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With agentic AI, insurers have new tools for their fight against sophisticated claims fraud. The post Agentic AI raises the stakes in the insurance fraud battle appeared first on SAS Blogs.
Agentic AI raises the stakes in the insurance fraud battle Read More »
Deploy Public MCP servers as an API endpoint and integrate its tools into LLM workflows using function calling.
Agentic finance AI improves business efficiency and ROI only when deployed with strict governance and clear return on investment targets. A recent FT Longitude survey of 200 finance leaders across the US, UK, France, and Germany showed 61 percent have deployed AI agents merely as experiments. Meanwhile, one in four executives admit they do not
Deploying agentic finance AI for immediate business ROI Read More »
Basware has introduced a AI agents in its invoice lifecycle management platform to extend the existing InvoiceAI abilities of the platform. The company positions the agents as a step towards what it calls “Agentic Finance,” a model in which AI systems undertake finance tasks under preset controls. Jason Kurtz, chief executive officer of Basware said:
Basware’s AI agents: From invoicing to “100% automated” Read More »
Large context windows have dramatically increased how much information modern language models can process in a single prompt. With models capable of handling hundreds of thousands—or even millions—of tokens, it’s easy to assume that Retrieval-Augmented Generation (RAG) is no longer necessary. If you can fit an entire codebase or documentation library into the context window,
For the past year, AI devs have relied on the ReAct (Reasoning + Acting) pattern—a simple loop where an LLM thinks, picks a tool, and executes. But as any software engineer who has tried to move these agents into production knows, simple loops are brittle. They hallucinate, they lose track of complex goals, and they
In the world of Generative AI, latency is the ultimate killer of immersion. Until recently, building a voice-enabled AI agent felt like assembling a Rube Goldberg machine: you’d pipe audio to a Speech-to-Text (STT) model, send the transcript to a Large Language Model (LLM), and finally shuttle text to a Text-to-Speech (TTS) engine. Each hop
In this tutorial, we build an advanced Griptape-based customer support automation system that combines deterministic tooling with agentic reasoning to process real-world support tickets end-to-end. We design custom tools to sanitize sensitive information, categorize issues, assign priorities with clear SLA targets, and generate structured escalation payloads, all before involving the language model. We then use
A recent demonstration from Mastercard suggests that payment systems may be heading toward a future where software agents, not people, complete purchases. During the India AI Impact Summit 2026, Mastercard showed what it described as its first fully authenticated “agentic commerce” transaction. In the demo, as reported by Times of India, an AI agent searched
Mastercard’s AI payment demo points to agent-led commerce Read More »
Building a Retrieval-Augmented Generation (RAG) pipeline is easy; building one that doesn’t hallucinate during a 10-K audit is nearly impossible. For devs in the financial sector, the ‘standard’ vector-based RAG approach—chunking text and hoping for the best—often results in a ‘text soup’ that loses the vital structural context of tables and balance sheets. VectifyAI is
