The whole funnel, connected

Every touch, person, account, opportunity, and dollar linked in one graph, so attribution, forecasting, and agents traverse the same reality instead of joining tables and hoping.

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Module 01 · Why a graph

Tables lose the relationships

Account graphConnected

Node	Linked to	Edges
Account · Cursor	Opportunity	3
Buying group	People	7
Opp · $140K	Touches	22
Touch · LinkedIn	Person	1

A lead, an account, three opportunities, and forty touches live in separate tables joined by brittle keys. The relationships, who influenced what, which touch preceded the deal, are exactly what attribution and forecasting need, and exactly what a row-and-column join throws away.

Touches, people, accounts, and opps as connected nodes
Relationships preserved, not flattened into a join
Multi-threaded buying groups mapped to the deal
Influence paths that a flat table cannot express

Module 02 · Stitched journeys

Every journey, end to end

Journey · CursorLive

Step	Touch	Person	Stage
1	Ad click · LinkedIn	Anonymous	Visit
2	Content · SEO	VP Eng	MQL
3	Demo request	VP Eng	SQL
4	Exec call · Gong	CTO	Opp
5	Closed won	CTO	Won

The graph stitches the full path from first anonymous touch to closed revenue, across people and channels, so you can see the sequence that actually created the deal, not the last click before it.

First-touch to closed-won, stitched across people
Cross-channel and cross-device paths joined
Buying-group journeys, not single-contact trails
The real sequence behind the deal, in order

Module 03 · What it powers

One graph. Every model reads it

Powered by the graphLive

Nodes

0.0M

Touches linked

Journeys stitched

Attribution credits the right touches, the forecast traces pipeline to its source, and agents traverse the same connected reality. The graph is the substrate, the rest of the platform just queries it.