Autosana is live · pricing from $999/mo · last verified 25 Oct 2026 · viability healthy
Autosana
Autosana writes end-to-end tests in plain English and self-heals them when your iOS, Android, or web UI changes.
The self-healing loop plus PR-embedded session replay is the direct answer to Maestro and Appium's maintenance tax, and MCP support means your coding agent can drive QA instead of you. The price ladder is the sore spot: $0 to $999/mo skips the entire mid-market, so a small mobile team burning 3,000 actions a month has no sane tier to buy. Pilot it on one flaky mobile branch and watch your real AI-action burn before committing.
Verdict generatedVerified 5d ago · liveness 88/100 · cite: rightaichoice.com/tools/autosana
- Mobile product teams whose iOS and Android E2E suites break on every UI change
- Teams migrating off Maestro, Appium, or Cypress selector maintenance
- Engineering orgs that want coding agents to write and run E2E tests via CLI, API, or MCP
- Teams testing push notifications, RevenueCat purchases, or real OTP logins on physical devices
- Teams needing deterministic, fully specified tests for compliance and auditor sign-off
- Solo developers or small teams testing one simple web app — the free allowance runs out fast
- Mid-sized teams wanting a tier between the 1,000 free actions and $999/mo Startup plan
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Skip Autosana if your regression volume sits between the 1,000 free AI actions and Startup's $999/mo commitment and you can't absorb a $0.10-per-action overage while you build up cache coverage.
Every step the agent takes counts as an AI action, so a broad suite can burn the free 1,000 monthly actions in a few runs and start charging $0.10 per extra action.
Pay-as-you-go at $0 with 1,000 free AI actions is the cheapest realistic entry point versus Maestro or Appium where you pay in engineer hours instead. Startup at $999/mo is priced like a headcount replacement for a small mobile team — cheap against a QA hire, expensive against a $50-$200/mo browser-testing tool. Pro at $2,499/mo with 25 cloud sessions and 5 physical device sessions is aimed at orgs already paying for device farms.
In short
Autosana — Autosana writes end-to-end tests in plain English and self-heals them when your iOS, Android, or web UI changes. Best for Mobile product teams whose iOS and Android E2E suites break on every UI change, Teams migrating off Maestro, Appium, or Cypress selector maintenance, Engineering orgs that want coding agents to write and run E2E tests via CLI, API, or MCP. Plans from $999/mo.
No head-to-head comparison for Autosana yet — the alternatives below are the closest matches we list.
What is Autosana?
Autosana — Autosana writes end-to-end tests in plain English and self-heals them when your iOS, Android, or web UI changes. Best for Mobile product teams whose iOS and Android E2E suites break on every UI change, Teams migrating off Maestro, Appium, or Cypress selector maintenance, Engineering orgs that want coding agents to write and run E2E tests via CLI, API, or MCP. Plans from $999/mo.
Autosana is an end-to-end test automation layer for iOS, Android, and web apps built around plain-English flows rather than selectors. You upload an .app or .apk build or point it at a URL, then write something like "log in with the test account and confirm the home screen loads" and an agent drives a real device, cloud simulator, or browser through the steps. It's aimed at mobile product teams who keep losing days to selector maintenance in Maestro, Appium, or Cypress. When your UI shifts, self-healing tests read your code diffs and update the steps instead of failing the build. Coverage runs across Flutter, React Native, Swift, Kotlin, and React on mobile plus Chrome, Firefox, Edge, and Chromium on web, with cloud simulators, emulators, and real iPhones and Android phones available without local setup. Flows stay in your repo as code, and a CLI, API, and MCP server let your coding agent write and run tests directly. Beyond the test loop you get session recordings posted into every pull request, AI code review on PRs, and a GitHub bot that decides which flows matter for a given change. Automated runs fire on an interval, daily, or every new build. Debugging output includes per-run network requests, CPU and memory monitoring, and bug or UX reports the agent files itself, including RevenueCat purchase flows, real OTPs for email and SMS login, and APNs/FCM push testing. Failures route to Slack, email, webhooks, Linear, or Jira. Pricing starts self-serve: $0 with up to 1,000 free AI actions refilled monthly and $0.10 per extra action, then Startup at $999/mo and Pro at $2,499/mo, with custom Enterprise. Against Appium and Maestro, Autosana's pitch is that you stop owning selectors at all; against generic AI browser agents, it's that mobile is the primary surface, not an afterthought.
