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United States · Hardware · AI
Wafer runs AI inference infrastructure that adapts a model-serving stack to each customer's workload. It benchmarks and tunes models, engines, kernels and available hardware together, then keeps optimizing live serving for latency, reliability and cost as traffic changes.
Wafer provides an inference endpoint for AI teams and enterprises. Customers bring a model, request pattern and service targets; Wafer evaluates the serving stack—including batching, caching, routing, decoding kernels and hardware—to select an implementation that meets those requirements while preserving output correctness.
After deployment, the platform observes real traffic and continues to optimize performance and reliability rather than treating an initial benchmark as final. Wafer is already serving production workloads for customers including DigitalOcean, which reports improving inference speed for a model running on AMD hardware. The product is AI infrastructure, with a systems-optimization approach that spans software and compute choices.
| Announced | Round | Amount | Investors |
|---|---|---|---|
| Series A | $40M | Chemistry — LeadMarathon — LeadAMD Ventures — ParticipantFifty Years — ParticipantOutset Capital — ParticipantWing Venture Capital — ParticipantY Combinator — Participant |