Socotra has introduced a major new tool for the insurance industry: the Model Context Protocol (MCP) Server. It’s the most advanced MCP server on the market today. This technology makes it easier and safer for insurers to add intelligent AI agents into their workflows, boosting efficiency and automation. Why the Insurance Industry Needs Better AI
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All posts tagged in AI Agents
PolyAI has developed a new set of AI-powered roles that work alongside human agents to enhance customer service. These specialized AI teams are designed to provide faster insights, better quality, and continuous improvement in contact centers. By integrating these AI agents into their operations, companies can deliver more efficient and personalized experiences to their customers.
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Microsoft and Workday are teaming up to make AI agents easier to create and manage within companies. They want developers to register these AI helpers using Microsoft’s Azure AI Foundry and Copilot Studio, then connect them to Workday’s Agent System of Record (ASOR). This setup aims to let both humans and digital workers work together
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Nissan has been working on a new way to help reduce traffic congestion, and it doesn’t rely on the usual vehicle-to-vehicle communication tech like V2V or DSRC. Instead, they’re using their existing driver assist system, ProPilot Assist, in an innovative way to keep traffic flowing smoothly. Recently, Nissan teamed up with the Contra Costa Transportation
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Bealls, a retail company with over a century of history, has recently embraced artificial intelligence to improve how it plans and makes decisions. Since adopting Profitmind’s Agentic AI solution, the company has seen a notable boost in planning accuracy, with a 20 percent improvement during the initial rollout. This new technology is helping Bealls make
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When experimenting with voice AI for tasks like booking restaurants or handling customer calls, a common problem pops up. A single AI trying to do everything at once often struggles. It can’t understand complex requests, research options, hold conversations smoothly, and adapt to surprises all at the same time. The result? The AI performs poorly
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Databricks is facing a tricky moment after losing Naveen Rao, its head of artificial intelligence. Rao’s departure comes at a time when competitors like Snowflake, Teradata, and the big cloud providers—AWS, Azure, and Google Cloud—are all racing to develop their own generative AI tools. With a recent $1 billion funding round pushing its valuation above
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BigBear.ai, a leader in mission-ready AI solutions, has introduced a new biometric system at Nashville International Airport’s (BNA) International Arrivals Facility. This innovative technology aims to make international arrivals quicker and easier for travelers while boosting airport operations. The system, known as Enhanced Passenger Processing (EPP), uses advanced identity verification tools to streamline customs procedures.
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Box, a well-known cloud storage provider, is stepping up its game by adding smart AI tools that help businesses make the most of their data. Since it has been around for over 20 years, Box has seen many shifts in tech, and now it’s riding the wave of generative AI, which took off in late
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As AI systems become more advanced, they are now tackling increasingly complex tasks. This progress is exciting, but it also brings new challenges. One of the biggest is making sure different AI agents and tools can work together smoothly. Traditional methods of integration, where tools are built and trained together, are no longer enough. That’s
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