Key features
- Write end-to-end tests in plain English instead of code
- Self-healing tests that adapt to UI changes using code diffs
- No XPath or CSS selectors to maintain
- Real iPhone and Android device testing on cloud hardware
- Cloud simulators and emulators for iOS and Android
- Web testing across Chrome, Firefox, Edge, and Chromium
- Multi-device flows that run one flow across two phones
- Chrome extension for capturing and running web flows
- Run tests locally against localhost and your own simulators
- Session replay recorded and posted into every pull request
- GitHub PR bot runs relevant flows and posts videos plus AI code review
- Scheduled runs on an interval, daily, or on every new build
- Tests as code: flows and suites stored in your repo, synced via GitHub
- CLI, API, and MCP server for agent-driven and IDE-driven test runs
- Email and SMS login codes with real OTPs entered by the agent
Behind the verdict
Where Autosana earns its keep is the part of QA nobody wants to own: the three-hour Tuesday afternoon where a refactor renamed six accessibility IDs and half your Maestro suite went red. Because flows are described in plain English and the agent re-derives steps from your code diffs, that afternoon mostly stops happening. Teams coming off selector-based suites consistently describe it as testing the app the way a user would. Pick it when mobile is your problem surface, not an afterthought to a web suite. The cloud physical-device sessions (five in parallel on Pro) matter for anything touching push notifications, RevenueCat entitlements, or real OTP entry, which is exactly where emulators lie to you. The MCP server and CLI are the sleeper feature. If your engineers already run Cursor, Claude Code, or a similar agent, the loop of "agent writes the flow, runs it, reads the recording" is short and hands-off. A QA lead on record describes running the whole workflow through MCP to avoid dashboard wading. Pass on it if you need deterministic, fully specified tests that an auditor signs off on. Self-healing means the agent sometimes adapts a step for you, and that is a feature for regression coverage and a liability for compliance evidence. Also pass if your app is desktop-only, or if you're a solo dev testing one small web app, where the free 1,000 actions will run out quickly once you add scheduled runs. Pricing is the honest caveat. Pay-as-you-go at $0.10 per action is cheap to try and easy to underestimate. Startup bundles 15,000 actions (~5,000 flow runs at an 80% cache rate), but the gap between free and $999/mo is a cliff with nothing on it. Cached runs at $0.01 (5 to 8x faster, roughly 90% cheaper) are what make the bundles stretch, so tune your suite to lean on
Models under the hood
as of 2026-10-23
Limitations
- Pricing is usage-based: the pay-as-you-go tier includes up to 1,000 free AI actions refilled monthly, then $0.10 per AI action ($0.01 cached); Startup is $999/mo for 15,000 actions with $0.075 overage and Pro is $2,499/mo for 50,000 actions with $0.05 overage, so effective cost depends heavily on cache rate.
- The platform targets iOS, Android, and web apps (Chrome, Firefox, Edge, Chromium); desktop platforms are not referenced.
- The changelog/news pages render no dated release entries ('Loading'), so release cadence cannot be verified from the site, and all customer quotes and metrics on the site are vendor-curated.
- An agent that self-heals and adjusts its own test steps is a poor fit for audits demanding fixed, fully specified scripts.
as of 2026-10-20
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Is Autosana still active?
Autosana is live · pricing from $999/mo · last verified 25 Oct 2026 · viability healthy.
Viability score
How well maintained and how widely used is Autosana? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What do users say about Autosana?
What people actually say about Autosana — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
ResearchedDiscussed by users across 3 sources (Hacker News, YouTube, Product Hunt) · researched Oct 11, 2026.
Weighted by the 20 posts each of 3 sources contributed.
