Find the real cause behind software failures.
CauseSignal is a governed, read-only agentic analysis platform that investigates production issues, test failures, and system regressions using cited evidence across code, tests, incidents, and release history.
Checkout failure after release
Requirements, release notes, and incident timeline retrieved
Relevant services, tests, and code paths inspected read-only
Conflicting hypotheses challenged and weak evidence rejected
Human-reviewable RCA assembled with confidence and citations
Read-only investigation for real engineering teams.
CauseSignal is built for teams that need faster diagnosis without giving autonomous tooling permission to edit production code or make unreviewed changes.
Multi-source retrieval
Searches code, tests, prior incidents, requirements, release notes, and domain documents together.
Code path reasoning
Builds and challenges hypotheses across existing software paths before presenting an explanation.
Cited RCA output
Produces durable, human-reviewable reports with evidence references and confidence signals.
Safe MVP boundary
The MVP does not patch code, push branches, or run unapproved changes inside customer repos.
How CauseSignal investigates an issue
Each investigation follows a governed path designed to reduce guesswork and surface defensible conclusions.
Understand the symptom
Capture what failed, what was expected, and what changed around the event.
Retrieve the evidence
Gather related requirements, code, tests, prior incidents, and supporting domain documents.
Inspect and challenge
Analyze likely code paths, test the logic, and reject claims that are not supported by evidence.
Report the cause
Produce a cited root-cause analysis with confidence, gaps, and next-review recommendations.
AI investigation with control boundaries.
CauseSignal is positioned for organizations that want faster root-cause work while preserving review discipline, system safety, and auditability.
No code edits, no automatic fixes, no silent repository mutation in the MVP.
Every conclusion is meant to be inspected, challenged, and approved by engineering or support leads.
The platform favors citation, traceability, and confidence scoring over unsupported narrative.
Useful for regulated, high-trust, or operationally sensitive environments that cannot accept uncontrolled AI actions.
Production incident triage
Help support and engineering teams narrow likely causes faster after an outage or customer defect.
Test failure investigation
Analyze regressions across code changes, test evidence, and requirement expectations.
Release readiness review
Surface suspicious changes, weak coverage, and historical risk signals before defects spread.
Interested in CauseSignal?
CauseSignal is being developed by Emporia IT Inc. as a focused agentic code analysis product.