Systems | Development | Analytics | API | Testing

Chat with Your Data: The Official Databox MCP

Jan 27, 2026 By Databox: Modern BI Software In Databox
Your AI is brilliant, but it’s blind. Until now. We are thrilled to launch the official Databox MCP (Model Context Protocol). This open standard server bridges the gap between your business data and your favorite AI tools, turning general-purpose LLMs into specialized data analysts that know your business data. Stop manually exporting CSVs or taking screenshots of dashboards. With Databox MCP, you can connect 130+ data sources (Google Analytics, HubSpot, Salesforce, Stripe, and more) directly to tools like Claude, ChatGPT, Cursor, and n8n.
View Video
antino

AI-Powered Loan Management Software Development

Jan 27, 2026 By Radhakanth Kodukula In Antino
The world has really come a long way due to widespread digital transformation adoption! And, it’s no secret that it has changed the FinTech sector drastically. In light of this evolution, it has become imperative for lenders to adapt and refine their operations with a well-defined Loan Management System.
Read Post
honeybadger

How to build a Copilot agent

Jan 26, 2026 By Joshua Wood In Honeybadger
A customer recently shared their debugging workflow with me. When an error shows up in Honeybadger, they import it to Linear, manually add context about where to look in the codebase, then assign GitHub Copilot to investigate. It works, but they asked a good question: could Copilot just access Honeybadger directly? The answer is yes—and it's easier than I expected.
Read Post
alphabin

Top 25 Test Generating Tools

Jan 26, 2026 By Pratik Patel In Alphabin
Software testing was once a slow and repetitive process that developers accepted as unavoidable, often consuming significant time without delivering proportional value. Traditional manual testing struggled to scale with growing application complexity and rapid release cycles. In 2026, test generating tools have reshaped this landscape by introducing automated test generation, AI-driven logic, and intelligent coverage strategies.
Read Post
ClearML

Multi-Node Training with ClearML

Jan 26, 2026 By ClearML In ClearML
Orchestrating distributed AI workloads Distributed (multi-node) training has become a requirement rather than an optimization for many modern AI workloads. As model sizes grow, datasets expand, and training timelines tighten, teams increasingly rely on multiple machines, often with multiple GPUs each, to complete training efficiently.
Read Post
kong

A Developer's Guide to MCP Servers: Bridging AI's Knowledge Gaps

Jan 26, 2026 By Adam DeHaven In Kong
Have you ever asked an AI assistant to generate code for a framework it doesn't quite understand? Maybe it produces something that looks right, but the syntax is slightly off, or it uses deprecated patterns. The AI is working hard, but it lacks the specific context it needs to truly help you. The Model Context Protocol (MCP) was designed to bridge this knowledge gap by giving AI assistants access to domain-specific knowledge and capabilities they don't have built in.
Read Post

Can We Still Trust the Code? #speedscale #qualityassurance #digitaltwin #trust #devops

Jan 26, 2026 By Speedscale In Speedscale
The "Velocity Gap" is real. AI like Claude and GitHub Copilot are pumping out code faster than ever, but there’s a catch: Engineers don't trust it yet. We’re moving away from the old days of "clicking around" in a test environment, but how do we verify code at the speed of light? Ken breaks down why the future of QA isn't just "testing," it’s simulation. Video collab with @ScottMooreConsultingLLC Learn More: speedscale.com.
View Video

Copyright © 2026 OpsMatters™. All rights reserved.