- +Plain-English test authoring removes XPath and CSS selector maintenance entirely, a real mobile QA pain point
- +Self-healing tests adapt using code diffs, targeting the rewrite tax that kills selector-based suites
- +Real iOS and Android devices plus web browsers under one natural-language contract
- +Session replay posted directly into the pull request for visual verification of agent results
- +Framework coverage spans Flutter, React Native, Swift, Kotlin, and React
- −Pricing is contact-only, so buyers cannot compare cost-per-test against Maestro or Testim
- −The 90%+ testing-time reduction is a vendor case study, not an independent benchmark
- −Self-healing reliability across varied device sizes and React Native dynamism is unproven publicly
- −Session replay granularity for debugging failures is a launch question that went unanswered
- −Community discussion volume is low; most HN and PH engagement is founder-led or one-line congrats
- • Cloud-hosted real-device minutes typically bill separately in this category, though Autosana has not disclosed its model publicly
- • No public tier means no way to see seat, flow, or run limits before a sales conversation
How we verified this
Every listed fact about Autosana— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 25 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Autosana 21 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed who it suits, our verdict, pricing tiers, who should skip it, features, integrations, description, summary
- — changed limitations, pricing page
- — changed use cases, who should skip it, pricing tiers, our verdict, who it suits, summary, features, hidden costs, integrations, description, limitations, setup time, switching in, switching out, pricing fit
- — changed SSL certificate
- — changed description, who it suits, our verdict, who should skip it, features, pricing tiers, pricing model, integrations, summary
- — changed platforms, limitations, pricing page
Showing the 6 most recent of 21 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Autosana cost in 2026?
Autosana: Plans from $999/mo. Pricing last verified 25 Oct 2026.
Plans compared
Every published Autosana tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Pay as you go | $0.10 per AI actionVendor: “$0 to start + $0.10 per AI action” | usage | A team piloting AI-driven E2E on one or two mobile flows, or a web-only team validating the approach before committing budgetAdds: Free entry point: 1,000 AI actions refilled monthly, 1 concurrent cloud session, $0.10 per extra action, no credit card required |
| Startup | $999/mo | monthly | A growing mobile team running regression on every PR across iOS and Android, with someone who can own test strategyAdds: Adds 15,000 AI actions (~5,000 flow runs at 80% cache), 8 parallel cloud sessions, dedicated Slack channel, white glove onboarding, and a bi-weekly test strategy call |
| Pro | $2,499/mo | monthly | A larger org with a broad suite that needs real-device coverage and many flows in flight at onceAdds: Jumps to 50,000 AI actions (~17,000 flow runs), 25 parallel cloud sessions, 5 parallel physical device sessions, weekly strategy calls, and a direct line to the founders |
| Enterprise | Custom | quote | Regulated or large organizations that need unlimited runs, SSO, and a named engineer embedded with the teamAdds: Adds unlimited AI actions, unlimited cloud and physical device sessions, a dedicated forward-deployed engineer, SSO, SOC 2 report, and custom SLAs |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Autosana's pricing actually pencils out — and where peers do it cheaper.
Pay-as-you-go at $0 with 1,000 free AI actions is the cheapest realistic entry point versus Maestro or Appium where you pay in engineer hours instead. Startup at $999/mo is priced like a headcount replacement for a small mobile team — cheap against a QA hire, expensive against a $50-$200/mo browser-testing tool. Pro at $2,499/mo with 25 cloud sessions and 5 physical device sessions is aimed at orgs already paying for device farms.
Has Autosana's pricing changed?
No plan price for Autosana has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Autosana?
Pick Autosana if you are Mobile product teams whose iOS and Android E2E suites break on every UI change, Teams migrating off Maestro, Appium, or Cypress selector maintenance, Engineering orgs that want coding agents to write and run E2E tests via CLI, API, or MCP, Teams testing push notifications, RevenueCat purchases, or real OTP logins on physical devices.
Look elsewhere if you are Teams needing deterministic, fully specified tests for compliance and auditor sign-off, Solo developers or small teams testing one simple web app — the free allowance runs out fast, Mid-sized teams wanting a tier between the 1,000 free actions and $999/mo Startup plan, Teams shipping only desktop apps — coverage is iOS, Android, and web browsers.
Skip it if Skip Autosana if your regression volume sits between the 1,000 free AI actions and Startup's $999/mo commitment and you can't absorb a $0.10-per-action overage while you build up cache coverage.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Autosana actually fits — and what changes day-one when you adopt it.
