One change.Many journeys.
Let a swarm explore the paths your users take, including the ones you didn’t plan for. Run it in the cloud and integrate Feena with Greptile to bring browser findings into your code-review workflow.
Simulate
every user
feena deploys cloud testing agents that use and break your app like real users do and turns every failure into a reproducible bug and a regression test, because manual QA can't keep up with how fast teams ship.
Cloud swarms · Greptile integration
The testing timeline
From URL to answers.
Select a stage to see how it worksOne continuous journey
Your app. Different perspectives. Evidence at every step.
Verify your URL
Feena checks the target before cloud work begins. Use a staging environment you own; private and localhost targets are outside this hosted flow.
Input: a verified URL and testing goal.Scout
The scout samples up to six pages in the cloud. It follows navigation without submitting forms, building a starting map of routes and visible controls. Hidden, signed-in and multi-step states may need explicit goals.
Output: a bounded map of routes and controls.Set the dynamic plan
The scout interprets your app map, testing goal and selected review hints to recommend journeys, personas and the number of cloud agents. This sets the coverage and limits for the swarm.
Output: recommended journeys, agent mix and limits.Greptile + GitHubImport existing Greptile reviews from a GitHub pull request, inspect the source links and select the hints that should guide coverage. Your app map and goal shape the plan alongside those selected hints.
Review before launch
Check the plan against your staging app and goal. Optional imported Greptile review hints can inform planning. Agent counts remain subject to quota, budget and cloud capacity.
Output: the plan you choose to deploy.Cloud agents
Cloud agents explore their assigned journeys in parallel. Each observes the live page, chooses from available browser actions and repeats within its budget. Personas guide how the agents explore.
Output: recorded browser actions and observations.Meet the personalities
Regular The focused first-time user
Well-intentioned and goal-driven. Follows the core journey, fills in expected test values and tries to reach the final confirmation. Looks for dead ends, errors and actions that fail to complete.
The scout recommends the mix; each cloud agent explores within the plan’s time and action limits.Clumsy The distracted user
Imperfect and curious about recovery. Tries missing inputs alongside ordinary actions, checks how forms respond, and looks for broken states or validation gaps on the way to the goal.
Collect the evidence
Inspect exact steps and available console, network and DOM evidence. Missing evidence, blocked access or a failed worker remain visible as inconclusive or blocked outcomes.
Output: evidence attached to the run.PlaywrightReal browser interactions produce available screenshots, videos, traces, console logs and network evidence, attached to the run for inspection.
Inspect the results
Agent agreement and provider completion alone do not prove a bug or a pass. Configured deterministic assertions can confirm their expected outcomes; exploratory observations need review.
Output: findings with explicit verification status.Keep repeatable coverage
Portable exports cover configured deterministic scenarios. They are not an automatic conversion of every AI observation into a verified regression test. Exported tests run without Feena or a model API key.
Output: standalone tests you can commit and replay.Playwright + pytest · Your CICommit exported deterministic tests to your repository and run them in your CI, including GitHub Actions. These tests replay without Feena or a model API key.