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Artificial Specialized Intelligence
We are on a mission to build the world’s most accurate, fastest, and cheapest task-specific models for every production AI system. Most AI products, whether copilots, agents, or search systems, depend on frontier LLMs to handle every step of their pipeline. Yet, the vast majority of these steps are narrow, repeatable workloads: reranking, embedding, classification, routing, query rewriting, context compression, where frontier intelligence is overkill. Running them on general-purpose models is slow and expensive, capping what production AI can achieve. That is why we're building ZeroEntropy: to train small, task-specific models that replace frontier LLMs on these workloads, and empower developers to ship AI products that are more accurate, faster, and cheaper.
ZeroEntropy provides specialized AI models, including state-of-the-art rerankers, embeddings, and custom-trained models for production AI systems. Their focus is on higher accuracy, lower latency, and reduced cost compared to generalist models, with on-prem enterprise options and dedicated SLAs.
ZeroEntropy trains and offers lightweight, specialized AI components that plug into production AI pipelines: rerankers (zerank-2 family), embeddings (zembed-1), and custom models for context compression, query rewriting, and fine-tuning. They provide enterprise on-prem and dedicated deployments with SLAs, open-weight models, optimized serving stacks for low latency, and one-line-of-code integration for reranking. The product suite includes a catalog of products (zerank-2, zerank-2-small, zerank-2-nano, zembed-1) and accompanying infrastructure and documentation to support production AI systems.
Who it’s for: Developers and engineering teams building production AI systems requiring accurate retrieval, fast latency, and cost efficiency; enterprises needing on-prem or dedicated deployments with SLAs across Legal, Manufacturing, Healthcare, Finance, Customer Support, E-Commerce, and related sectors.
funding (seed round mentioned) and active customer deployments; production usage by thousands of developers and multiple industry benchmarks
cofounder & CEO @ ZeroEntropy (YC W25) - moroccan founder with 2 masters in applied maths from École Polytechnique and UC Berkeley
Cofounder & CTO @ ZeroEntropy (YC W25) - My background is in theoretical mathematics and computer science. Dropped out of CMU to pursue startups. Worked on low-level C/C++/Assembly/GPU Code. CTO and/or main dev for 5 different startups. Created stat-arb algorithms and audited blockchains for bug bounties and hedge fund due diligence. Built the AI @ myko.ai, manifestapp.xyz, magibook.co
ZeroEntropy is the first search engine designed from the ground up to answer natural language queries by deeply understanding the language in long, complex documents.
ZeroEntropy launches a simple API for an AI-focused search engine designed to answer natural language queries over complex, unstructured documents with higher accuracy. It targets developers building RAG, search bars, or AI agent tools, aiming to reduce hallucinations and improve retrieval precision.
Frontier models for critical domains
Specialized AI for Every Job
