About SignalPath
Every week a support queue fills up with clues about what to build next. Most of them go unread. SignalPath makes sure none of them do.
The problem
The average mid-market SaaS company receives thousands of support tickets every month. Buried in those tickets are the exact problems your customers care about most — described in their own words, attached to real account values, and sorted roughly by frequency already.
The problem is that nobody has time to read them all. Support teams triage and close. PMs rely on what bubbles up in customer calls and their own intuition. Engineers build what’s on the roadmap. The signal stays locked in the helpdesk.
We’ve worked at companies where a single lurking bug, mentioned in 300 tickets over 18 months, cost more in churn than the entire Q3 roadmap recovered. Nobody connected the dots because the data was there but the analysis wasn’t.
SignalPath connects those dots automatically — and hands engineers a spec that references their actual codebase, so they can start building the same day.
How it works
Connect your help desk — Zendesk, Intercom, or Freshdesk. SignalPath reads every ticket and conversation, plus optional Salesforce data for account ARR. Nothing leaves your security perimeter without encryption.
Our ML pipeline groups related signals into product opportunities and scores each one across six dimensions: churn risk, account breadth, severity, frequency, recency, and revenue at risk. Scores improve as your team rates results.
Connect your GitHub repository and SignalPath indexes its skeleton — file paths, routes, models, functions. When a spec is generated it references your actual files, not generic service names. Push directly to Linear or Jira, or open in Cursor.
What we believe
A PM's gut is useful. 800 tickets saying the same thing is a fact. We bias toward evidence.
A spec that says 'fix the auth bug' wastes engineering time. A spec that says modify TokenRefreshMiddleware in app/middleware/ starts a sprint.
We index your codebase skeleton — file paths, routes, function names. We never store source code, and all data is encrypted in transit and at rest.
You already have analytics. We tell you what to build next and why, ranked by what will actually move your retention curve.
Team
We’re a small team of engineers and product people who have been on both sides of the support queue — as customers and as the people trying to make sense of it.
Nishi Kantamneni
Founder · Product & Engineering
Previously built ML-powered analytics at enterprise SaaS. Spent too many Fridays manually tagging support tickets and decided there had to be a better way.
We’re hiring
Looking for a founding engineer who wants to work on hard ML + product problems.
Connect your help desk in minutes. See your first ranked opportunities within 48 hours.