Rainforest QA rents you testers. agent-qa gives your team a QA agent that learns.
Rainforest QA leans into managed and no-code QA workflows. agent-qa keeps the durable test contract, runtime choices, and evidence in engineering hands, where they compound.
Try agent-qa, the source-available path where runs build team memory.
agent-qa vs Rainforest QA
| Capability | agent-qa | Rainforest QA | Details |
|---|---|---|---|
| Source access | Rainforest QA 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 | Rainforest QA 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. | ||
| No platform lock-in | Every durable asset stays in your repository. Cancel agent-qa tomorrow and the tests, the memory and the evidence are still there and still readable. |
Why teams switch from Rainforest QA
Runs compound instead of resetting
Rainforest QA 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.
Built for coding agents, not dashboards
Your team already ships code with coding agents, and a coding agent cannot click around Rainforest QA's interface. agent-qa ships MCP tools, packaged Skills and a CLI, so Claude Code, Cursor and their peers author the test, run it and triage the failure inside the same loop that wrote the change.
Crowd testers don't learn your product
Every Rainforest run starts from zero product knowledge. That's the nature of externalized QA. agent-qa's memory files accumulate your product's actual behavior, so runs get more reliable and more informed with every release instead of perpetually re-discovering the basics.
Rainforest scales QA by adding people. agent-qa scales it by adding memory. One of those gets cheaper and smarter every release.
Frequently asked questions
Is agent-qa a good Rainforest QA alternative?
Yes, and the reason is structural rather than a feature count. Rainforest QA is a managed QA platform combining no-code automation with human testing services, 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 Rainforest QA?
Rainforest QA is priced on managed platform and service plans, 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 Rainforest QA to agent-qa?
You are re-describing intent, not porting code, which is why this is far smaller than a normal test migration. Your Rainforest test cases are written as human-followable steps, which is precisely the format agent-qa consumes: turn each into a plain-English YAML test and automation replaces the crowd. 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 Rainforest QA?
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. agent-qa covers Android and iOS flows with the same repo-owned YAML used for web, no service loop required.
When do humans still matter if agent-qa automates the flows?
Exploratory judgment, design taste, and edge-case hunting stay human. What shouldn't stay human is regression proof on every release. That's mechanical verification, and agent-qa makes it automatic and remembered without per-run service fees.
Sources
This page is based on public product and documentation sources. Verify current features and pricing with each vendor before making a purchase decision.
Where agent-qa pulls ahead of Rainforest QA
The parts of agent-qa that answer what Rainforest QA 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.
Built for Humans & Agents
Humans and agents author the same reviewable YAML, backed by your repository, skills, and MCP.
Learn about MCP and skillsSkills and MCP for agents
Skills teach the workflow; MCP validates, runs, and returns artifacts.
Learn moreCaching and token optimization
Reuse validated actions while the screen still matches, cutting tokens and runtime without generating scripts.
Learn about cachingCheaper the longer it lives
Every proven run reduces the work, time, and tokens needed next.
Learn moreExecution speed
42s to 8s
A run that meets screens it has already proved spends its time acting rather than deciding.
Token saving
less token usage
A reused action never reaches the model, so the only thinking billed is the thinking your app made necessary.
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
* This comparison is based on publicly available information. Product capabilities and pricing can change; verify details with each vendor before making a purchase decision.