Microsoft is investing $2.5 billion in a new unit called "Frontier Company" that puts 6,000 engineers directly at enterprise customers. The goal is to integrate AI into core processes with measurable ROI, not more experimentation. Microsoft is positioning itself as a platform-neutral alternative to OpenAI and Anthropic, which push their own models through their own deployment companies.<br /> The article Microsoft launches $2.5 billion "Frontier Company" to embed 6,000 AI engineers inside enterprise clients appeared first on The Decoder. [...]
Microsoft today announced the general availability of Agent 365 and Microsoft 365 Enterprise 7, two products designed to bring security and governance to the rapidly growing population of AI agents op [...]
For three years, Microsoft's artificial intelligence story has been inseparable from OpenAI. The partnership — cemented by a cumulative investment exceeding $13 billion — gave Microsoft early [...]
Perplexity, the AI-powered search company valued at $20 billion, announced on Wednesday at its inaugural Ask 2026 developer conference that its multi-model AI agent, Computer, is now available to ente [...]
If you thought Anthropic was about to run away with the enterprise AI business...you're not totally off the mark, actually.This morning, Microsoft announced "Copilot Cowork" a new cloud [...]
Microsoft on Wednesday launched three new foundational AI models it built entirely in-house — a state-of-the-art speech transcription system, a voice generation engine, and an upgraded image creator [...]
Microsoft last week took Agent 365, its management platform for AI agents, out of preview and into general availability — a move that signals the software giant believes the governance challenge aro [...]
Microsoft AI released two new in-house models into public preview on Wednesday — MAI-Image-2.5-Pro, its highest-fidelity image generator to date, and MAI-Voice-2-Flash, a speech model built for high [...]
Microsoft and OpenAI on Monday announced a sweeping overhaul of the partnership that has defined the commercial AI era, dismantling key pillars of exclusivity and revenue-sharing that bound the two co [...]
Enterprise AI has largely been built around context engineering. Teams connect enterprise systems, generate chunks and embeddings, build retrieval pipelines, and assemble the context needed by individ [...]