48k ARR3 named it a renewal blocker. Build cost is low — your codebase already has a real-time presence layer4, so this is ~3 weeks, not ~10.

evidence
Zendesk
39 tickets matched “collaboration”
Canny
#2 on the feature board · 211 votes
Renewal notes
2 accounts · $48k ARR at risk
Codebase
presence layer in socket-server
14 sources scanned · 0 uncited claims
connects to Zendesk Intercom Linear Canny your codebase more, by evidence value
how it works

From raw idea to tickets
your team can build — cited end to end.

STEP 01

connect your evidence

Point Corroso at where your customers already talk — and, if you like, at your codebase. Every source connects the same way; one high-signal source is enough to start.

Zendesk · Intercom · Linear · Canny · your code
STEP 02

drop in an idea

Describe what you're considering in plain language. Corroso retrieves every relevant ticket, request, and metric — with provenance kept on each one.

“should we build team collaboration?”
STEP 03

get a cited scope — and the tickets

A PRD and MVP scope where every claim links to its source, plus an evidence panel. Then Corroso drafts the implementation tickets — codebase-informed — for you to review and push. You commit; it never writes on its own.

Markdown · PDF · Jira / Linear
the wedge

Should we build it? Can we, cheaply?
Both answers, cited.

Every build decision is two questions — is there demand, and is it feasible. Corroso answers both from your own evidence: demand from your tickets and feature requests, feasibility from your codebase. A raw chatbot can't hold both on one bus and cite them. That's the difference.

a generated guess
“Users want team collaboration. We should prioritize it for the next quarter.”
No source. No number you can defend. No idea what it costs to build.
corroso, wired to your data
Team collaboration appears in 28% of support tickets1 and is the #2 most-requested feature2, blocking $48k ARR3 at renewal. And it's ~3 weeks, not ~104 — your codebase already has the presence layer.
Zendesk #4412, #4419 +37 Canny · #2 · 211 votes Renewal note · $48k ARR socket-server/presence.ts
the trust model

The category lives or dies on trust.
So these are non-negotiable.

No claim without a citation

If Corroso can't link a quantitative claim to an ingested source, it says “no internal evidence found” — it never invents a number to fill the gap.

No false precision

You'll never see “expected revenue: $145,000.” You get ranges with explicit assumptions and a confidence band — or an honest abstain.

revenue simulation is excluded from v1, on purpose

Show the retrieval

Every report carries an Evidence panel listing exactly which tickets, requests, and metrics were used — and which were considered but left out.

Editable, not authoritative

The output is a draft you own and edit. We measure the share of PRDs shipped with minimal edits as our own quality signal — not the other way around.

where we fit

Generating a PRD is commoditized.
Defending one isn't.

The cheap IC tier is a crowded race to the bottom. The incumbents are built for enterprise. Corroso is the under-served middle: the startup Head of Product who needs evidence, not just output.

  Corroso ChatPRD Productboard / Aha!
Generates a PRD & MVP scope
Wired to your own customer dataenterprise setup
Every claim cites a source
Reads your codebase for feasibility
Drafts the tickets into Jira / Linearmanual
No false-precision numbersvaries
Priced as a team tool$15–29 IC
Built for the seed/Series-A HoPIC-first
pricing

Priced for the retention curve,
not the adoption vanity metric.

Team
$299 / mo
3 seats included · $79 / extra seat
  • One high-signal integration (tickets or requests)
  • Evidence-backed idea analysis & cited PRDs
  • MVP scope generator — must / nice / avoid
  • Evidence panel on every report
  • Export to Markdown & PDF
request early access
Growth
$799 / mo
Multi-product teams · Series B and up
  • Everything in Team
  • Multiple integrations, added by evidence value
  • Roadmap prioritization on cited demand
  • Connect-to-execution → push scope to Linear / Jira
  • Priority design-partner support
talk to us
No $15–29 IC tier. That's the 23% retention death zone — and we don't compete there.
what we hold ourselves to

Measurable commitments,
with baselines we'll publish.

≥60%
of new workspaces connect a source within 7 days
≥95%
of quantitative claims carry a working source link
≥70%
logo gross retention at month 6
<10 min
to your first fully-cited PRD
questions

What people ask
before they connect their data.

What is Corroso?

Corroso is the evidence layer in your product team's build loop. It connects to your tickets, feature requests, and codebase, turns an idea into a cited PRD and MVP scope — is there demand, and is it feasible? — then drafts the Jira/Linear tickets. Every claim links to its source.

Why not just use ChatGPT or Claude?

A chatbot can't hold your live tickets and your private codebase on one connection and cite both. Corroso stays wired to your data, gives you verifiable clickable citations instead of a one-off paste-in, and drafts the tickets that put the decision in motion.

Who is it for?

Heads of Product, VPs of Product, and technical founders/CTOs at seed and Series-A startups who own build decisions and have no product-ops team or analyst to delegate to.

Does it make up numbers?

No. If Corroso can't link a claim to a real source, it says "no internal evidence found" instead of inventing a figure. It avoids false precision and excludes revenue simulation on purpose — a projection can't cite a source.