Enterprise AI is burning tokens without context and teams are paying the price

15 hours ago 3

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What is new in the newest release of Computer
The evolution of shared memory at every level ensures that every Computer session now builds on the last. At the individual level, Computer learns how each person works, picking up where they left off with each new session. At the team level, the skills and AI agents one person develops become available to everyone. At the organizational level, institutional knowledge stays in the system permanently. When a top-performing rep leaves, their account knowledge does not leave with them.

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Before this release, AI insight disappeared the moment it left one person’s screen. Now the introduction of Multiplayer AI lets teams share a live Computer session where everyone sees the full context and continues the analysis together. Colleagues can question, build on, and correct reasoning in real time. In a 2025 study, KPMG and University of Melbourne reported that 57% of employees admit to using AI in non-transparent ways, including avoiding revealing when they have used AI tools to complete their work. Teams rarely benefit from one another’s AI work. Multiplayer AI changes the unit of attribution from “what I did with AI” to “what we did with AI, together.”

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Earlier versions of Computer answered questions and took single-step actions. The addition of the new desktop app shifts Computer from a question-answering tool to a content-producing system. From the in-app canvas, any user can generate complete, fully branded and formatted work artifacts grounded in real business data: competitive slide decks, QBR reports, structured dashboards, knowledge base articles, and multi-step workflows; these outputs are available in a variety of file formats, including PPT, HTML PDF, DOCX, and more. Skills and outputs built in the Canvas are saved at the user, team, or organization level and become reusable across the business.

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Agent Studio gives any team the ability to build, test in a sandbox environment, and deploy AI agents that take action across connected systems. Every action runs under individual user permissions, not a shared account. Every step is traceable, auditable, and reversible: if an agent makes a mistake, it can be rolled back.

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Key capabilities at a glance

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  • Shared Memory: personal, team, and organizational memory that compounds over time
  • Trusted Answers: intent-aware search and consistent data answers. Same question, same answer, every time. Computer doesn’t guess – it knows, and it shows its work.
  • Safe Actions: governed, auditable actions across your systems. Computer acts on your behalf with guardrails, so teams move faster without risk.
  • Multiplayer AI: shared live sessions for human-to-human, human-to-AI, and team-wide collaboration
  • Skills – reusable workflows that any team can build, share, and deploy. One person’s expertise becomes everyone’s capability. Agent Studio allows users to build and deploy AI agents with sandboxed testing, full audit trails, and rollback

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Additional capabilities:

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  • Text2SQL: analytical queries across structured data in plain language, no data analyst required
  • Connectors: Gmail, Outlook, Slack, Notion, Google Drive, Jira, Microsoft OneDrive, SharePoint, and any MCP-compatible tool
  • Usage-based pricing: that scales with adoption and not headcount

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With the newest release of Computer, the above capabilities are all generally available today.

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Results from customers in production
More than 250 organizations have Computer live in production, with over 1,000 users onboarded since launched in September 2025. Customers include BILL, HDFC Bank, and FAME, spanning financial services, aviation, retail, and technology.

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The results Computer, by DevRev’s customers are reporting speak for themselves. Customers Pebl and Uniphore are resolving 85% of support tickets without any human involvement. BILL has achieved around $5M in operational savings. India’s largest airline went from kickoff to production in 14 days and selected Computer over Salesforce Agentforce in a head-to-head evaluation. A retail loyalty customer is saving $1.2M annually, with sales reps reclaiming six hours a week and the team reporting a 30% productivity boost. And FAME is saving users more than 10 hours a week, resolving tickets approximately 40% faster, and accelerating specific workflows by up to 75%.

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