
LLMWare.ai provides a platform called Model HQ for running private AI models locally on AI PCs, data centers, and private clouds. It optimizes AI model deployment for various hardware, including Intel and Qualcomm powered devices, enabling secure and efficient AI workflows. Model HQ supports running models up to 32 billion parameters and offers features like on-device document search (RAG), natural language SQL queries, and built-in safety tools such as AI explainability, PII filtering, and hallucination detection. The company emphasizes ease of use, with a claim of getting started in under a minute, and cost-effectiveness, with zero expected incremental cost per token for running models on AI PCs. LLMWare.ai is also committed to open-source contributions via GitHub and Hugging Face.

LLMWare.ai provides a platform called Model HQ for running private AI models locally on AI PCs, data centers, and private clouds. It optimizes AI model deployment for various hardware, including Intel and Qualcomm powered devices, enabling secure and efficient AI workflows. Model HQ supports running models up to 32 billion parameters and offers features like on-device document search (RAG), natural language SQL queries, and built-in safety tools such as AI explainability, PII filtering, and hallucination detection. The company emphasizes ease of use, with a claim of getting started in under a minute, and cost-effectiveness, with zero expected incremental cost per token for running models on AI PCs. LLMWare.ai is also committed to open-source contributions via GitHub and Hugging Face.
What: Ai Bloks (dba LLMWare.ai) provides Model HQ, a platform for running private AI models on local devices, data centers, and private clouds.
Tech: Supports models up to 32B parameters; features on-device RAG, natural language SQL, explainability, PII filtering, and hallucination detection.
Business focus: Targets privacy- and compliance-sensitive enterprises (financial, legal, regulatory).
Team & scale: Reported employee count: 7.
Funding: Crunchbase lists a Pre-Seed round dated 2022-03-01; total funding reported as USD 0.00 in provided snapshot.
Private and secure deployment of large language models for regulated, privacy-sensitive industries.
2021
Enterprise AI / ML infrastructure
Crunchbase lists a Pre-Seed round dated 2022-03-01; investor details are obfuscated in the provided evidence.