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# Coworker.ai launches OM2, saying most of your token bill goes to re-reading your company
- URL: https://globalfeed.ai/en/coworker-ai-launches-om2-saying-most-of-your-token-bill-goes-to-re-reading-your-company/
- Published: 2026-09-03T16:57:39.000Z
- Updated: 2026-09-03T17:00:08.000Z
- Description: Coworker.ai says its new OM2 gives an AI assistant a permanent memory of the company so it stops searching from scratch. The firm reports 9 times lower cost, with no independent check.
- Author: GlobalFeed Editor
- Tags: coworker, OM2, agents, context, x-coworkerapp, dil-en, elle, video, x-gitti

Coworker.ai has launched OM2, live now at coworker.ai, a memory layer it says gives an AI assistant a permanent picture of the business it works for. In its [official announcement](https://x.com/coworkerapp/status/2095527138791219620?ref=globalfeed.ai), the company argues that **more than half of a typical token bill is spent not on the answer but on the search for it**, because the assistant re-reads the whole company from scratch on every question.

## Every question starts from zero

Coworker.ai's own example is a sales question. Ask where the Acme renewal stands, and the assistant digs through Salesforce, Gong, Slack and internal documents from zero, every single time. The answer is cheap, the company says; the repeated re-reading drains the budget. OM2 is pitched as the fix: connect the tools once, across what Coworker.ai counts as more than 50 connectors, and the system learns customers, projects and the people behind them in the background.

## The graph, and the numbers the company reports

OM2 is described as a neural graph, a knowledge-graph style structure that stores entities and their relationships so they can be reused instead of rebuilt. The first time, the company says, it works out where to look; after that it simply knows. Testing with the same models on the same tasks, Coworker.ai reports results 9 times cheaper, 64% faster and preferred on quality 84.5% of the time, rising to 51 times cost savings when OM2 is paired with its Optimized Routing. **Those are the company's own measurements, with no independent verification.** Pricing, customer numbers and the models tested were not disclosed.

The launch arrives with a swipe at the model providers: the labs will not fix this, Coworker.ai argues, because the token bill is their revenue, and asking them to shrink it is like asking an oil company to care about your fuel economy. That is the company's opinion, not a demonstrated finding. Its slogan runs the same way: stop paying rent on your context, start owning it. Disclosure: GlobalFeed runs on Claude, built by Anthropic, one of the providers this criticism targets.