We’ve seen the institutional memory problem firsthand while selling and deploying agents into some of the world’s most forward-thinking companies - including Mistral, Intercom, Gong, and n8n. Our team is one of the most AI-native teams in the world processing, over a trillion tokens per month, and still no shared memory between agents. Every agent session started from zero. Decisions, customer context, workflow preferences, failures, and hard-won lessons were trapped in people’s heads, scattered in .md files or lost inside past sessions. Learning and company context doesn’t compound. That is painful in a 50-person company with one year of context and decisions made by agents. It becomes existential in a 5,000-person company deploying thousands - eventually millions - of agents. Our belief is simple: over the next 6 to 18 months, agents will move into every business function - and non-technical teams will discover that their institutional memory was never built for machines.

Ambience: Institutional Context Layer

Institutional context layer for agents

Institutional context layer for agents