Coworker.ai has introduced OM2, a unified memory layer designed to reduce enterprise AI token consumption by 9 times and improve response speed by 64% through precomputed, permission-aware facts that streamline how internal AI models access corporate data.
- OM2 ingests data from 50+ enterprise tools into precomputed, permission-aware facts
- Claims 9x reduction in token spend and 64% faster AI response times
- Optimized model routing combined with OM2 can reduce total AI costs by up to 51x
What happened
Coworker.ai has launched OM2, an organizational memory layer that transforms how enterprises manage AI context and costs. Instead of forcing AI agents to repeatedly scrape and reprocess thousands of documents, chat messages, and CRM entries to respond to internal questions, OM2 continuously integrates data from over 50 enterprise platforms. It converts this data into structured, permission-aware neural graph facts that the AI can reuse across sessions.
This shift from brute-force document retrieval to a surgical extraction of discrete facts means the AI no longer has to recreate context for every prompt. As a result, Coworker.ai claims OM2 achieves a 9x reduction in token usage and improves response times by 64%. The platform also includes an Optimized Routing engine that assigns queries to cheaper, faster models when appropriate, enabling total AI cost savings of up to 51x.
Why it matters
Enterprise AI deployments often suffer from inefficiencies caused by repetitive data processing that consumes a majority of token budgets. OM2 addresses this pain point by enabling AI systems to maintain a continuously updated, permission-controlled knowledge graph, drastically lowering computational waste and expense.
Furthermore, OM2’s design supports data sovereignty by connecting seamlessly with a company’s existing AI tools such as ChatGPT, Claude, or custom internal agents, rather than locking intelligence within a proprietary environment. Its robust security controls ensure sensitive information is filtered according to access rights, a critical feature for protecting corporate intelligence and compliance in complex organizations.
What to watch next
The adoption of OM2 by early customers like RapidSOS signals growing enterprise interest in more efficient AI architectures that unify data silos and reduce operational costs. Observers should monitor how broadly OM2 integrates with popular AI platforms and whether its claims on token savings and performance gains are validated at scale.
Additionally, the evolution of model routing strategies in conjunction with organizational memory layers like OM2 may redefine cost structures and technical design for enterprise AI solutions. The ability to maintain strict permission controls while improving AI utility will likely become a competitive factor in the AI infrastructure market.