Octomind is winding down. Your QA memory shouldn't die with it.
Octomind publicly announced its app turns off at the end of May 2026. agent-qa is the source-available replacement path where your tests, and everything they learned, stay yours no matter what happens to any vendor.
Try agent-qa, the source-available replacement path with memory your team can keep.
agent-qa vs Octomind
| Capability | agent-qa | Octomind | Details |
|---|---|---|---|
| Source access | Octomind is not positioned as a repo-owned framework with published source, so behaviour you disagree with is a support ticket. With agent-qa it is a pull request. | ||
| Repo-owned YAML | Octomind keeps the test intent inside its own product. agent-qa keeps intent, config, hooks, memory and suites beside the code they cover, where your engineering process already works. | ||
| Coding-agent native | A coding agent cannot click through a hosted editor. agent-qa ships MCP tools, packaged Skills and a CLI, so the agent that changed the code writes the test, runs it and reads the failure without leaving the loop. | ||
| Bring your own LLM | Whoever picks the model sets your quality ceiling and your bill. agent-qa lets you point at any provider, any compatible endpoint, or a model on your own hardware, and change it in one line. | ||
| Local and CI execution | One command on a laptop, in CI, and from an agent. No run depends on somebody else's control plane being up, and nothing queues behind another tenant. | ||
| Web and mobile QA | Web, Android and iOS from the same natural-language flow and the same evidence model. The surface is a target named in a file, not a different product tier. | ||
| Memory, cache, hooks | Execution memory, a validated action cache and sandboxed hooks compound. A suite that has been running a month is faster, cheaper and better informed about your app than the day it was written. | ||
| Replacement path | The intent you have already written survives the move, in code you own, rather than being re-recorded into somebody else's format. |
Why teams switch from Octomind
Continuity risk stopped being hypothetical
Octomind's wind-down is the case study every hosted-QA skeptic warned about: the tests, the run history, the learned behavior. All of it lives on infrastructure that is going away. Keeping tests and evidence in your own repo is the structural fix.
Your tests stop being hostages
Every test you write in Octomind makes leaving Octomind more expensive. That is not an accident, it is the business model. Every test you write with agent-qa is a YAML file in your repository: reviewed in a pull request, portable to any runner, and still yours the day you cancel.
Runs compound instead of resetting
Octomind runs a test and forgets. Every run starts from nothing, which is why the hundredth run costs exactly what the first one did. agent-qa writes what it learned into memory committed beside your tests, so the next run starts where the last one finished and the suite gets better at your app on its own.
The lesson of Octomind isn't that AI testing failed. It's that renting your QA can fail you. agent-qa makes the replacement durable: source available, in your repo, with memory you keep.
Frequently asked questions
Is agent-qa a good Octomind alternative?
Yes, and the reason is structural rather than a feature count. Octomind is an AI E2E testing product whose team publicly announced the app will shut down at the end of May 2026, which means the asset you are building lives on their side of the line. agent-qa is a source-available QA agent with no paid tier, governed by FSL-1.1-ALv2: tests are plain-English YAML in your repository, runs execute on your laptop, in your CI, or from your coding agent, and every run writes back into memory committed beside the tests. The suite gets better at your app whether or not you renew anything.
How much does agent-qa cost compared to Octomind?
Octomind is priced on a product that is being discontinued, so the bill tracks how much you test. agent-qa has no paid tier, no seats and no platform fee; FSL-1.1-ALv2 governs permitted use. You pay for the model tokens and infrastructure you already control, on the provider you choose, and the validated action cache takes roughly 60% of the tokens off a matched rerun. Adding coverage does not add a line item.
How do I migrate from Octomind to agent-qa?
You are re-describing intent, not porting code, which is why this is far smaller than a normal test migration. Treat migration as an intent transfer before the shutdown deadline: list your Octomind test cases, then re-express each as an agent-qa YAML flow. Run npx agent-qa init, write each critical flow as a plain-English YAML test, and let the runtime work out the selectors and the recovery. Most teams move a smoke suite in an afternoon, and there is nothing to un-pick later because the output is files in your own repository.
Does agent-qa cover web and mobile like Octomind?
Yes, and from the same file. agent-qa runs end-to-end tests on web, Android and iOS with one natural-language format, one memory store and one evidence model, so a flow written once survives being pointed at another surface. Octomind focused on web E2E; agent-qa covers web and mobile from one contract, so the replacement also expands your coverage.
What happens to my Octomind tests after the shutdown?
Per Octomind's public wind-down notice, the hosted app turns off, which is exactly why the replacement should be source-owned. agent-qa tests are YAML files in your repository; no vendor decision can turn them off, and their accumulated memory stays with your code.
Sources
This page is based on public product and documentation sources. Verify current features and pricing with each vendor before making a purchase decision.
Octomind publicly announced that its app would turn off at the end of May 2026, so this page frames agent-qa as a replacement path.
Where agent-qa pulls ahead of Octomind
The parts of agent-qa that answer what Octomind leaves you carrying.
Execution memory
Turn successful runs into reviewable, evidence-backed memory that makes every future run faster.
Learn about memoryProven before it is used
New knowledge must pass replay and live evidence before guiding a run.
Learn moreFaster warm runs
Reuse proven flows and supersede stale facts instead of rediscovering them.
Learn moreA run leaves evidence
Elements that resolved, a flow that worked, and timings that are real, all attached to the steps that produced them.
Self-improvement
agent-qa diagnoses each run, learns only from valid evidence, and proves every lesson before using it.
Learn about the curatorIt never rewrites itself
It updates app knowledge and proposes rules, never its own prompts or code.
Learn moreEvery run is evidence
A finished run hands over its steps, artifacts, and timings. The verdict is already final, so nothing downstream can change whether it passed.
Version controlled, built for teams
Tests, knowledge, and rules stay as reviewable files shared by teammates, agents, and CI.
Learn about configurationFiles, not a database
Tests, config, memory, and rules stay as files your team can inspect and own.
Learn moreLearning arrives as a diff
New memory and issues arrive as pull-request diffs, with their evidence.
Learn moreOne commit everywhere
Humans, coding agents, and CI share the same knowledge from one commit.
Learn more- Tests
- Configs
- Memory
- Self improvement
- Knowledge
- Engineeragent-qa
- QA engineeragent-qa
- Coding agentagent-qa
- CIagent-qa
Bring your own model
Switch providers, endpoints, or models in config without rewriting a single test.
Learn about LLM providersUse your existing seat
Run with supported Codex or Claude Code subscriptions, with no second bill.
Learn more
Compatible endpoints and Codex subscription workflows.
Compatible endpoints and Claude Code subscription workflows.
Gemini configs with named credentials.
Cloud and open model workflows through compatible endpoints.
Open model workflows through compatible endpoints.
Cloud and open model workflows through compatible endpoints.
Cloud model access through compatible endpoints.
Local models through compatible endpoints.
Desktop local model workflows via compatible servers.
Route compatible requests across a broad hosted model catalog.
MiMo model workflows through compatible endpoints.
Hunyuan model workflows through compatible endpoints.
DeepSeek model workflows through compatible endpoints.
GLM model workflows through compatible endpoints.
MiniMax model workflows through compatible endpoints.
Nemotron open models through compatible endpoints.
Step model workflows through compatible endpoints.
Ling open models through compatible endpoints.
* This comparison is based on publicly available information. Product capabilities and pricing can change; verify details with each vendor before making a purchase decision.