Modelence
Modelence is a unified TypeScript platform that accelerates AI application development by providing integrated authentication, MongoDB data modeling, and LLM orchestration. It streamlines the creation of agentic workflows and scheduled tasks, enabling teams to build and deploy production-ready AI solutions up to ten times faster.
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Developing production-ready AI applications requires integrating multiple complex components, including authentication, data management, and LLM orchestration, which significantly slows down development cycles. Managing observability across these disparate systems further complicates the process, leading to extended time-to-market for AI-driven products.
Solution
Modelence provides a unified TypeScript platform designed to accelerate the development and deployment of AI applications. It offers pre-built authentication modules, integrated MongoDB data modeling capabilities, and seamless LLM integration with automatic observability. The platform streamlines the creation of agentic workflows and scheduled tasks, enabling developers to build and ship production-ready AI solutions up to ten times faster. By abstracting away boilerplate infrastructure concerns, Modelence allows teams to focus on core AI logic and feature development.
Target Audience
The platform targets AI startups and development teams building production-grade AI applications who require a streamlined, type-safe, and integrated development environment.
Features
- Full-stack TypeScript framework with built-in Vite + React frontend support.
- Integrated authentication system with user management, password hashing, and secure session handling.
- MongoDB data modeling with schema and index definition alongside data retrieval methods.
- Direct integration with major LLM providers (OpenAI, Anthropic, Google Gemini) via a unified SDK with API key management.
- Automatic tracing and real-time metrics for all LLM and AI agent actions, providing comprehensive observability.
- Framework for building persistent, stateful AI agents with built-in cron job scheduling and background worker capabilities.
- Type-safe development across the entire stack, including data models, API endpoints, and database queries.
- Database migration scripts with versioning support for managing schema changes across environments.
- TanStack Query-style hooks for efficient client-server data fetching and state management.