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Giga ML Raises $3.6 Mn To Help Enterprises Train And Deploy On-Premise LLMs

Giga ML Raises $3.6 Mn To Help Enterprises Train And Deploy On-Premise LLMs
SUMMARY

Founded three months ago, Giga ML helps enterprises secure on-premise deployment of Large Language models (LLMs)

Enterprises can take Giga ML's base model and further continue pre-training and fine-tune it to meet their specific needs

Nexus Venture Partners, Y Combinator, Liquid 2 Venture, 8vdx and prominent angels like Garry Tan (Y Combinator president and CEO) participated in this round of funding

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San Francisco and Bengaluru-based Giga ML has raised $3.6 Mn in a seed funding round led by Nexus Venture Partners. Y Combinator, Liquid 2 Venture, 8vdx and prominent angels like Garry Tan (Y Combinator president and CEO), also participated in this round of funding.

Founded three months ago by Varun Vummadi and Esha Manideep Dinne, GigaML helps enterprises secure on-premise deployment of Large Language models (LLMs).

Enterprises are seeking to deploy AI and LLM-powered solutions for multiple internal and external use cases. However, data security and compliance are significant challenges today. Open-source models have emerged as strong contenders for enterprise adoption.

Giga ML allows businesses to deploy LLMs as robust as GPT-4 directly on their servers — eliminating the need to send sensitive information to external servers like OpenAI.

Abhishek Sharma, Managing Director, Nexus Venture Partners, believes that there are significant challenges today around the need for more tooling and know-how of internal teams to put these models in production in a secure way. Enterprises can take Giga ML’s base model and further continue pre-training and fine-tune it to meet their specific needs.

Giga ML’s X1 Large 32k model is a pre-trained and comprehensively fine-tuned iteration of the llama2 70B 4k model, designed for enhanced performance and capabilities. While well-funded competitors like Mosaic ML and Together AI have not been able to fine-tune Llama 2 with 32k context length fully, Giga ML has already achieved this technical milestone, claims the startup founders.

Most notably, healthcare, legal, and finance organisations are looking to leverage Giga ML’s offerings for use cases like customer support and internal knowledge search and code generation for the productivity of engineering teams. Just 15 days after its public launch, the company’s website has already become the fourth most-visited among startups in Y Combinator’s S23 batch, as claimed by the startup.

“At Giga ML, our utmost priority is to ensure the privacy and security of enterprise data. Our goal is to position our company as the leading provider of On-Premise Secure LLMs, allowing enterprises to leverage the power of LLMs without compromising their data integrity,” said Varun Vummadi.

With over $2 Bn under management, Nexus operates as one team across the US and India. Nexus portfolio includes Postman, Apollo.io, MinIO, Fingerprint, Nx, Druva, Hasura, Observe.ai, Rancher, Pubmatic, Delhivery, H2O.ai, Aryaka, Kaltura, Quizizz, Sibros, TileDB, Turtlemint, Unacademy, Zepto, and Zomato.

Earlier this year, Nexus closed its Nexus Ventures VII fund at $700 Mn to back AI, SaaS, fintech, and commerce startups in India and the US. On the other hand, Y Combinator seems to be losing its focus on Indian startups. As reported by Inc42 earlier, the data for the Y Combinator Summer 2023 batch shows that this is the lowest participation by Indian startups since 2020.

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