Application mapping
Heal scans a codebase and maps product features and entry points, including UI, API, CLI, SDK, webhooks, and scheduled jobs, to understand what it needs to exercise.
Runtime testing for application defects
Heal is an AI-assisted runtime testing and product verification tool for software teams. Instead of limiting analysis to the changed lines in a pull request, it builds a production-like sandbox around an application and drives its user and machine-facing entry points to look for behavior, security, and performance issues.
The product combines codebase mapping, controlled dependency handling, candidate generation, and runtime validation. Findings are intended to be actionable: each reported defect includes reproduction steps and a failing test that demonstrates the issue, while code review remains useful for concerns that do not depend on running the product.
Runtime product verification features
Production-like sandbox
It builds a controlled application sandbox around the product, using real application components and seeded storage where possible, while mocking, stubbing, or emulating dependencies that cannot run.
End-to-end runtime exploration
The agent drives product flows as users and machines do, observing screens, responses, exit codes, logs, stored data, and interactions with third parties.
Candidate generation and validation
Heal combines code analysis, runtime security tools, UI checks, and manual QA patterns to generate candidates, then validates them against the sandbox before filing them.
Reproducible defect reports
Reported defects include reproduction steps and a failing test that demonstrates the behavior. Heal says it re-runs each defect and does not file issues it cannot reproduce.
Runtime security testing
For security checks, Heal runs exploits against the sandbox and can test scenarios with different signed-in users, reporting findings that are reproduced at runtime.
Where Heal fits in a development workflow
Pre-release and recurring product checks
Run the product across its features before a release or on a recurring schedule to find defects that span unchanged code, configuration, data, and service interactions.
Testing external-service behavior
Exercise flows that depend on payments, email, or other third-party services by substituting controlled mocks or emulators, then verify how the application behaves when those services fail, respond slowly, or return unexpected data.
Runtime security validation
Validate security issues in the context of a running application, including exploit scenarios involving different signed-in users, rather than filing findings solely because a code pattern looks suspicious.
Failure-mode and edge-case testing
Investigate edge cases that standard end-to-end tests may not stage, such as missing fields, failed requests, broken assets, or disabled integrations, using a sandbox where failure conditions can be controlled.
Evidence-led defect fixing
Use the generated failing test and reproduction details as a handoff to an engineer or coding agent; the site shows a workflow where a defect is fixed and the test is run again.
Pros and Cons
Pros
- Findings are tied to runtime behavior rather than only static patterns or changed lines.
- The sandbox can account for data, application services, and external dependencies that are difficult to exercise in ordinary staging tests.
- Defects are accompanied by reproduction steps and a failing test, providing evidence for investigation and verification.
- The workflow covers behavior, performance, and runtime security checks across multiple application entry points.
- It is positioned as complementary to code review, helping teams examine the running product without discarding existing review tools.
Cons
- The benchmark describes a full run as slower than a pull-request review, taking minutes or hours rather than seconds or minutes.
- The site does not publish a complete list of supported runtimes, sandbox requirements, pricing, or plan limits.
- Because Heal focuses on issues reachable during runtime, it does not cover all code-review concerns such as style, consistency, or internal guidelines.
FAQ
How does Heal work?
Heal takes a codebase, maps its product entry points, and builds a production-like application sandbox. It can use real application components and seeded data while mocking, stubbing, or emulating external dependencies that cannot run in the sandbox. It then drives the application and re-runs candidate defects to verify them.
What does Heal provide when it finds a defect?
A reported defect includes reproduction steps and a failing test. Heal states that candidates are filed only when the behavior can be reached and reproduced; a test should turn green after the defect is fixed.
Does Heal replace code review?
Heal is intended to complement code review rather than replace it. Code review evaluates diffs, style, consistency, and other code-level concerns, while Heal focuses on behavior, security, and performance issues encountered while running the product.
Can Heal run locally, and what parts of an application can it test?
The site says Heal can run locally or in the cloud. The benchmark describes entry points including UI, API, CLI, SDK, webhooks, and scheduled jobs, but the site does not provide a complete list of supported runtimes or deployment requirements.
How is Heal priced?
The available pricing page does not contain plan or price information. The homepage advertises a free trial with no credit card required, but detailed trial terms are not provided.
Quick Facts
- Category
- Developer tool; AI-assisted runtime testing
- Primary users
- Software teams testing web applications, services, and related product entry points
- Execution
- Runs locally or in the cloud
- Application surfaces
- UI, API, CLI, SDK, webhooks, and scheduled jobs
- Output
- Reproducible defect report with steps and a failing test
- Pricing evidence
- Homepage advertises a free trial with no credit card required; detailed pricing is not published on the available pricing page
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