MintzTech Connect: All Things Technology — July 2025

Coworker.ai has recently announced the launch of the world’s first AI “teammate,” an agent that can perform complex work at the level of an experienced colleague. Powered by Organizational Memory (OM1), a proprietary memory architecture that essentially acts as a company’s brain, Coworker tracks information across more than 120 business parameters such as projects, teams, meetings, and documents, providing the tool with relevant information to the company’s data, knowledge, and overall culture. Coworker has the ability to answer questions, create plans, and execute multilevel tasks across more than two dozen enterprise tools (including Jira, Slack, GitHub, and Salesforce).

Coworker.ai was founded by Alex Calder and Bradford Church, two former Uber executives, before its launch this May, and was backed by a $13 million seed round led by Jeff Huber, former SVP of Google Ads, Maps, and Workspace, who is now at Triatomic Capital. The financing round was backed by several other notable VCs, joining pre-seed investors. Before its launch, Coworker had been in private release since December 2024 and was being used by more than 25 companies across various industries including engineering, product management, sales, marketing, and operation.

What sets Coworker apart from other AI tools is its ability to understand a company’s internal knowledge, working across departments and teams to assist in workflows across an entire organization. Whereas other more general-purpose large language models (LLMs) can produce content based on public information, Coworker’s access to company context allows the agent to perform like a teammate, not an assistant. Coworker can perform various tasks such as finding information and answers, managing full teams and projects, and conducting detailed research and analysis, without the usual sources of wasted time (re-prompting AI chats, uploading additional files or extra context, correcting inaccuracies or mistakes, etc.).

Because Coworker has access to internal knowledge and handles sensitive information, the software is built from the ground up with specific consideration for security, privacy, accuracy, and data permissions.

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Dan + Sam

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