Engram, an AI memory startup founded just eight months ago, raised $98 million to enhance model efficiency and reduce operational costs, capitalizing on the growing demand for cost-effective AI solutions. With a technology that claims to match or outperform leading models while using up to 100 times fewer tokens, Engram aims to help companies like Microsoft and Notion navigate the rising costs associated with sophisticated AI models. As corporate America begins to impose stricter controls on AI expenditures, startups like Engram are well-positioned to assist organizations in managing these escalating expenses by specializing in organizational memory and workflow efficiency.

Engram: Engram is an AI startup developing specialized models that serve as learned memory for organizations, recalling workflows and context to deliver intuitive responses. The company focuses on efficiency in AI applications to address rising operational challenges. In this news, Engram announced a major funding round to expand its compute resources and team while attracting clients such as Microsoft, Notion, and Harvey.
Harvey: Harvey is a legal AI startup that provides specialized tools for lawyers and legal professionals. It builds AI solutions tailored to domain-specific tasks in the legal industry. In this news, Harvey is noted as a client of Engram, reflecting adoption in professional services.
Notion: Notion is a productivity software company offering collaborative tools for note-taking, project management, and knowledge bases. It increasingly incorporates AI features to enhance user workflows. In this news, Notion appears as one of Engram’s initial clients seeking efficiency gains in AI usage.
Sequoia: Sequoia is a venture capital firm that funds high-growth startups in technology and emerging fields like AI. It has a track record of backing foundational companies. In this news, Sequoia contributed to Engram’s recent funding to advance its memory architecture.
Microsoft: Microsoft is a major technology company that integrates advanced AI capabilities into its products and services. It participates in the AI ecosystem through partnerships and investments. In this news, Microsoft is listed as an early client of Engram’s memory-focused models.
Andrej Karpathy: Andrej Karpathy is an AI researcher and co-founder of OpenAI who has since joined Anthropic, with expertise in machine learning and neural networks. He contributes insights on model development and efficiency. In this news, Karpathy invested in Engram as part of the funding round supporting its specialized approach.
Kleiner Perkins: Kleiner Perkins is a venture capital firm known for supporting transformative technology companies, particularly in AI and enterprise software. It provides strategic guidance to portfolio companies. In this news, Kleiner Perkins led or joined the investment in Engram, highlighting its focus on efficiency solutions.
General Catalyst: General Catalyst is a venture capital firm that invests in early-stage technology companies across various sectors. It backs innovative AI and infrastructure startups. In this news, General Catalyst participated in Engram’s funding round alongside other prominent investors.

Investor Interest: Prominent venture firms and AI leaders are directing capital toward startups addressing memory and context challenges in large language models.
AI Efficiency Trends: Sophisticated new AI models are proving more expensive to run than prior versions, driving demand for specialized solutions that reduce token usage.
Corporate AI Oversight: Companies are increasingly implementing controls on developer AI spending to manage escalating costs associated with widespread model usage.