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AI memory startup focused on cutting token costs raises $98 million

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Why This Matters

Engram's innovative AI memory technology aims to significantly reduce token costs for enterprise AI applications, addressing the rising expenses associated with advanced AI models. This development is crucial for the tech industry as it enables more cost-effective deployment of AI solutions, making sophisticated AI accessible to a broader range of companies and consumers.

Key Takeaways

With corporate America finally starting to crack down on untamed AI usage by developers, an 8-month-old startup called Engram sees a big business opportunity in helping companies save money.

Engram on Tuesday announced that it raised $98 million from investors including General Catalyst, Kleiner Perkins and Sequoia, as well as OpenAI co-founder Andrej Karpathy, who recently joined Anthropic.

The startup, which dubs itself the "learned memory" of AI, says its models can recall organization-specific workflows and context to anticipate questions and give smarter responses with cheaper output. The company claims its models can match or outperform frontier labs using up to 100 times fewer tokens, which are the currency for running AI queries.

New and more sophisticated AI models are proving pricier than previous iterations, challenging the conventional view that greater scale would lead to lower costs.

"You've got this explosion of data, explosion of cost," said Leigh Marie Braswell, a partner at Kleiner. "Engram comes in and basically maps out your organization and offers orders of magnitude cheaper output."