Giga ML, a firm that assists businesses with large language model (LLM) deployment on-premise, has revealed that it has raised $3.6 million in seed funding from a round-headed by Nexus Venture Partners. Y Combinator's president and CEO, Garry Tan, as well as Liquid 2 Venture, 8vdx, and angel investors, participated in the round. Startup covers concerns including data security and compliance to help businesses who want to implement artificial intelligence (AI) and LLM-powered uses. With the platform, firms may deploy LLMs as strong as GPT-4 on their own internal servers. As a result, sending sensitive data to outside servers such as OpenAI is longer essential.

Founded by IIT Kharagpur alumni Varun Vummadi and Esha Manideep Dinne, the three-month-old startup said that organizations in the legal, healthcare, and financial services sectors were using its platform for a variety of use cases, including code generation and internal knowledge search in addition to customer support. At Giga ML, protecting the security and privacy of company data is our primary goal. Vummadi, the company's Co-Founder and CEO, said, "Our objective is to establish our company as the top supplier of On-Premise Secure LLMs, enabling organizations to harness the power of LLMs without sacrificing their data integrity".

A pre-trained variant of the llama2 70B 4k model, Giga ML's X1 Large 32k model offers enhanced efficiency and customization. "GigaML is the crucial missing layer that Llama 2 truly requires". The future of AI that we want to live in, one free from major tech lock-ins or those dependent on it, is built around open-source LLM models, according to Tan of Y Combinator. In the first half of FY23, funding for AI companies totaled $498 billion worldwide, with 40% of that amount going to GenAI startups in October. As of 2023, seven AI unicorns with a combined enterprise valuation of $25.4 billion were developed in India.

Managing director of Nexus Venture Partners Abhishek Sharma said, "We have been big believers in the open-source ecosystem, and we think this will play out equally or even more strongly in the case of LLMs and enterprise adoption". There are serious concerns with internal teams' inadequate tooling and knowledge to deploy these models safely in production. Giga ML has risen to the occasion to establish itself as the standard platform for LLM deployments in organizations.