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Prevent outages with AI-driven production simulations

Autonomously generate and run hundreds of scenarios trained on actual user traffic, so you can quickly identify functional and performance defects.

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Mimic real-life scenarios, test performance, and create desired conditions of third party and internal backends to prepare for production.

No need to spin up costly new environments each time you test.
AI-generated mocks provide what you need, when you need it.
Skip the manual scripts and environments. Get immediate CICD feedback, test lots of code quickly and ship faster.
Load and Performance Testing

Confirm performance under REALISTIC load

Don’t guess. Maximize your revenue opportunity and be confident that new code changes can scale in production simulations.
Prevent outages, uphold SLAs, and protect the customer experience.

Service Virtualization and Mocking

AI-generated mocks for internal and external dependencies

Auto-identify necessary backends for any API and autogenerate mocks for reliable, scalable development and testing.
No need to manage costly end-to-end environments or limit  access.
AI Data Generation

Augment production simulations with
AI-generated data

What’s better than production simulations? Autogenerating more permutations without having to wait on data refreshes and PII scrubbing.
Self-service for your dev and test data needs.
API & Kubernetes Observability

Quickly pinpoint and resolve problems

Drill down into specific subsets of traffic and view the exact details of each call, including message payloads, headers, cookies, authentication tokens, and more.

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“Speedscale gave us clear insight on the upper load limit of our software. Whereas with K6, it was more binary, like a PASS/FAIL grade. Speedscale took it one step further to help us understand, based on transactions per second, exactly where our breakpoints were. We felt more confident in where our service could be.”

How it works


Train Speedscale’s AI on your API calls via sidecar, Postman collection or logs

AI Analysis

Our AI detects auth tokens, dates, and data patterns to simulate production

Generative Simulation

Run your code changes against  realistic production simulations

You're in good hands

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Catch performance defects before production