Systems | Development | Analytics | API | Testing

Hevo's Next Evolution: Powering 2000+ Customers with AI-Ready Data

Across 8 years and 2,000+ data teams in 40+ countries, three principles have shaped every decision we've made. That's the conviction behind Hevo's next chapter. In our latest video, Manish Jethani, Founder & CEO at Hevo Data, along with Scott Husband, Director of Partnerships, and Amit Gupta, VP of Engineering, walk through what's changed under the hood, and why every architectural decision traces back to three non-negotiables: Reliability, Simplicity, and Transparency.

AI Inference for Mission-Critical Applications | Run AI Where Your Data Lives

What happens when your AI system stops responding in the middle of a critical decision? This demo shows how organizations run AI inference for real-world applications like pneumonia detection to: See how Cloudera AI Inference Service enables teams deploy and monitor multiple models with full control, predictable costs, and no dependency on external APIs, so mission-critical AI keeps working when it matters most.

AI in Credit Underwriting: Improving Risk Assessment Accuracy

For years, credit underwriting was pretty straightforward. Lenders looked at a few fixed factors like credit scores and income, to decide who was worthy of a loan. If you didn’t fit the criteria, you were simply rejected. It worked, but only to a point. This approach left out many people who were actually creditworthy and often missed subtle shifts in market stability.

We built a Custom Transport for Vercel's AI SDK

Ably is a realtime messaging platform, it's a pub/sub product where you can publish messages to channels and clients subscribed to those channels will receive those messages in realtime. It turns out that the Ably realtime platform is really well suited to being the transport that sits between your AI models and the clients receiving the generated responses.

What is an MCP Registry? The Centralized Directory for AI Agents

A guide to learning how MCP registries help govern AI agent-to-tool connectivity AI agents are only as capable as the tools they can reach. When an agent needs to query a database, file a support ticket, or pull data from a CRM, it has to find the right tool, authenticate, and invoke it — all at runtime. The Model Context Protocol (MCP) standardizes how agents communicate with these tools. But MCP alone does not answer a fundamental question: how does the agent know which tools exist?