Backed by builders from Meta, Nvidia & OpenAI

Let your product
optimize itself.

Levered gives your agent the infrastructure to optimize and personalize your product in real time.

levered — optimizations

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

Manage goals, not single tests

Define a goal. Levered optimizes toward it, continuously.

Set a goal

Define the metric to optimize for, as well as the health metrics to monitor.

"Use purchase_rate as the goal metric"

Prompt your optimization

Tell Levered where to optimize. It writes the variants and wires up tracking.

"Optimize the checkout flow for first-time buyers"

Approve and run

Levered shifts traffic to winners and explores new variants autonomously.

+12.5% conversion · 23 variants · 95% confidence

Capabilities

Optimization that keeps learning

Levered combines data-efficient optimization algorithms with AI-assisted variant generation.

Built for your agent

Works via MCP, CLI, or SDK. Your agent manages the full optimization lifecycle without leaving the terminal.

A/B → f(x)

Multivariate, contextual learning algorithms out of the box.

Personalization at runtime

Each user gets the variant most likely to convert, based on their context and behavior.

Optimization memory

Every optimization informs the next. Continuously learns what works in which context across all optimizations.

Warehouse native

Connects directly to BigQuery and your existing data stack. No data duplication or new pipelines.

True incrementality

Built-in holdout groups let you measure incrementality and prove that optimizations are driving real lift.

Why Levered

A different approach

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

Let your productoptimize itself.