Engram raises $98M to cut runaway AI costs
What's the deal? Engram, an eight-month-old AI memory startup, has raised $98 million to help companies cut runaway AI costs.
The round drew General Catalyst, Kleiner Perkins, and Sequoia, plus OpenAIDealroom has a profile for this one. Try Dealroom → co-founder Andrej KarpathyDealroom has a profile for this one. Try Dealroom →, who joined AnthropicDealroom has a profile for this one. Try Dealroom → in 2026.
Engram bills itself as the "learned memory" of AI. Its models recall organisation-specific workflows and context to give smarter, cheaper answers.
The company claims it can match or beat frontier labs using up to 100 times fewer tokens — the currency for running AI queries.
Why now? Newer, more sophisticated AI models are proving pricier than earlier ones, upending the view that scale lowers 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 organisation and offers orders of magnitude cheaper output."
With corporate America cracking down on untamed AI use by developers, Engram sees a big opening in helping firms save money.
The 13-person company, founded in October 2025, already counts Microsoft, Notion, and legal AI startup Harvey as clients. It will spend the funding on compute and talent.
What could go wrong? Co-founder and chief executive officer Dan Biderman admits Engram's models aren't "absolutely better" than those from OpenAI or Anthropic.
They excel at specialising — sometimes at the expense of other capabilities. Too much context can also overwhelm models, demanding more reading and higher costs.
Biderman, who holds a PhD in computational neuroscience from Columbia University and worked at Stanford University's AI lab, calls this the "genius stranger model": AI is smart, but its memory is more limited than it seems.
The signal: Engram's positioning as open-source cognitive memory infrastructure for AI agents taps into a growing push to make agentic AI affordable at scale. Drawing a roster of top-tier funds in General Catalyst, Kleiner Perkins, and Sequoia — alongside angel backer Andrej Karpathy — signals that investors see efficiency, not just model size, as the next frontier for an early-stage bet.
Read more: CNBC
