Coworker.ai Launches AI Agent with Deep Company Context
Coworker.ai has launched an AI agent that can independently research, plan, and execute complex tasks by leveraging a deep understanding of a company's internal data. This launch is backed by a $13 million seed round led by Jeff Huber of Triatomic Capital, with participation from other notable investors such as Ramtin Naimi and Mallun Yen, announced in a press release.
The AI agent, powered by Coworker's proprietary memory architecture OM1, retains accurate information across more than 120 business parameters. This allows it to provide critical context that is often missing from other AI tools. The agent can operate across 25+ enterprise tools, including Jira, Slack, GitHub, and Salesforce, acting as a reliable teammate that stays in sync with the team.
Coworker.ai's AI agent is designed to enhance productivity by understanding complex, cross-department work and collaborating across the organization. It supports various functions such as sales, engineering, customer success, and leadership by automating tasks like analyzing sales calls, writing code, and generating real-time updates on team priorities.
The company emphasizes security and compliance, ensuring that the AI agent is built with privacy and data permissions in mind, adhering to standards like SOC 2 and GDPR.
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Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
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