[Webinar] Delivering HIPAA X12 Compliance with EDI Agent

Fixing 834 enrollment files, rejected 837 claims, and HIPAA X12 validation errors can consume hours every week. Every new trading partner or requirement can mean more mapping, validation, testing, and troubleshooting for healthcare EDI teams. Astera EDIConnect helps take that work off your team. Teams can automate workflows that parse and validate HIPAA X12 transactions in a no-code, drag and drop interface. Its built-in EDI Agent helps teams create and adapt flows faster, without relying on custom code or specialized EDI resources.

AGNTCon + MCPCon Europe 2026: five takeaways

Two days at RAI Amsterdam (17–18 September), nearly a hundred sessions, and energy throughout the hallways. AGNT Con + MCPCon Europe is the Agentic AI Foundation's flagship event under the Linux Foundation, and this year it consolidated the European MCP content that previously lived at MCP Dev Summit Europe. If you care about MCP, this was the place to be.

MCP vs. API: What's the Difference and When to Use Each

An API is a defined way for one piece of software to request data or actions from another. The Model Context Protocol (MCP) is an open standard that gives AI agents a consistent way to discover and use tools and data sources, so they don't need a custom integration for each one. The short version: MCP doesn't replace APIs. Most MCP servers call APIs behind the scenes. What MCP changes is who the interface is designed for. APIs are designed for developers who read documentation and write code.

The Next Question Matters More Than the First Answer

With Claude Dashboards entering beta, Anthropic is making it possible for people to ask quick, exploratory questions about their business data and get a dashboard back. You don't need to write SQL or build a visualization. I think that's a good thing. We've spent years trying to make analytics more accessible, and anything that shortens the path from question to answer is progress. I'm increasingly asked what the future of business intelligence looks like when AI can do more of the analysis for us.

Agentic AI Security and Governance: Risks, Controls, and a Practical Checklist

Agentic AI security is the set of controls that keep AI agents from accessing, changing, or sharing more than they should. It covers who an agent acts for, which data and tools it can use, which actions need approval, and how its activity is recorded and reviewed. AI agents are moving from pilots into daily operations. They read invoices, update records, answer customers, and trigger workflows across business systems.

LLM and AI Agent Observability: What to Monitor, Evaluate, and Test

LLM observability is the practice of collecting and analyzing data about how a language model application or AI agent behaves, including prompts, responses, tool calls, cost, speed, and errors, so teams can find problems, measure quality, and improve results. AI agents can now plan tasks, call tools, and work across business systems. That makes them powerful, and it also means a single request can involve many steps that no one sees directly.

Accounts Payable Process: Steps, Exceptions & Controls

Many invoice problems don't start in accounts payable. They start earlier, when someone buys without a purchase order or a delivery goes unrecorded. AP is simply where those gaps become visible, usually as an invoice that can't be paid. That's why it helps to see the accounts payable process end to end. It's how a business receives, checks, approves, pays, and records the bills it owes suppliers, whether those steps run by hand or through accounts payable automation.

How ThoughtSpot's Marketing Team Built an Agent to Segment Their Entire Database

Marketing teams spend more time waiting on ops tickets to segment their database than they do actually running campaigns. By the time the segmentation comes back, the brief has changed, the moment has moved on, and someone is already asking for a revision. In this clip from the Thought Tank: Marketing in the Age of Agents, ThoughtSpot SVP Marketing EMEA Katie Marcham introduces the agent her team built to change that. They call it Slicy McSliceface, and it does exactly what the name suggests.

Controlling the Uncontrollable: Bring FinOps discipline to AI spend

AI costs are unpredictable and behave nothing like traditional cloud spend. FinOps teams face new challenges: opaque model pricing, and hidden costs in places like prompt design and context length. In this session, our Head of AI, Prajakta, will show you how to bring FinOps discipline to AI costs: how to see them, attribute them, and optimize them. She’ll give you practical levers that can cut AI costs by 20 – 80%.