Knowledge

As GenAI applications move from prototype to production, inference demands are exploding — across models, hardware, and environments. But most runtime

Most people assume that to run LLMs well, you need an H100 or expensive cloud GPUs.We decided to challenge that

LLMs aren’t just about parameter counts anymore.When deploying LLMs at scale, performance isn’t theoretical - it’s measured in tokens per

Most teams begin their GenAI journey using cloud-based LLM APIs - and for good reason.- They're convenient- Pay-as-you-go feels cost-efficient-

The cloud made AI accessible.But it also made it expensive.And slow.And

Scaling to 70B Models on Mid-Range Enterprise Hardware Using our EdgeMatrix framework, we recently completed benchmarking for the meta-llama/Llama-3.3-70B-Instruct model. The

In the dynamic field of Optical Character Recognition (OCR), Mistral AI's recent introduction of Mistral OCR (Mistral OCR 2503) has

As enterprises scale their AI adoption, they face a dual challenge—delivering real-time AI performance while optimizing infrastructure costs. High-end GPUs

At SandLogic, we've consistently pushed the boundaries of AI innovation across diverse modalities. With the successful launch of Shakti-1B and

At SandLogic, our mission is to push the boundaries of artificial intelligence by developing highly optimized language models that cater