Systems | Development | Analytics | API | Testing

Ricoh's AI-Powered Transformation: A Seamless User Experience with ThoughtSpot

Discover how @ricoheurope transformed its user experience with ThoughtSpot Embedded Analytics! In this video, Ricoh's Director of Innovation shares how our developer-friendly embedding creates a seamless, branded look, and how the Spotter AI Agent empowers users to get instant data insights, freeing up internal teams.

The real key to culture change = access to real-time data

Cultural change doesn’t start with strategy — it starts with visibility. Andrew Wood explains how real-time access to data helps teams shift their mindset and drive action. With Databox, outdated reporting cycles are replaced by on-demand insights — turning finance and ops from reactive to proactive. Already using Databox to understand your own business? Then it’s time to help your clients—and grow your bottom line.

How Coinbase Simplifies ML Workflows With Snowflake

Hear from Tuhin Ghosh, Head of Data Science for the Platform Product Group at Coinbase, as he shares how Snowflake ML capabilities are simplifying the way Coinbase delivers machine learning at scale. From eliminating complex, multi-tool pipelines to enabling ML workflows directly on the same platform as the Snowflake data, Coinbase is reducing model production time from months to hours.

Kong AI Gateway: Prompt Compression

High token consumption from long prompts can degrade model performance and lead to expensive, inefficient LLM operations. This video demonstrates how to solve that problem using Kong's AI Gateway. AI Prompt Compressor Plugin: See how this plugin intelligently compresses incoming prompts before they hit the model. It summarizes context, removes redundant information, and trims excess tokens—all while preserving the original meaning.This could lead to significant cost savings and improved performance.

What is an AI Gateway?

Ever wondered what an AI Gateway is? Think of it as an airport for your AI traffic! We break down how an AI Gateway can: Act as a central access point for different AI models. Provide security for your LLM prompts. Route traffic to the best model for the job. Save on AI costs with features like response caching. Learn the basics of this essential tool that helps manage AI and LLM costs, security, and efficiency.

Xray Requirement Coverage explained: automating quality with Test Executions

Xray’s Requirement Coverage refers to how defined requirements inside a specific project are being validated by tests. Each requirement – whether Jira Story, Epic or Feature - should be connected to one or more test cases. When these tests are being executed and the results are being reported, the coverage status of the requirements automatically updates. Bottom line, only creating tests is not enough.

TCP Proxy: Expose TCP Ports Publicly

Today, we’re announcing the public preview of TCP Proxy — a new way to expose TCP ports publicly. Until now, services on Koyeb could only be publicly exposed via HTTP, HTTP/2, WebSocket, and gRPC protocols. TCP-based workloads were limited to private access within the mesh network for service-to-service communication. With TCP Proxy, that changes. You can now make any TCP service publicly accessible with minimal configuration.

How to Build a Multi-LLM AI Agent with Kong AI Gateway and LangGraph

In the last two parts of this series, we discussed How to Strengthen a ReAct AI Agent with Kong AI Gateway and How to Build a Single-LLM AI Agent with Kong AI Gateway and LangGraph. In this third and final part, we're going to evolve the AI Agent with multiple LLMs and Semantic Routing policies across them. In this blog post, we'll also explore new capabilities introduced in Kong AI Gateway 3.11 that support other GenAI infrastructures.

Benefits of Test Management in Software Testing Life Cycle

Automation testing for websites is one of the fastest ways to improve software quality while speeding up delivery. It removes repetitive manual work and ensures that every release is tested thoroughly before going live. Effective automation testing becomes even more powerful when paired with a solid test management strategy. The benefits of test management in testing process include better organization, clearer visibility, and improved collaboration across teams.