Dinakar Munagala
CEO / Co-founder
Blaize
Blaize provides a unified AI computing platform that combines its Graph Streaming Processor (GSP) silicon with a composable software suite to deliver production‑ready, application‑level AI services via modular APIs. Its edge‑focused hardware families (Pathfinder and Xplorer) and code‑free AI Studio enable low‑power, high‑throughput inference across edge, on‑premise, and cloud environments, reducing the complexity and cost of deploying AI at scale.
- Artificial Intelligence
- Data & Analytics
- Automotive Technology
- Developer Tools
- Enterprise Software
- Hardware
- Industrial Automation
Updated 5 months ago
Funding
Funding not disclosed
Funding rounds are not available yet.
Founders
Product
Problem
Enterprises and infrastructure providers struggle to move AI prototypes into production at scale because building and managing the underlying AI stack—hardware, software, orchestration, and lifecycle tools—is complex, costly, and power‑inefficient, especially for edge deployments.
Solution
Blaise offers a unified AI computing platform that combines programmable Graph Streaming Processor (GSP) silicon with a composable software suite. The platform delivers production‑ready, application‑level AI services through modular APIs, enabling cloud providers, system integrators, and enterprises to launch AI‑driven applications without developing the underlying stack. Edge‑focused hardware families (Pathfinder and Xplorer) provide high‑throughput, low‑power inference, while the code‑free AI Studio and Picasso SDK accelerate model conversion, optimization, and deployment across heterogeneous environments. Forward‑deployed engineering support bridges the final integration gap, reducing time‑to‑value and operational complexity.
Target Audience
Primary customers are cloud and data‑center operators, system integrators, and large enterprises that need to deliver AI‑powered services at scale across edge, on‑premise, and cloud environments, particularly in automotive, smart‑vision, and industrial automation markets.
Features
- GSP® architecture delivers up to 16 TOPS at ~7 W, offering 50× lower memory bandwidth and 10× lower latency than traditional CPU/GPU solutions
- Modular, application‑level AI services (vision, video, document, speech, multimodal) exposed as ready‑to‑use APIs with built‑in inference scheduling and business‑logic orchestration
- Hybrid compute engine that dynamically routes workloads between GSP accelerators and GPUs to optimize cost, power, and performance
- Code‑free AI Studio platform with drag‑and‑drop UI for end‑to‑end DataOps, DevOps, and MLOps, reducing reliance on specialized data scientists
- Picasso SDK automates model conversion and optimization (NetDeploy) for rapid deployment on GSP hardware
- Scalable edge hardware families (Pathfinder SOM, Xplorer PCIe/M.2 accelerators) with flexible form factors and enterprise‑grade reliability
- Forward‑deployed engineering services that handle integration, workflow configuration, and ongoing optimization in customer environments