DeepXplore delivers two independent but complementary products. Use either on its own or combine them for a fully automated, closed-loop performance intelligence system.
Simulate production-like conditions, test complete user flows, generate GDPR-safe data, and run continuous 24/7 validation — without replacing anything in your stack.
Real traffic is never flat. Peak hours, holiday surges, gradual ramps — DeepXplore models production-like curves so your autoscalers and infrastructure are validated against conditions that actually mirror production. Constant-rate testing misses the bugs that matter.
Real users don't call a single API — they browse, add to cart, check out, and pay. DeepXplore chains requests into full stateful journeys with automatic data extraction between steps, turning isolated endpoint tests into true system-level validation.
Import your OpenAPI specifications and DeepXplore automatically generates comprehensive test scenarios with distribution-aware synthetic data — from GDPR-safe customer profiles to sanction-list edge cases — so your tests reflect reality, not random noise.
Detailed insights into infrastructure performance across every test run. Track trends over time, compare against baselines, analyze system behavior, and produce reports that translate raw data into actionable decisions.
Instantly identify the root cause of any performance incident. Parallel AI agents correlate telemetry, code changes, deployments, and infrastructure events to deliver ranked findings in seconds — triggered by DeepXplore's own tests or your existing alerting stack.
Continuous baseline traffic builds dense historical data that reveals trends days before they breach SLAs. Models trained on your traffic account for seasonality and repeated bursts, distinguishing genuine degradation from normal variance.
Models specifically trained on your traffic data account for seasonality, deployment markers, and repeated bursts. Detect slow memory leaks, creeping latency, and resource exhaustion days before they breach SLAs — before users are ever impacted.
When an anomaly is detected, parallel AI agents query your telemetry, code repositories, deployment history, and incident systems simultaneously. A final synthesizer correlates findings into ranked, evidence-backed root causes — delivered in seconds, not hours. No war room required.
Shared capabilities that underpin both products — integrations, alerting, and security by design.
Connects to your existing stack out of the box. No rip-and-replace required. DeepXplore adds intelligence on top of the tools you already use — Prometheus, Datadog, Elastic, GitHub, GitLab, Jenkins, PagerDuty, OpsGenie, Slack, Teams, Jira, and many more.
A comprehensive alerting suite that triggers your alerting system of choice when thresholds are breached, anomalies are detected, or forecasted violations are predicted. Works as both an output channel and an input trigger for root cause analysis.
Built with a security-first mindset from the ground up. Credentials and secrets are stored in an encrypted, isolated secret store — never hard-coded, never exposed. Hierarchical access control ensures the right people see the right data.