Build production-ready apps with everything you need to go live - authentication, database and monitoring included out of the box. Powered by an open-source framework designed for the AI era.
Aram and Eduard here - co-founders of Modelence. We previously built and scaled a startup where we kept solving the same infrastructure problems over and over: auth, database, APIs, cron jobs, deployments. So we built an open-source full-stack TypeScript + MongoDB framework to never do that again.
The problem: AI coding agents (Claude Code, Cursor, etc.) are great at writing application logic. But they constantly fail at backend setup from scratch - wiring up auth, database connection, infrastructure. That's because most platforms were designed for humans reading docs, not agents writing code.
We built Modelence from the ground up as an open-source framework for agentic development, unlike other app builders that simply use existing third party frameworks and platforms not designed for AI agents.
Built-in guardrails for agents to catch and auto-correct errors before you deploy.
Automated database schema and index management, so agents don't have to attempt to solve these tricky problems on their own every time. Agents focus on your product logic instead of burning tokens on boilerplate and failing at infrastructure setup.
Cloud that actually closes the loop - persistent containers, dev environments, one-click deploy, and built-in observability around every operation. Because building is the easy part - running in production is where things actually get hard.
And there is zero lock-in: you fully own all source code and data.
AI App Builder included - Type a prompt on modelence.com and get a working full-stack app. Then pull it locally, continue in your own IDE, and deploy back to Modelence Cloud.
What's coming next - A built-in DevOps agent that lives in your cloud environment, knows the framework end-to-end, and uses observability data to act on errors, alerts, and incidents automatically.
Our bet is that the real challenge in AI coding isn't the builder tool - it's the framework and platform underneath. If your agent has a solid foundation, it ships real apps. If it doesn't, it generates impressive demos that break in production.
Modelence is open-source - tell us what's missing, what you'd want to see, and how your workflow actually looks - we want to hear it.
Hey PH 👋
Aram and Eduard here - co-founders of Modelence. We previously built and scaled a startup where we kept solving the same infrastructure problems over and over: auth, database, APIs, cron jobs, deployments. So we built an open-source full-stack TypeScript + MongoDB framework to never do that again.
The problem: AI coding agents (Claude Code, Cursor, etc.) are great at writing application logic. But they constantly fail at backend setup from scratch - wiring up auth, database connection, infrastructure. That's because most platforms were designed for humans reading docs, not agents writing code.
We built Modelence from the ground up as an open-source framework for agentic development, unlike other app builders that simply use existing third party frameworks and platforms not designed for AI agents.
Built-in guardrails for agents to catch and auto-correct errors before you deploy.
Automated database schema and index management, so agents don't have to attempt to solve these tricky problems on their own every time. Agents focus on your product logic instead of burning tokens on boilerplate and failing at infrastructure setup.
Cloud that actually closes the loop - persistent containers, dev environments, one-click deploy, and built-in observability around every operation. Because building is the easy part - running in production is where things actually get hard.
And there is zero lock-in: you fully own all source code and data.
AI App Builder included - Type a prompt on modelence.com and get a working full-stack app. Then pull it locally, continue in your own IDE, and deploy back to Modelence Cloud.
What's coming next - A built-in DevOps agent that lives in your cloud environment, knows the framework end-to-end, and uses observability data to act on errors, alerts, and incidents automatically.
Our bet is that the real challenge in AI coding isn't the builder tool - it's the framework and platform underneath. If your agent has a solid foundation, it ships real apps. If it doesn't, it generates impressive demos that break in production.
Modelence is open-source - tell us what's missing, what you'd want to see, and how your workflow actually looks - we want to hear it.
Try it now: modelence.com 🚀