Hoid
Hoid provides an agentic AI compiler that automates the chip-specific optimization work traditionally done by hand, creating a fast route between any AI model and any target silicon. This software-driven approach lets teams unlock the raw performance of AI accelerators without maintaining scarce, hardware-specific expertise, dramatically reducing the time and cost of production-ready inference.
- Developer Tools
- Artificial Intelligence
- Software Only
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Optimizing an AI model for deployment is slow, manual, and chip-specific work that teams typically perform once for a single stack. As a result, most hardware never gets used well, and AI accelerators with exceptional raw performance remain underutilized because software determines how much of that performance actually gets used.
Solution
Hoid provides an agentic AI compiler that creates a fast route between a model and its target silicon, automating the optimization process that has traditionally required scarce, hardware-specific expertise applied by hand. The compiler hardwires this expertise into software, allowing teams to run any model on any hardware without the usual labor-intensive re-optimization work. By handling the chip-specific tuning automatically, Hoid lets organizations unlock the raw performance of AI accelerators through software alone, dramatically reducing the time and cost required to achieve production-ready inference.
Target Audience
Primary customers are AI engineering teams and organizations deploying machine learning models at scale who need to run their workloads across diverse accelerators and hardware platforms without maintaining dedicated hardware optimization expertise.
Features
- Agentic AI compiler architecture that autonomously performs model optimization tasks across different hardware targets
- Hardware-agnostic design that supports running any model on any silicon, eliminating the need for one-off, chip-specific optimization efforts
- Automated encoding of scarce, hardware-specific optimization expertise directly into the software stack
- Software-driven performance unlock that maximizes utilization of AI accelerator raw capabilities
- Streamlined deployment pipeline designed to reduce both the engineering time and compute cost of bringing models to production