Checks onboarding, pricing, billing, docs, auth, support, and the rough edges that can stall a launch.
Audit this beta before I send it to the first 25 users.
AI project workers for builders
Hire AI project workers for your build.
Supr gives solo developers, founders, and small teams supervised agents for launch audits, repo reviews, bug hunts, product planning, research, and release cleanup. Keep the speed of AI without losing project context, approval, usage, or billing.
ProjectShip the beta
Agent runLaunch auditor
Review onboarding, pricing, billing, docs, support, and production gaps before the invite list opens.
Output
17 launch blockers found
- Checkout path needs a live price sanity check.
- Agent run failure states need clearer recovery copy.
- Docs should explain runtime boundaries before onboarding.
The problem
Chat is great for sparks. Shipping needs a workspace.
A chat tab can brainstorm. It can answer a question. It can even write a useful chunk of code. But real project work has memory, risk, cost, and follow-through. When every request becomes another loose thread, the builder still has to manage the whole job manually.
Supr is built for the work between idea and shipped: the audits, plans, investigations, cleanup passes, and decision briefs that need project context and a visible trail.
Agent workers
Start with the work you already keep postponing.
Supr is not trying to be a generic chatbot with a nicer wrapper. It is a place to assign project-shaped work to agents and review what they did.
Reads the codebase like a teammate: what is wired, what is risky, what is fake, and what needs a test.
Tell me what has to be true before this frontend can be called production-ready.
Turns a failure, log trail, or weird product behavior into a focused root-cause brief and next repair.
Find why agent runs fail after checkout succeeds.
Converts fuzzy ideas into scoped implementation plans with files, dependencies, acceptance criteria, and review points.
Plan the smallest usable version of shared projects.
Compares tools, docs, competitors, and technical options, then hands you a clean decision brief.
Compare worker queues for this runtime and recommend the fastest useful path.
Builds release checklists, tracks loose ends, reviews copy, and keeps the final mile from turning into fog.
Give me the launch-day checklist for this SaaS.
Why Supr
Built for controlled autonomy, not AI theater.
The product is opinionated around the boring things that make agents useful in production: boundaries, approvals, metering, and a clean place to review the work.
Project memory
Every run belongs to a project, so prompts, context, outputs, usage, and decisions stay attached to the build.
Approval gates
Let Supr draft a plan before higher-autonomy work begins. You keep the steering wheel when the stakes go up.
Visible usage
Agent work is metered run by run. You can see what was submitted, what completed, and what it cost.
Protected runtime
Customers use the dashboard and API boundary. The raw Google Cloud agent runtime is not exposed directly.
Flow
From signup to useful output in one project loop.
- Create a project.Give Supr the product, repo, launch, or workflow you want help with.
- Assign the work.Ask for an audit, plan, investigation, research brief, or release pass.
- Approve the plan.Choose autonomy and review the proposed path before higher-risk work starts.
- Monitor the run.Track status, output, errors, runtime metadata, and usage from the dashboard.
- Keep the trail.Return to the project history when you need the decision, artifact, or billing record.
Positioning
Why not just another AI chat?
Great for one-off answers, brainstorming, snippets, and quick help when the task is small.
Better when the work has a project, policy, run history, billing impact, and output you need to revisit.
Start small
Give Supr one messy project task and see what comes back.
Start with a launch audit, repo review, bug investigation, or product plan. If the output saves you a real afternoon, make Supr part of the weekly shipping rhythm.