*Exciting news: TitanML raises a $2.8 million pre-seed funding round to make large language model deployment far faster, cheaper, easier and more sustainable*
We are thrilled to announce that TitanML has raised $2.8 million in pre-seed investment, in a round that was oversubscribed. Led by the deep tech team at Octopus Ventures, alongside a number of heavy-weight technology angel investors, Team Titan are grateful to have partners that are totally aligned with our core mission of making large language model (LLM) deployment far faster, cheaper, easier and more sustainable than ever before.
Having already partnered with key industry partners including Intel and AWS, we have big plans to become the infrastructure layer of choice for deep learning in the enterprise.
Our raise comes off the back of our flagship product launch, The Titan Takeoff Inference Server. Thus far, we have demonstrated up to 90% reductions in compute costs and 20x latency improvements within just hours of deployment for our enterprise clients. We have also been experiencing significant industry and community recognition for the product, most recently being invited to demo our latest features at both the ‘Woodstock of AI’ event: Hugging Face’s Community Event in Paris, as well as the upcoming Web Summit in Lisbon where Intel have invited us to be one of their spotlighted startups.
So, if you are looking to unlock the true value of your AI investment, feel free to reach out to us to get started with a trial.
Equally, if you are curious to see what difference Takeoff can make, we have a community edition which we have open-sourced.
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About TitanML
TitanML enables machine learning teams to effortlessly and efficiently deploy large language models (LLMs). Their flagship product, the Titan Takeoff Inference Server, is already supercharging the deployments of a number of enterprise ML teams.
Founded by Dr. James Dborin, Dr. Fergus Finn and Meryem Arik, and backed by key industry partners including AWS and Intel, TitanML is a team of dedicated deep learning engineers on a mission to supercharge the adoption of enterprise AI.
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