Pezzo is an open-source, developer-first LLMOps platform designed to streamline prompt engineering, version control, collaboration, and observability for LLM-powered applications. It addresses the growing complexity of managing prompts across teams and environments by providing centralized tools for tracking performance, caching responses, and reducing latency and cloud costs. Built with TypeScript and NestJS, Pezzo is optimized for developers working with OpenAI, GPT-3/4, LangChain, and other LLM providers. It offers both cloud-hosted and self-hosted options, making it ideal for teams building production-grade AI applications who need transparency, control, and efficiency in their LLM workflows.
What You Get
- Prompt Management - Version-controlled, collaborative prompt editing with history tracking and environment-specific variants (dev/staging/prod) for consistent LLM behavior across deployments.
- Observability - Real-time monitoring of LLM requests, token usage, response times, and error rates with detailed traces to identify performance bottlenecks or degradation.
- Caching - Intelligent response caching that reduces redundant API calls, cutting costs and latency by up to 90% while maintaining prompt fidelity across identical inputs.
Common Use Cases
- Building a multi-tenant SaaS dashboard with real-time analytics - Teams use Pezzo to manage dynamic prompts per customer segment, track usage patterns, and cache frequent queries to reduce OpenAI API costs at scale.
- Creating a mobile-first e-commerce platform with 10k+ SKUs - Developers leverage Pezzo’s prompt versioning to A/B test product description templates and monitor hallucination rates across product categories.
- Problem: High API costs from redundant LLM calls → Solution: Pezzo’s caching layer automatically detects and serves cached responses for identical prompts, reducing token usage by up to 90%
- DevOps teams managing microservices across multiple cloud providers - Pezzo’s unified dashboard provides consistent LLM observability whether running on AWS, GCP, or self-hosted Kubernetes clusters.
Under The Hood
Pezzo is a developer-first platform designed to streamline prompt engineering and AI observability, offering tools for tracking, versioning, and managing LLM interactions. It provides a comprehensive solution that bridges the gap between AI development and operational monitoring through a modular, extensible architecture.
Architecture
The system adopts a layered architecture with distinct separation between frontend and backend components, promoting clear modularity and maintainability.
- The architecture follows a layered design with well-defined boundaries between presentation, application logic, and data access layers.
- Modular organization is evident across multiple applications such as console, proxy, and server, each with dedicated configurations.
- Design patterns like middleware and guards are consistently applied to handle cross-cutting concerns such as context management and authentication.
- Component interactions emphasize reusable UI elements and clear service boundaries between frontend and backend systems.
Tech Stack
The project leverages a modern TypeScript ecosystem with React and NestJS, ensuring type safety and scalability across the stack.
- Built primarily in TypeScript with React for frontend and NestJS for backend, enabling a full-stack typed environment.
- Key dependencies include Prisma for database operations, Supertokens for authentication, and Radix UI with Lucide React for UI components.
- Development tools encompass Nx for monorepo management, Webpack for bundling, Tailwind CSS for styling, and Jest for testing.
- Testing infrastructure includes Jest and Nx’s built-in tools, supporting both unit and integration test coverage.
Code Quality
The codebase reflects a balanced approach to quality with strong type safety and structured components, although some areas require improvement in consistency and testing.
- Code linting and TypeScript usage are well-configured, ensuring better maintainability and error prevention.
- Error handling is implemented with a focus on clarity and resilience across services and components.
- Component organization shows good structure, though there are inconsistencies in code style and documentation practices across modules.
- CI/CD pipelines are established, supporting automated checks and deployment workflows.
What Makes It Unique
Pezzo distinguishes itself through its focus on developer experience and extensibility in AI prompt management and observability.
- A modular architecture enables separation of concerns for prompt handling, analytics, and provider configuration into reusable modules.
- Provider abstraction layers allow seamless switching between AI services like OpenAI and Azure, enhancing flexibility for developers.
- The UI component library built with Radix and Tailwind supports rapid development of AI-focused interfaces with consistent design.
- Emphasis on inline code snippets, environment-based configuration, and testing utilities enhances developer productivity and tooling.