Systems | Development | Analytics | API | Testing

Migrating Your BlazeMeter Tests With an AI Agent

Our BlazeMeter to OctoPerf Maven plugin is archived. What replaces it is not another tool to install: OctoPerf 17 ships a BlazeMeter migration playbook for AI agents. Real prompts, real output, run against a real BlazeMeter account. The plugin worked: one mvn command copied your workspaces, projects and JMeter scripts into OctoPerf. But a Maven command cannot ask you a question, so it never said which tests were worth moving, never brought your load profiles, and never replayed what it imported.

Insurance Underwriting Automation: Architecture, AI Models, and ROI (2026)

Insurance underwriting automation integrates data ingestion, validation, risk scoring, decisioning, and policy workflows. It connects core insurance platforms with rules engines, AI models, and external data sources. Insurance underwriting automation in 2026 looks markedly different from earlier pilots.

Agentic AI in Banking: How Autonomous AI Is Changing Financial Services

Quick answer: Agentic AI in banking refers to AI systems that don’t just generate text or answer questions – they take a goal, break it into steps, use tools and data sources, make decisions, and complete multi-step workflows (like investigating a fraud case or processing a KYC file) with minimal human intervention, looping in a person only for genuine judgment calls. Walk into any banking technology conference in 2026, and you’ll notice the conversation has quietly shifted.

[Product Demo] AgentSpot Use Case - Automate Release Notes

Release notes are the thing that always gets written last, usually by whoever has the least context, usually the morning after ship day. Everything you need is already sitting in GitHub, it just isn't in a form anyone outside engineering can read. In this video, we use AgentSpot to build a Release Notes Workflow that reads what's been merged in GitHub, translates the changes into human-readable notes, posts them to your team's Slack channel, and keeps a running Slack canvas so every release stays in one place.

AI in Claims Processing: What's Actually Working in 2026

‍AI claims processing applies predictive models, machine learning, computer vision, and generative AI across claims workflows. These technologies analyse documents, images, policy terms, historical records, and structured claim data. Insurers use AI for document extraction, claim triage, fraud detection, damage assessment, and adjuster assistance. Predictive models classify claims, estimate severity, and identify cases requiring specialist review.

From IoT Data to AI-Ready: The Edge Solution

Is your data actually ready for AI? While companies rush to deploy machine learning models, 83% of executives realize that high-value, real-time data is trapped at the physical edge—on factory floors, inside hospitals, and at retail terminals. With billions of connected IoT devices, managing this data creates massive hidden headaches like security risks and pipeline blind spots. True AI readiness starts at the edge. Bridge the gap between your edge devices and your AI goals today.

[Product Demo] AgentSpot Use Case - PM Jira Assistant

Writing tickets is the tax every PM pays. You know exactly what needs to get built, then you spend an hour turning it into properly scoped Jira issues with acceptance criteria, labels, and the right epic. AgentSpot does the writing for you. In this video, we use AgentSpot to build a Product Assistant that turns a rough feature idea into fully drafted Jira tickets, pulls in context from your existing backlog so nothing gets duplicated, and files them to the right epic ready for grooming.

Ep 88 | AI Adoption vs. Adaptation: What Problem Are You Solving?

Paul McDonough-Smith estimates that many business leaders would struggle to define their organization’s problem clearly in fewer than 25 words. With AI, that lack of clarity can quickly turn into fragmented solutions and misplaced expectations. In this episode of The AI Forecast, Paul Muller sits down with Paul McDonough-Smith, a Visiting Senior Lecturer at MIT Sloan School of Management and a Senior Advisor to NASA's Goddard Space Flight Center, to explore how organizations can approach AI with greater clarity and purpose.

How AI Is Rebuilding the Insurance Claims Automation Lifecycle: The 2026 Guide

AI is restructuring how insurers run the claims lifecycle end to end from first notice of loss through payment and closure. This guide breaks down where AI insurance claims automation is delivering measurable results in 2026, the reference architecture behind it, and what insurers should prioritize first. Insurance claims automation 2026 connects AI, workflow orchestration, and core systems across the claims lifecycle the specific discipline behind Zymr’s own claims processing automation practice.

Add resumable streaming and reliable tool calling to your OpenAI agent

If you build an agent against OpenAI's Responses API then the simplest way to get output to the user is streaming over HTTP/SSE. If the user refreshes the page, loses connection, switches devices, or needs to approve a tool call, then there's nothing in the API to help you. AI Transport is Ably's session layer for agent-to-user conversations. An agent built on it gets resumable streams, multi-device sessions, and approval gates that wait for a human user, without deploying additional infrastructure.