Tricentis was built for procurement. agent-qa learns your product from inside the repo.
Tricentis serves enterprise continuous-testing programs with enterprise licensing to match. agent-qa is for engineering teams that want fast, inspectable E2E checks in the same workflow as code changes.
Try agent-qa, the source-available option for agent-run QA that learns without suite weight.
agent-qa vs Tricentis
| Capability | agent-qa | Tricentis | Details |
|---|---|---|---|
| Source access | Tricentis 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 | Tricentis 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 Tricentis
No license fee, no seat math
Tricentis runs on enterprise license agreements sized for testing programs, not product teams, and that number grows with the coverage you add. agent-qa has no paid tier or licence fee for FSL-permitted use and its source is available under FSL-1.1-ALv2. You pay for tokens and infrastructure you control, on whichever provider is cheapest this quarter, and the cache cuts that too.
Built for coding agents, not dashboards
Your team already ships code with coding agents, and a coding agent cannot click around Tricentis'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.
Procurement-grade weight, repo-sized problem
Tricentis exists for organizations that manage testing as a program, with the rollout time, training, and licensing that implies. If your actual problem is 'verify the app before every release,' agent-qa addresses it from your repo without a paid tier or platform fee.
Tricentis is a testing program. agent-qa is a testing loop. Teams shipping continuously need the loop, and they need to own it.
Frequently asked questions
Is agent-qa a good Tricentis alternative?
Yes, and the reason is structural rather than a feature count. Tricentis is an enterprise continuous-testing suite (Tosca and related products) sold through enterprise license agreements, 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 Tricentis?
Tricentis is priced on enterprise license agreements, 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 Tricentis to agent-qa?
You are re-describing intent, not porting code, which is why this is far smaller than a normal test migration. You don't migrate a Tricentis program overnight. You carve out the product-team E2E layer first. Start with release-blocking user flows as agent-qa tests and let the suite earn its way outward. 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 Tricentis?
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. Tricentis covers mobile across its suite; agent-qa covers it with the same lightweight YAML-and-CLI loop it uses for web.
Can agent-qa really replace an enterprise testing suite?
For model-based enterprise programs spanning SAP and legacy estates, Tricentis is built for that scope. For web and mobile E2E verification wired into engineering and coding-agent workflows, agent-qa offers a repo-owned YAML, local/CI, and coding-agent workflow instead of an enterprise suite.
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 Tricentis
The parts of agent-qa that answer what Tricentis leaves you carrying.
Natural-language tests
Write actions and assertions in plain English; agent-qa resolves them against the live interface.
Learn about natural language testsPlain-English YAML
Describe the behavior once; it stays as reviewable YAML in your repository.
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
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.