Issues rarely start as tasks.
They start as a screenshot, a recording, a comment, an idea, or someone saying “something is wrong here.” The first challenge is making that observation actionable.
From issue
to approved task.
Aproow records what a tester saw, writes it up as a task a developer can act on, and hands it to the coding agent on your own machine. Your source stays out of Aproow Cloud by default.
Works with the coding agents you already use
Your setup, your choice
Claude
Codex
Gemini- Cursor
- GitHub Copilot
- OpenCode
Devin- Hermes
- Pi
Kimi
Qwen- Grok
DeepSeek
Qoder- Kilo
Aider
Trae
Mistral Vibe- MiMo
Antigravity- Reasonix
Why we built Aproow
Good work gets lost in the gaps.
A simple observation should become a clear, verified result. Instead it travels through missing information, disconnected tools and repeated explanations.
The context goes everywhere.
The screenshot stays in chat. Requirements move to a ticket. Decisions hide in a call. The original intent gets scattered across tools that don’t share one history.
Too many questions. Not enough progress.
“Which page?” “Can you send the recording?” “Who owns this?” A simple problem becomes a loop of clarification between business, QA and engineering.
The brief isn’t the whole picture.
Even a well-written ticket can omit reproduction steps, environment details, project rules and earlier decisions. Whoever builds the fix has to reconstruct what was never passed on.
A strong LLM doesn’t fix a fragmented workflow.
An agent can produce a convincing patch from incomplete instructions. But the original intent, project constraints and QA criteria may live elsewhere. Good output is not a verified outcome.
“Implemented” isn’t “verified.”
A plan needs human review before execution. A merged PR still doesn’t prove the original problem is solved. Without a clear QA handback, the loop stays open.
Now multiply the friction.
One issue is frustrating. A backlog adds duplicates, dependencies, competing priorities and no coordinated path from ready to verified.
The product
Everything between “it’s broken” and “it’s fixed”.
Secure architecture by default
Choose which Aproow workflows you use.
Engineers fixing bugs can choose the workflow that fits. Plan and manage multiple tasks in parallel, wherever you are.
Use your GitHub repository and your own LLM provider inside your controlled environment.
Copy-pasteSelected context, pasted into your AI tool.
MCPSelected context shared with your AI.
BYOYour repository, your own LLM provider.
Aproow LauncherRuntime · chat · workflow state
Super PromptGenerated against your repository by your own LLM.
Human approval
VS Code executionRuns on your computer after the approved handoff.
Use cases
Built for every team behind the product.
From product and design to engineering and QA, Aproow turns feedback into actionable work and keeps approvals moving.
Explore all use casesProduct teams
Turn user feedback into actionable product work.
FeedbackAction
Design teams
Capture and share visual feedback with full context.
CaptureShare
Engineering teams
Turn bug reports into structured tasks with clear context.
Bug reportTask
QA teams
Report and track bugs with screenshots and recordings.
ReportTrack
Case study
Nimbus
How Nimbus made reviews 3× faster with Aproow.
See how one team reduced back-and-forth and brought clarity to every approval.
Read the full storyAproow transformed how we handle feedback. What used to take days now takes hours, and everyone has clarity on what’s approved.
Maya TorresHead of Product, Nimbus
- 3×
- Faster reviewsafter 3 months
- 40%
- Less back-and-forthafter 3 months
- 95%
- Team satisfactionafter 3 months
Workflow transformationFrom a message.
From a message.
To verified work.
Follow one image-download issue from an ordinary Slack-style message to a structured Aproow, a human-reviewed plan, controlled execution and QA. Scroll to transform the same original request.
01 / 13 · Capture
A quick message. No structure.
One observation is easy to send, but hard to carry through a product workflow.
01 · Capture & structure
Maya Today at 10:24
Users can’t download the image. The download button doesn’t work on mobile.
AP-108 Bug / Image download / Mobile
Image download button doesn’t respond on mobile
BugMobileOriginal requestOwner · Unassigned
Original request
Maya · #product-feedback · 10:24Users can’t download the image. The download button doesn’t work on mobile.
One work item · DemonstrationOriginal request retained
AP-108 · Local agent runLocked
Approved work. Controlled execution.
Approve the proposed plan first, then explicitly submit the approved version for a demonstration run.
- Plan authorization
- Investigation & implementation
- Tests and changed files
- Ready for human QA
Locked until a human approves the plan.
Zoom out. The work is bigger than one card.
The original AP-108 is one of many work items. Only explicitly approved, unblocked plans can enter this demo pipeline.
- AP-108 Image downloadAwaiting QA · Not queued
- AP-109 Sidebar layoutApproved + Ready
- AP-110 Export dialogApproved + Ready
- AP-111 Search resultsNeeds plan approval
- AP-112 Navigation bugBlocked by dependency
AP-111 (unapproved) and AP-112 (blocked) are excluded. AP-108 is not rerun.
AP-108 Bug / Mobile
Image download button doesn’t respond on mobile
OverviewEvidence · 3Super PromptPlan
Original request, evidence and decisions stay connected through execution and QA.
Demo · scrolling only reveals the story
Illustrative UX, not a recording of an existing integration. Screenshot, transcription, diagnostics, repository context, AI-ready output, implementation and tests require corresponding inputs and permissions. This demonstration never connects to AI or changes code.
Wherever work finds youDifferent windows.
Different windows.
One Aproow.
Capture evidence in the browser, with context where supported.
