Inferact
Category: AI Infrastructure
A high-performance AI inference platform designed to commercialize and scale the vLLM engine for enterprise-grade Large Language Model (LLM) deployment. Inferact was founded in 2025. The company is led by Simon Mo. Based in San Francisco, USA. Team size: 10-50. Total funding raised: $150.0M. Latest round: Seed. Key investors include Andreessen Horowitz (a16z), Lightspeed Venture Partners, Sequoia Capital, Altimeter Capital, Redpoint Ventures, ZhenFund.
- Founded
- 2025
- Headquarters
- San Francisco, USA
- Team size
- 10-50
- Total funding
- $150.0M
Value proposition
Reduces LLM operational costs and latency by maximizing GPU throughput through advanced memory management and distributed systems optimization.
Products and solutions
Enterprise vLLM Managed Service, Inferact Inference Optimization Engine, Distributed LLM Orchestration Layer, High-Throughput Model Serving APIs
Unique value
Founded by the original creators of vLLM and the pioneers of PagedAttention, the company possesses the deepest technical expertise in the industry's most widely adopted open-source inference engine.
Target customer
Enterprise AI engineering teams, LLM application developers, cloud service providers, and organizations deploying generative AI at scale.
Industries served
Artificial Intelligence & Machine Learning, Enterprise Software (SaaS), Cloud Infrastructure, Financial Services, Healthcare & Life Sciences
Technology advantage
Utilizes 'PagedAttention' technology, which manages attention key-value caches like virtual memory in operating systems, virtually eliminating memory fragmentation and allowing for 10x-20x higher throughput than standard systems.
How they differentiate
Founded by the original creators of vLLM and PagedAttention, offering the deepest technical optimizations for the industry's most widely adopted open-source inference engine.
Main competitors
Together AI, Fireworks AI, Anyscale, Groq
Key partnerships
UC Berkeley Sky Computing Lab (research origin / talent pipeline; UC Berkeley Chancellor's Fund investor)
Notable customers
Enterprise AI engineering teams, Cloud Service Providers, Generative AI Application Developers
Major milestones
Secured $150M Seed funding at an $800M valuation in January 2026, Commercialized the vLLM open-source project for enterprise-grade use, Pioneered PagedAttention technology for high-throughput memory management
Growth metrics
Reached an $800M valuation at the Seed stage; underlying vLLM project is the industry standard for LLM inference.
Market positioning
Premium AI infrastructure provider specializing in high-throughput, low-latency LLM serving for enterprise-scale deployments.
Geographic focus
Global (Headquartered in San Francisco, USA)
Patents and IP
Proprietary enterprise-grade optimizations built on top of the open-source vLLM (Apache 2.0) framework; specific commercial patents pending for advanced distributed memory management.
About Simon Mo
Simon Mo is a co-creator and co-lead of the vLLM open-source project, which pioneered PagedAttention for high-throughput LLM inference. He was previously a Software Engineer at Anyscale, where he worked on the Ray distributed computing framework. He is a PhD candidate at the UC Berkeley Sky Computing Lab, specializing in AI infrastructure and distributed systems.
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Official website: https://inferact.ai