You upload your latest .apk through the GitHub Action, write three flows in natural language covering sign-in with an OTP, a RevenueCat purchase, and the home screen load, then wire them to run on every pull request.
Outcome: Each PR gets a recording of the run posted inline plus an AI code review, so a reviewer can watch the agent navigate the app instead of asking you whether the login flow still works.
You rewrite your brittle selector-based flows as natural-language instructions, keep them as code-managed files in the repo synced through GitHub, and add setup/teardown hooks so each flow starts from a clean environment.
Outcome: When a redesign moves a button, the self-healing tests read the code diff and adapt instead of failing the build, and multi-device flows run the same script across two phones.
You point your agent at Autosana's MCP server, let it write new flows as it builds a feature, and have it trigger runs against your cloud simulators before opening the PR.
Outcome: The agent closes its own loop — write the feature, run the flow, read the per-run network requests and CPU/memory readings, then file bugs to Linear or Jira if something breaks.
Use cases
- Write end-to-end tests for iOS and Android apps without maintaining selectors
- Automate regression testing in CI/CD pipelines on every pull request
- Catch UI regressions with self-healing tests that read code diffs
- Test web apps across Chrome, Firefox, Edge, and Chromium
- Verify agent results visually via session replay posted into the PR
- Test push notifications, in-app purchases, and one-time password flows
- Run the same flow across two phones for multi-device coverage
- Route test failures and bugs into Linear or Jira as triage tickets
Setup time & first value
How long it actually takes to get something useful out of Autosana — broken out by persona, not the marketing-page minute.
Docs claim a first flow in about 5 minutes: upload an iOS .app, Android .apk, or web URL, write one natural-language flow, and run it. Web-only teams can be live in an afternoon. Wiring the GitHub bot, PR session replays, and EAS or GitHub Actions CI realistically takes a day. An Enterprise rollout with SSO and private network access is a project, not an afternoon.
Switching to or from Autosana
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Maestro: rewrite YAML flows as natural-language flow instructions, then sync them as code-managed files in your repo via GitHub.
- →From Appium: drop the driver/selector layer and describe each user journey as a flow; the agent handles element finding and off-screen scrolling.
- →From Cypress: point Autosana at your web URL for Chrome, Firefox, Edge, and Chromium coverage, then move the critical journeys into flows.
- →From manual QA checklists: convert each release checklist item into a flow so scheduled runs replace the manual pass.
- ↗To Maestro: export flows from your repo since Autosana keeps tests as code, then translate the natural-language steps back into YAML commands.
- ↗To Appium: rebuild flows against driver-based selectors, which reintroduces the maintenance you left behind.
- ↗To a browser-only tool: keep your web flows and re-author mobile coverage separately, since desktop surfaces aren't covered by either.
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Autosana”, and we withheld 6: 6 could not be judged, because “Autosana” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Autosana.
Official links
What are the best Autosana alternatives?
The closest alternatives to Autosana we list are Drizz, Testzeus Hercules and MobileBoost. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Drizz | Freemium | Pricing not published | — |
| Testzeus Hercules | Freemium | Pricing not published | — |
| MobileBoost | Contact Sales | Custom pricing | — |
Alternatives to Autosana
View all
Drizz
Vision AI mobile test automation that writes, self-heals, and debugs iOS and Android tests from plain English.
Testzeus Hercules
Open-source AI testing agent that runs plain-English or Gherkin scenarios and self-heals as your DOM changes.
MobileBoost
MobileBoost turns plain-English test flows into self-healing iOS and Android end-to-end tests, with a Test Agent verifying every pull
Tools that pair well with Autosana
Common stack mates teams adopt alongside Autosana, with the specific reason each pairing earns its keep.
Drizz
Vision AI mobile test automation that writes, self-heals, and debugs iOS and Android tests from plain English.
Testzeus Hercules
Open-source AI testing agent that runs plain-English or Gherkin scenarios and self-heals as your DOM changes.
MobileBoost
MobileBoost turns plain-English test flows into self-healing iOS and Android end-to-end tests, with a Test Agent verifying every pull
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