Levered
PRODUCT · INTENT GRAPH

The commercial graph that explains what to do next.

The Intent Graph is the decision layer underneath Levered. It connects people, accounts, campaigns, products, regions, agent requests, evidence, economics, and outcomes so every commercial signal has context, proof, and a recommended action.

ENTITY TYPES
12
INTENT TYPES
06
OUTPUT
DECISION
DATA POLICY
1P ONLY
WHAT IT IS

Not a warehouse. Not a dashboard. A graph of commercial cause and effect.

Most teams store activity in separate tools: ads in platforms, accounts in CRM, orders in commerce, behaviour in analytics, and agent requests in workflow systems. The Intent Graph joins those pieces into a living map of who is showing intent, what triggered it, how reliable it is, what it could be worth, and what should happen next.

RESOLVE

Know who or what the signal belongs to

A page view, ad click, CRM update, order, support request, or agent action is not useful on its own. The graph attaches it to a person, account, campaign, product, region, agent, and commercial goal.

INTERPRET

Turn raw activity into commercial intent

Levered classifies whether the activity suggests buying readiness, research, churn risk, market demand, campaign response, stock pressure, or an agent permission request.

PROVE

Separate signal from noise

The graph links intent to evidence from OpenLift, prior outcomes, confidence tiers, and business constraints so decisions are not based on attribution screenshots alone.

DECIDE

Make the next action explicit

Every traversal ends in a recommendation: scale, pause, hold, retest, route, discount, restock, generate a report, or approve a scoped agent action.

LIVE GRAPH · WORKSPACE=ACMEtraverse=signal→evidence→decision
STREAMING
ENTITYSIGNALINTENTEVIDENCEDECISIONACTIONPersonu_84021Agentgpt-agent/1.4CampaignC-104 · LondonRegionUS-NYCPricing viewed3× · 42sAgent requestscope=quoteCreative clickedcr_9a2Region lift+18.2%Buying intent0.87Agent intent0.71Market intent0.63OpenLiftTier 3 · p<0.01DecisionD-9917Scale +£800/daybudget ΔGrant scopeagent permission
SIGNALS/SEC1,942HOT · PERSONACT
EVENT LOG · TAILLIVE
    GRAPH · LIVE · 14 EDGES · 15 NODES

    What the graph connects

    Every node carries commercial meaning. The value is not in storing the nodes; it is in understanding the relationships between them and updating those relationships as outcomes arrive.

    PERSON

    Visitor, lead, user, customer, or buyer identity.

    COMPANY

    Account, client, buyer organisation, or pipeline opportunity.

    AGENT

    AI shopping, research, reporting, routing, or commerce agent.

    CAMPAIGN

    Meta, Google, TikTok, email, lifecycle, affiliate, or partner stimulus.

    CREATIVE

    Ad, angle, hook, landing page variant, offer, or message.

    PRODUCT

    Plan, SKU, service, category, margin profile, or offer.

    REGION

    Country, city, store catchment, sales territory, or treatment market.

    EVENT

    Page view, checkout, purchase, demo request, CRM update, or agent request.

    SIGNAL

    Interpreted event such as pricing intent, comparison, urgency, or risk.

    EVIDENCE

    OpenLift result, holdout, confidence tier, prior outcome, or constraint.

    DECISION

    Scale, pause, route, retest, approve, reject, report, or action.

    OUTCOME

    Revenue, margin, CAC, ROAS, pipeline, conversion, retention, or payback.

    GRAPH DYNAMICS

    Intent is not static. It strengthens, weakens, compounds, and decays.

    A useful graph has to behave like the market. It should understand timing, repetition, proximity to money, causal proof, commercial constraints, and feedback from outcomes.

    RECENCY

    Fresh signals carry more weight. A pricing page visit today matters more than a whitepaper download six months ago.

    FREQUENCY

    Repeated intent across channels is stronger than one isolated event. The graph compounds patterns across web, CRM, ads, commerce, and agents.

    PROXIMITY

    Signals close to money, such as checkout, demo request, quote request, or stock check, are weighted differently from early research.

    CAUSALITY

    A channel claiming credit is not enough. Levered can connect signals to OpenLift evidence so the business knows whether activity caused incremental value.

    CONSTRAINTS

    The graph understands budget, stock, margin, sales capacity, region, campaign limits, and permission scope before recommending action.

    FEEDBACK

    Outcomes flow back into the graph. When a recommendation succeeds or fails, the next decision becomes better calibrated.

    The economics the graph unlocks

    The Intent Graph is valuable because it connects commercial behaviour to money. It helps teams decide where to spend, what to route, when to hold, which markets to test, and which actions should be allowed.

    BUDGET ALLOCATION

    Spend moves faster

    Shift budget toward campaigns, regions, creatives, and audiences with rising intent and evidence of incremental lift.

    CAC & ROAS

    Efficiency becomes explainable

    Understand whether CAC is improving because demand quality is changing, creative is working, or a platform is simply over-crediting itself.

    PIPELINE QUALITY

    Sales works the right accounts

    Route accounts when website behaviour, CRM movement, fit, and timing indicate readiness instead of relying on static lead scores.

    MARGIN CONTROL

    Growth respects profit

    Tie product demand to margin, stock, return rate, region, and discount pressure before recommending scale or promotion.

    AGENT RISK

    Automation gets boundaries

    AI agents can request reports, pricing, routing, or checkout actions, but the graph checks purpose, principal, scope, evidence, and permission.

    OPERATING SPEED

    Meetings become decisions

    Replace weekly dashboard interpretation with live recommendations that show the signal, evidence, economics, and proposed action.

    How questions become answers

    Every recommendation starts as a traversal: from actor to behaviour, behaviour to intent, intent to evidence, evidence to economics, and economics to a decision.

    AGENTgraph.traverse()
    PrincipalAgentRequestIntentEvidenceScopePermissionAction
    HUMANgraph.traverse()
    PersonBehaviourIntentProductConstraintDecisionOutcome
    MEDIAgraph.traverse()
    CampaignCreativeRegionSignalOpenLiftEconomicsBudget Decision

    Decisions businesses can see

    Levered is designed to make the output plain enough for a team to act on and detailed enough for finance, leadership, and operators to understand the reasoning.

    Performance marketingdecision.output

    Scale London prospecting by +£800/day because treatment markets show Tier 3 lift, intent is rising, and CAC remains inside target.

    B2B growthdecision.output

    Route Acme Corp to sales today because pricing intent, return visits, account fit, and product engagement crossed the readiness threshold.

    Ecommerce tradingdecision.output

    Hold discounting on Product B because demand is rising organically, stock is limited, and margin would fall below the goal constraint.

    Agent permissionsdecision.output

    Approve a scoped report-generation action because the agent has a verified principal, a narrow purpose, and supporting evidence.

    WHY IT MATTERS

    Businesses do not need more disconnected data. They need a better decision surface.

    Marketing sees which spend is creating incremental value, not just which platform claimed the conversion.

    Sales sees which accounts are genuinely warming up and why now is the right moment to act.

    Commerce sees demand, margin, stock, and campaign pressure in the same decision path.

    Operations can let AI agents act inside boundaries instead of giving them broad, risky access.

    Leadership gets a clearer line from signals to economics to decisions, which makes performance easier to defend.

    Give every signal context. Turn context into action.