Levered gives your agent the infrastructure to optimize and personalize your product in real time.
| Optimization | Status | Variants | Traffic | Conversion | Lift | Confidence | Users | Segment |
|---|---|---|---|---|---|---|---|---|
| Onboarding FlowOptimizing signup-to-activation path | Active | 23 | 25% | 3.2% | ↑ 12.5% | 95% | 12.3K | New Users |
| Payment Page RedesignTesting checkout layouts and copy | Active | 45 | 50% | 4.8% | ↑ 8.3% | 89% | 8.7K | Premium |
| Pricing Calculator WidgetEnterprise pricing page conversion | Completed | 46 | 100% | 5.1% | ↑ 24.3% | 99% | 34.2K | Enterprise |
| Checkout FlowNew checkout variant exploration | Draft | 29 | 0% | — | — 0% | 0% | 0 | All Users |
| Hero CTA VariantsTesting headline and button copy | Paused | 18 | 0% | 2.1% | ↓ 1.2% | 42% | 3.1K | Returning |
How it works
Define a goal. Levered optimizes toward it, continuously.
Define the metric to optimize for, as well as the health metrics to monitor.
Tell Levered where to optimize. It writes the variants and wires up tracking.
Levered shifts traffic to winners and explores new variants autonomously.
Capabilities
Levered makes your product learn from every user — continuously, in production.
Works via MCP, CLI, or SDK. Your agent manages the full optimization lifecycle without leaving the terminal.
Multivariate, contextual learning algorithms out of the box.
Each user gets the variant most likely to convert, based on their context and behavior.
Every optimization informs the next. Continuously learns what works in which context across all optimizations.
Connects directly to BigQuery and your existing data stack. No data duplication or new pipelines.
Built-in holdout groups let you measure incrementality and prove that optimizations are driving real lift.
Why Levered
Classic platforms are built for manual testing. Levered is built for optimization at agent speed.
| Classic A/B testing | Levered | |
|---|---|---|
| Setup time | Days to weeks | Minutes |
| Team required | PM + Dev + Analyst | Just you + your agent |
| Variants tested | 2–4 per optimization | Dozens, in parallel |
| Statistical method | Fixed-horizon tests | Reinforcement learning |
| Optimization | Manual analysis | Autonomous, 24/7 |
| Learning | Starts from scratch | Compounds across tests |
See how Levered can optimize your product. Book a demo and get started in minutes.
Get a DemoFAQ
Levered is the optimization layer for AI-built products — the infrastructure that lets any product generated by a coding agent learn from its users at runtime.
Connect Levered to your warehouse, define a reward metric, and create an optimization using Levered's agent skills. Then integrate the Levered SDK. Levered's algorithm trains on your warehouse data and continuously improves variant selection to optimize for your goal.
Levered's optimization algorithms are far more data-efficient than fixed-horizon A/B tests, so it can test a wide array of variants with only a few thousand visitors per month.
Yes. Every user gets the experience most likely to work for them based on their context (e.g. device type, user state, traffic source). If no context is provided, Levered defaults to finding the globally best experience.
Levered is agent-first, with no UI-only path. Every capability is accessible via CLI and REST API with structured JSON, so your agent can set up optimizations, generate variants, and monitor results on its own. A Claude Code plugin bundles the CLI with skills for common growth-engineering workflows.