Revolte
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Automated Quality Engineering

Automated Quality Engineering

Revolte generates, stabilises, and maintains the tests that keep pace with a changing codebase - so coverage grows with the code instead of falling behind it.

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Built for teams with test suites growing slower than the system they protect

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Amazon
Google
Cognizant
Verizon
Indium
Akamai
PayPal
Amazon
Google
Cognizant
Verizon
Indium
Akamai
PayPal
Amazon
Google
Cognizant
Verizon
Indium
Akamai
PayPal
AmazonGoogleCognizantVerizonIndiumAkamaiPayPal
Amazon
Google
Cognizant
Verizon
Indium
Akamai
PayPal
Amazon
Google
Cognizant
Verizon
Indium
Akamai
PayPal
Amazon
Google
Cognizant
Verizon
Indium
Akamai
PayPal
Amazon
Google
Cognizant
Verizon
Indium
Akamai
PayPal
AmazonGoogleCognizantVerizonIndiumAkamaiPayPal

Teams don't stop writing tests. The suite stops keeping up.

Coverage climbs while confidence doesn't. Runs get long enough that people skip them, flaky tests get muted until red stops meaning anything, and the cases that mattered most are the ones nobody had time to write.

Grow coverage with the code, not after it

Revolte software delivery workflow diagram showing Zero-Touch Development, Command Line Interface, Quality assurance & release, and Production Deployment stages
Revolte software delivery workflow diagram showing Zero-Touch Development, Command Line Interface, Quality assurance & release, and Production Deployment stages

What Revolte executes for quality engineering teams

Production visibility preview showing centralised dashboards

Write the tests the code is missing

Turn untested paths into real, running cases.

  • Risk-ranked gaps

    Orders untested paths by change frequency and blast radius, not by file.

  • Convention-matched generation

    New cases read like the ones your team already wrote.

  • Edge and failure paths

    Covers what breaks, not only what works.

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Grew real coverage while the suite got faster

SWFI case study - moved from requirement to live system faster without building separate workflows for coding, testing, and deployment

Quote icon Increased risk-weighted coverage on a live platform while reducing total run time using generated cases, flake quarantine, and a self-updating suite.

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A suite worth trusting when it goes red

01

Coverage measured by risk, not line count

Gaps are ranked by how often the code changes and how much depends on it, so effort goes to the paths where a failure actually costs something.

02

Tests that match how your team writes tests

Generated cases follow the existing structure, naming, fixtures, and frameworks, so they get reviewed like normal work instead of quarantined as machine output.

03

Red means broken, not flaky

Non-deterministic tests are found, evidenced, and quarantined rather than muted, so a failing run is a signal your team acts on.

04

The suite maintains itself as code changes

When behaviour changes on purpose, the affected tests are updated with it. When code is removed, its tests retire with it.

Designed for suites that have to keep up

Scan and validation comparison illustration

Risk-weighted, not line-count

Coverage is scored by what a failure would cost, so the number means something.

Risk-weighted, not line-count

Coverage is scored by what a failure would cost, so the number means something.

Risk and signal mapping illustration

Written in your conventions

Generated cases use your frameworks, fixtures, and structure - reviewable as normal code.

Written in your conventions

Generated cases use your frameworks, fixtures, and structure - reviewable as normal code.

Policy gate illustration

Flakes quarantined, not tolerated

Non-determinism is isolated with evidence instead of muted into background noise.

Flakes quarantined, not tolerated

Non-determinism is isolated with evidence instead of muted into background noise.

Runtime environment illustration

Maintained as the code changes

Tests move with intentional behaviour changes and retire with deleted code.

Maintained as the code changes

Tests move with intentional behaviour changes and retire with deleted code.

Grow test coverage at the speed the codebase changes

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Frequently Asked
Questions

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Yes. Revolte is designed to operate in live production environments after software is deployed. Revolte’s AI agents support monitoring, incident detection, remediation workflows, validation, observability, governed releases, and runtime operations across active production systems while engineers maintain operational oversight and approval control.

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