The architecture for trusted commercial decisions.
Levered is the operating layer between first-party commercial data and action. The platform connects signals, graph context, causal evidence, goals, permissions, and workflows so teams can move faster without giving up control.
It gives the business one place to understand, prove, decide, and control.
Levered is not a replacement for your CRM, ad platforms, warehouse, or commerce stack. It sits above them as a decision layer, reading signals from each system and returning a recommendation your team can inspect.
Bring first-party signals into one operating layer
Website events, CRM updates, campaign data, commerce outcomes, revenue targets, and agent requests can be read together instead of reviewed in separate tools.
Resolve signals into the Intent Graph
The platform attaches activity to people, accounts, products, campaigns, regions, evidence, goals, and outcomes.
Move from evidence to recommended action
OpenLift and the Goal Engine turn graph context into actions the team can inspect, approve, dismiss, or route into workflow.
Keep humans and agents inside boundaries
Every sensitive action can be scoped by purpose, principal, permission, evidence, and audit trail before anything moves.
Platform layers
Each layer has a specific job. Together they create the path from raw commercial signal to evidence-backed recommendation, controlled action, and outcome learning.
Browser, server, CRM, commerce, campaign, warehouse, and agent request inputs.
Identity, account, product, campaign, region, and agent-principal resolution.
Relationships between actors, signals, goals, evidence, economics, and outcomes.
OpenLift incrementality results, confidence tiers, prior outcomes, and experiment history.
Target pacing, constraints, trade-offs, ranked action queue, and outcome learning.
Human approval, agent scope, purpose checks, action policy, and audit log.
Alerts, reports, exports, CRM routing, budget recommendations, and operator review.
Workspace isolation, credential handling, revocation, data policy, and security review.
From signal to action, with control at every step.
The platform keeps a clear chain of reasoning so teams can understand how a recommendation was produced and why it should or should not be actioned.
Capture
A signal enters from the website, ad platform, CRM, commerce stack, warehouse, or AI agent request.
Resolve
Levered attaches the signal to known entities: person, account, product, campaign, region, goal, or agent.
Interpret
The platform classifies the signal as buying intent, research, demand shift, risk, constraint, or action request.
Prove
Evidence is attached from OpenLift, historical outcomes, confidence tiers, and experiment records.
Prioritise
The Goal Engine compares the action against targets, deadlines, constraints, and expected economics.
Permit
If the action touches workflow or automation, permission scope and audit requirements are checked.
Act
The team receives a recommendation or a controlled agent action is approved, denied, or narrowed.
Learn
Outcomes feed back into the graph so future decisions improve.
| REQ ID | Agent | Principal | Action | Scope | Decision | TS |
|---|---|---|---|---|---|---|
| AR-48221 | shop.gpt | acme.uk | price.compare(sku=SK-412) | read+action | GRANT | 12:04:11 |
| AR-48220 | atlas.claude | northstar-buyer | checkout.initiate(sku=SK-190) | read | REVIEW | 12:03:58 |
| AR-48219 | hermes.v2 | retail-uk | stock.check(sku=SK-701) | read+action | GRANT | 12:03:44 |
| AR-48218 | buyer.aria | london-labs | demo.book(sku=SK-233) | read+action | GRANT | 12:03:22 |
| AR-48217 | pilot.orion | acme.uk | report.generate(entity=A-442) | read | REJECT | 12:02:55 |
| AR-48216 | shop.gpt | retail-uk | price.compare(sku=SK-101) | read+action | GRANT | 12:02:31 |
POST /v1/agents POST /v1/agent/request GET /v1/goals/:id/agent GET /v1/intent/:entity_id GET /v1/evidence/:entity_id GET /v1/decisions/:entity_id // scopes commerce.read commerce.action intent.query evidence.query decision.query
Agent permissions are not a bolt-on. They are evaluated against the same context as human decisions: purpose, principal, scope, evidence, goal, and risk.
Integrations the platform is built around
Alpha onboarding starts with the sources that matter to the commercial goal. The platform does not need every system on day one; it needs the sources required to prove a decision loop.
Meta, Google, TikTok, affiliates, lifecycle, campaign exports, creative performance.
CRM, pipeline stages, account ownership, opportunity movement, lead routing, sales capacity.
Shopify or commerce tables, orders, products, stock, margin, returns, discount pressure.
Warehouse tables, CSV, server-side event batches, first-party web events, reporting exports.
Report generation, pricing requests, stock checks, routing requests, checkout or workflow actions.
Security, privacy, and governance
Levered is designed for teams that need to trust the decision path. The platform keeps data policy, credentials, permissions, and evidence visible enough for operators and leadership to inspect.
Levered is designed around the customer data you own: events, CRM, commerce, campaign, and operational sources. No cross-site tracking and no data resale.
Customer data is scoped to workspaces. Recommendations, goals, credentials, and agent policies are kept within the operating boundary.
Connector credentials are scoped, revocable, and inspected as part of onboarding. Sensitive keys are not exposed in product surfaces.
Important decisions and agent requests are logged with purpose, evidence, scope, action, status, and outcome.
The platform is built for decision support first. High-impact actions can require explicit review before budget, routing, pricing, or agent permissions change.
Teams can decide what level of evidence is required for different actions, from observation to causal proof.