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Engram, an AI memory startup whose core proposition is cutting token costs, has raised $98 million as the broader AI industry confronts a deepening expense problem tied to increasingly costly models.
The funding round positions Engram at the center of a commercial tension that is quietly reshaping how enterprises think about AI deployment: the gap between what the technology can do and what it actually costs to run.
The Cost Problem Engram Is Selling Against Token costs are the per-word billing meter at the heart of most commercial AI systems — every input and output a model processes is charged by the token.
As AI providers have introduced more capable, and more expensive, models, those costs have compounded for businesses running high-volume applications. Engram's market entry is timed directly to that pressure point.
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