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Design, model, and validate complex 3D interconnect architectures with a powerful standalone design environment.
Automate transmitter and receiver validation across next-generation I/O, memory, and fabric interfaces.
Strengthen 1.6T network reliability for AI-scale workloads from transceivers to interconnects.
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With extra memory and storage, these enhanced NPBs run Keysight's AI security and performance monitoring software and AI stack.
Explore end-to-end workflows spanning IC design, validation, wafer test, and photonics.
Save up to 50% on our latest instruments with eligible Keysight or competitor trade-ins.
Maximize accuracy and performance with precision accessories engineered for Keysight instruments.
Save up to 50% on our latest instruments with eligible Keysight or competitor trade-ins.
Four channels per 1U of rack space, up to 1 GHz bandwidth, and multi-oscilloscope synchronization.
Purpose-built solutions engineered for the design and test challenges unique to your industry.
Use Cases mapped to every stage of your product lifecycle, from design through operations.
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Authoritative application notes, data sheets, reference designs, and test procedures to accelerate design and validation decisions.
Hands‑on bootcamps that teach system design, test methods, and production workflows engineers can apply immediately.
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Explore methodologies, test strategies, and technical resources for designing, validating, and scaling AI systems and networks.
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AI test automation for QA teams running real end-to-end user journeys, across web, mobile, API, and complex systems like Citrix.
AI software testing built for the real world, not the demo.
Most test automation tools were built for simple web apps. Modern enterprise software isn't simple. It works across browsers, mobile, APIs, mainframes, virtualized desktops, and regulated environments, where traditional scripted tests often break when the UI or environment changes.
Eggplant is different. Instead of relying on large libraries of manually scripted paths, your QA team models how the application is used. The AI then generates and runs tests through that model, with scripts handling the UI and API actions.
You get broader end-to-end coverage. Less maintenance. Faster feedback. Evidence-based release decisions instead of crossed fingers.
Keysight Generator reads your requirements file and produces Gherkin scenarios and manual test cases automatically, without manual test design effort. It runs on-premises, keeping your requirements data inside your environment.
Point it at your engineering stack.
Eggplant tests at the UI level with image recognition, so it runs on any engineering application that renders on a screen, SAP, Teamcenter, Windchill, NX, 3DEXPERIENCE, Creo, and the integrations between them. No API access, no vendor-specific connectors, no code changes. A single test can walk one workflow across all of them at once, the way engineering data moves from design through production.
Eggplant works from a model of how people move through your application, then generates and runs thousands of paths, including the combinations no one would script by hand. It reads the screen the way a person does, so it reaches interfaces DOM- and code-based tools can't: packaged software, legacy systems, embedded UIs, virtual desktops. And one test can carry the whole journey, through the UI, then into the database to confirm the data landed.
Take the tour and watch it find the paths your scripts miss.
AI-driven testing across web, desktop, mobile, API, Citrix, and complex multi-system environments. Validate complete user journeys with results, screenshots, logs, and analytics.
Test the UI the way a real user sees it with image and text recognition, not DOM selectors. Tests remain stable regardless of what changes in the front-end stack.
AI generates and prioritizes paths through the model, including combinations no human would script. Update the model when the app changes, then the AI re-explores.
Validate API behavior and end-to-end workflows in one platform. Combine API checks with UI automation to catch integration bugs before they break the user experience.
Connect to CI/CD through public APIs and integrations including Jenkins and Bamboo. Run automated tests as part of any build or release process.
Reuse the same automation approach across browsers, operating systems, devices, and remote environments, without depending on DOM locators or object models.
Use Case
Use Case
For most automation teams, maintaining test scripts costs more time than writing them. Every UI change, theme update, or redesign breaks pixel-matched references, and engineers spend hours fixing scripts instead of extending coverage. Find by Description changes that equation entirely, using AI to locate UI elements from plain-English descriptions so tests stay current without maintenance.
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レポート
レポート
eBooks
"Eggplant enabled the team to move from completing a 10-hour test event every three days to running a 24-hour test event every day."
"Eggplant enabled the team to move from completing a 10-hour test event every three days to running a 24-hour test event every day."
“...we succeeded in reducing the man-hours by 92% across the entire testing process when compared to conventional manual testing.”
Ms. Mio Azuma
Researcher
“...we succeeded in reducing the man-hours by 92% across the entire testing process when compared to conventional manual testing.”
Ms. Mio Azuma
Researcher
“The execution time for the Flightkeys UI systems has been reduced by 93%, reducing three weeks of manual testing to just one day.”
Jerry Park
Automation Engineer
“The execution time for the Flightkeys UI systems has been reduced by 93%, reducing three weeks of manual testing to just one day.”
Jerry Park
Automation Engineer
“Keysight Generator has significantly improved productivity. It took only 30 minutes to generate test assets for 48 requirements; work that previously took about three weeks of manual scripting”
QA Manager
“Keysight Generator has significantly improved productivity. It took only 30 minutes to generate test assets for 48 requirements; work that previously took about three weeks of manual scripting”
QA Manager
“We are amazed by the engagement and no other vendor comes close to providing the support that Eggplant delivers.”
Michelle Divecchis
Quality Assurance Manager
“We are amazed by the engagement and no other vendor comes close to providing the support that Eggplant delivers.”
Michelle Divecchis
Quality Assurance Manager
Eggplant is an AI-powered test automation platform from Keysight for end-to-end software testing across web, mobile, API, desktop, and complex systems like Citrix. Teams model user journeys and system states; Eggplant generates and runs paths through those models using functional execution assets. It is used by enterprises in regulated and complex environments to expand coverage, reduce maintenance, and improve release confidence.
The AI explores model-based test paths that a human may not think to write, including edge cases, regression risks, and unusual user behaviors. Defects can surface earlier in the cycle when they cost less to fix. Coverage expands without requiring teams to manually script every path. Customers can reduce manual testing and maintenance effort, depending on scope and implementation maturity.
Eggplant can test web, desktop, mobile, API, Citrix/VDI, mainframe, kiosk, embedded, and proprietary GUI environments where visual or remote access is available. It supports Windows, macOS, Linux, iOS, and Android targets through supported connections and integrations, and API tests can be included alongside UI workflows.
By reducing the need to script every path by hand. When the application changes, teams update the model and reusable snippets, then Eggplant re-explores the workflows instead of forcing engineers to rewrite large sets of linear scripts. That helps teams maintain broader regression coverage with less manual rework.
Yes. Eggplant is designed for enterprise-scale testing, including distributed execution, centralized test asset management, CI/CD integration, results analytics, and requirements traceability. It is relevant for regulated industries including aerospace, defense, digital engineering and manufacturing, and financial services where evidence, auditability, and release confidence matter.
Scripted automation requires engineers to write each test path by hand. When the application changes, affected scripts often need to be updated. Model-based testing flips this: engineers build a model of the application's states and actions, and the AI generates and runs paths through that model. When the application changes, teams update the model or reusable snippets and the AI re-explores. This produces broader coverage with less maintenance than maintaining large sets of linear scripts.
JetBlue cut testing time 93%. Fujifilm reduced testing man-hours by 92% versus manual.
何をお探しですか?