BIRENTECH provides the 壁砺™ 166M AI accelerator, a single‑module, wind‑cooled Open Accelerator Module that combines training and inference in one high‑density, energy‑efficient package. The solution integrates easily into standard data‑center racks, supports major AI frameworks, and targets AI data‑center operators, telecom, fintech, energy, and large‑scale internet providers seeking reduced power costs and simplified deployment.
Funding
$209.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises in AI, telecom, finance, energy, and other high‑performance computing sectors require accelerator hardware that delivers high compute density while maintaining low power consumption and broad applicability across workloads. Existing solutions often involve separate training and inference units, complex cooling requirements, and limited integration flexibility, leading to higher operational costs and deployment friction.
Solution
BIRENTECH offers the 壁砺™ 166M AI accelerator, a single‑module solution that combines training and inference capabilities in a compact, wind‑cooled OAM (Open Accelerator Module) form factor. The product is engineered for high energy efficiency, delivering substantial FLOPS per watt to reduce data‑center power budgets. Its modular design enables straightforward integration into existing AI data‑center racks and supports a wide range of AI frameworks and workloads, providing a versatile compute layer for diverse industry applications. By consolidating functionality and simplifying thermal management, the module lowers total cost of ownership and accelerates deployment timelines for AI‑intensive services.
Target Audience
Primary customers are AI data‑center operators, telecom network providers, financial‑technology platforms, energy and utility firms, and large‑scale internet service providers seeking high‑performance, energy‑efficient accelerator hardware.
Features
- Integrated training‑and‑inference architecture in a single 166 M‑class accelerator module
- High‑efficiency wind‑cooled thermal design eliminating the need for liquid cooling infrastructure
- Open Accelerator Module (OAM) compliance for easy slot‑compatible installation in standard data‑center chassis
- Broad software stack support, including major AI frameworks (TensorFlow, PyTorch, ONNX) and industry‑specific SDKs
- Scalable performance scaling across AI data‑center, telecom, fintech, energy, and internet workloads
- Robust reliability features such as error‑correcting code (ECC) memory and real‑time health monitoring