MatterAI is a unified AI platform providing high-performance inference and agentic workflows for engineering teams. It offers a live model catalog with discounted access to open-source and third-party models, plus tools for terminal coding, visual coding, and automated code review. The platform supports production agents for customer support, research, and analytics, backed by a graph-orchestrated reasoning architecture for long-horizon tasks.
Funding
Funding not disclosed
Founders
Product
Problem
Engineering teams face significant bottlenecks when deploying AI agents for complex, long-horizon tasks. Standard LLM inference suffers from high costs, limited context windows, and performance degradation over multi-step workflows, while existing agent frameworks lack the structural state persistence needed for reliable, production-grade automation.
Solution
MatterAI provides a unified platform for high-performance inference and agent deployment, combining a cost-effective model catalog with specialized tools for coding and workflow automation. The platform offers access to a wide range of open-source and third-party models with up to 1M token context windows, enabling teams to handle full codebase indexing and complex reasoning tasks. MatterAI's agentic tools, including OrbCode for terminal coding and Orbital for visual coding, are designed to ship production-ready agents for customer support, internal automation, and deep research. The underlying Panoptic Thinking architecture uses a graph-orchestrated reasoning system to maintain global state, correct plan drift, and ensure reliable execution over extended tasks.
Target Audience
MatterAI targets engineering teams and organizations that need to build and deploy production-grade AI agents for coding, customer support, internal automation, and data analytics, particularly those requiring high-throughput inference and long-context reasoning.
Features
- Live model catalog with discounted access to models from providers like Google, Meta, DeepSeek, ZAI, and OpenAI, with automatic 30% discounts and up to 90% prompt caching savings
- Support for 1M token context windows, enabling full codebase indexing and analysis
- OrbCode terminal coding and Orbital visual coding interfaces for flexible development workflows
- Agentic review on every pull request with 95% precision in catching bugs pre-commit
- Panoptic Thinking architecture that uses a Global Execution Graph and Internal Q/A Map for structured, long-horizon reasoning
- Unified API endpoint (api2.matterai.so) for seamless integration with existing development pipelines