TypedAI delivers a developer-centric library that wraps large language models in strongly typed TypeScript abstractions. You define input and output schemas to validate data at compile time, create reusable prompt templates, and handle streaming or batch responses. It supports function calling patterns to connect AI outputs with backend logic, and integrates with popular LLM providers like OpenAI, Anthropic, and Azure. With built-in error handling and logging, TypedAI helps you ship robust AI features—chat interfaces, document summarization, code generation, and custom agents—without sacrificing type safety or developer productivity.
TypedAI Core Features
Type-safe schema definitions for prompt I/O
Reusable prompt templating engine
Streaming and batch response handling
Function calling & tool integrations
Multi-provider support (OpenAI, Anthropic, Azure)
Built-in error handling and logging
TypedAI Pro & Cons
The Cons
No explicit pricing information available on the website.
No mobile app or browser extension links provided.
Potentially steep learning curve due to extensive features and developer-centric focus.
The Pros
Supports advanced autonomous agents and complex task management with memory and persistent state.
Integrates multiple LLM services and extensive tool and service callable functions like Filesystem, Jira, Slack, etc.
Offers flexible deployment options including local, Docker, Cloud Run, and enterprise multi-user SSO.
Includes software engineering agents that can assist in building the platform and code review workflows.
Supports observability through OpenTelemetry and cost tracking for LLM usage.
TypeScript-first design enabling strong typing and easier refactoring.
Open source with active GitHub repository and community contributions.
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