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ReasonBlocks

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The runtime layer that makes AI agents cheaper and more reliable

Spring 20262 peopleSan Francisco, CA, USA
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AI insightcan contain mistakes
Agent Runtime OptimizationAPI/InfraAI agents developers and teamsMedium competition
Moat
Proprietary token compression and reasoning correction algorithms are defensible if performance gains compound.
Key risk
Model providers embedding similar optimizations natively could reduce value of external runtime layer.
Why now
Agent inference costs and token spend drive urgent demand for runtime optimization.
Competitors
Anthropic optimizations, LangChain, LiteLLM

About

ReasonBlocks is the runtime layer that makes AI agents cheaper and more reliable. We correct agent reasoning and compress tokens mid-run, with gains compounding across runs. On SWE-Bench pro we have seen a 52% token reduction and 42% accuracy lift.

Founders ยท 2

Sajeev Magesh
Sajeev MageshCEO & Co-Founder
Stanford

Formerly at Stanford CS. Published in Nature Sustainable Agriculture (ML ร— agriculture). UN Best Paper. USAMO qualifier. 11 years building with co-founder Rohan. Currently making AI agents smarter and more reliable @ ReasonBlocks

Rohan Vij
Rohan VijFounder
Carnegie Mellon

Formerly at CMU, studying Information Systems & Artificial Intelligence. Molecular dynamics + AI research. AI for distributed energy at ENGIE. IoT research at UC Davis. 11 years building with co-founder Sajeev; we're making LLMs cheaper and more reliable.

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