Systems | Development | Analytics | API | Testing

smartbear

Testing at AI speed: We built a drift detection capability, then used it on ourselves

Sep 8, 2026 By Ewa Ostrowska In SmartBear
Drift detection stays narrow on purpose. It checks contract conformance – structure, status codes, schema – and deliberately leaves workflows and business logic to functional and end-to-end tests. That’s what makes it a fast add to our pipeline to prevent API drift. That narrow scope keeps it cheap to run. Fast execution, low flakiness, low maintenance cost – the kind of checks that make you more confident shipping. Catching drift early is the whole point.
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Thought Tank: Marketing in the Age of Agents

Sep 7, 2026 By ThoughtSpot In ThoughtSpot
Join us for a live broadcast of The Thought Tank: Marketing in the Age of Agents. Our host and CMO Micheline Nijmeh sits down with Katie Marcham, SVP Marketing EMEA at ThoughtSpot, to pull back the curtain on what it actually looks like to run a modern marketing organization on live data in one of the most complex, relationship-driven markets in the world. They'll cover the transformation Katie's led over the past year: leaner teams, smarter tools, and a tighter partnership with EMEA sales, all grounded in what the data is showing in real time.
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zymr

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

Sep 7, 2026 By Suhas Phartale In Zymr
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.
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octoperf

Migrating Your BlazeMeter Tests With an AI Agent

Sep 7, 2026 By Gerald Pereira In OctoPerf
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.
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oril

PropTech SaaS Development: The Capabilities That Make Real Estate Platforms Scale

Sep 7, 2026 By ORIL Team In ORIL
A scalable PropTech SaaS platform is built in layers: product workflows, multi-tenancy, integrations, analytics, security, and eventually AI. The right sequence depends on the product, but skipping the architectural foundations creates expensive constraints later. That sequencing is an architecture decision as much as a product one.
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[Finance Demo] - AgentSpot Use Case - Collections Forecast

Sep 4, 2026 By ThoughtSpot In ThoughtSpot
Every month, finance teams rebuild their collections forecast by hand, copying and pasting from disconnected files and hoping nothing breaks. In this video, we use AgentSpot to build a Collections Forecast Agent that connects to accounting files, NetSuite, and live bookings data to automate the full monthly rebuild, reconcile actuals against forecast, and output a traceable Excel workbook your whole team can work from.
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databox

How to Answer Any Performance Question with an AI Analyst

Sep 4, 2026 By Nevena Rudan In Databox
Ask one question with a time range, a metric, a comparison, and a goal. The AI analyst does the gathering. You keep the judgment. To answer any performance question in minutes, ask Databox’s AI Analyst, Genie, one well-built question that includes: a time range, a metric, a comparison, and a goal. Genie queries the data sources you’ve connected, runs the calculation, and returns the answer with a recommendation attached.
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testhouse

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

Sep 4, 2026 By Testhouse In Testhouse
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.
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ably

Raw WebSockets for AI streaming: when patching stops paying off

Sep 3, 2026 By Madeleine Quinn In Ably
Raw WebSockets drop connections, lose track of canceled responses, and don't natively reach a second device. If your AI streaming feature has been in production for a while, you've probably already built a fix for at least one of these and found another one waiting. Reconnection, cancellation, multi-device delivery, and crash detection are the four problems raw WebSockets leave for you to solve, and each is its own piece of infrastructure to build. Solve one, and the other three remain unsolved.
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zymr

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

Sep 3, 2026 By Jay Kumbhani In Zymr
‍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.
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