Describe your product. Our AI plans, builds, tests, and prepares it for deployment.
Not a static mock. Auth, multi-tenant projects, usage plans, and an extensible AI + sandbox core.
Describe the app you want. KrushnaLabs turns it into a structured specification before writing code.
Planner, frontend, backend, database, testing, and debugging agents work as a modular pipeline.
Generated apps run in sandboxed environments — never inside the main platform process.
Specs, conversations, files, builds, and versions stay attached to each project for iterative changes.
Auth, project isolation, server-side keys, rate limits, and audit logs from day one.
Architecture is ready for GitHub sync and deployment providers as later phases land.
From a sentence to a versioned application with a clear build pipeline.
Pick a starter (SaaS, landing, CRUD…) or describe your app.
AI produces a structured app specification and file plan.
Agents write frontend, backend, and data models.
Sandbox builds, surfaces errors, and auto-patches.
Open a live preview and share a public link.
One-click ship: version, GitHub, and deploy.
Ops dashboards, CRMs, inventory apps for your team.
Auth, billing views, ticket flows, and admin panels.
Validate ideas with a working full-stack prototype in days.
Stripe and Razorpay adapters plug into this plan model later.
Explore the builder and ship small prototypes.
For indie builders shipping real products.
No. Phase 1 is a real SaaS shell with auth, orgs, projects, billing architecture, and admin. Later phases add generation, sandbox builds, and deploy.
Yes. Providers implement a shared AIProvider interface (generate, stream, analyze, plan, fix).
No. Execution goes through a SandboxProvider abstraction designed for Docker/Kubernetes isolation.
Founders, product teams, and operators who want software without starting from a blank IDE.