Radically Efficient Autonomous Agents
Built from the inference engine upwards, our agent inference stack leaves bloated multi agent frameworks behind. Experience deeper reasoning, auditable traces, and easy configuration with unmatched efficiency.
Introducing TIMThe Thread Inference Model
Our team at MIT designed TIM from the kernel up to tackle multi-step agentic tasks with significantly improved memory efficiency, faster inference, and support for a virtually unlimited context window.
We've found it's an incredible system for many use cases, including:
AI Search
Multi-step reasoning across vast knowledge bases with intelligent context management and memory efficiency.
AI Copilots
Seamless multi-tool integration with unlimited context for complex, long-running assistance tasks.
Complex Workflows
Automated subtask generation and completion with intelligent context pruning for enterprise workflows.
Research & Analysis
Deep multi-step reasoning across documents and data sources with persistent memory management.
Content Creation
Multi-stage content development with tool integration and unlimited context for comprehensive outputs.
Decision Support
Complex multi-criteria analysis with persistent reasoning chains and tool-assisted data gathering.
TIM enables breakthrough performance in agentic use cases that require sustained reasoning and memory.
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