How It Works

The Architecture Behind Intelligent GTM

Context Graph is Warmly's unified data layer — connecting every signal, contact, account, and engagement into one real-time system. Here's how it works and why it matters for your GTM motion.

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How does Context Graph work?

Context Graph operates in four continuous stages

01 • Ingest

Signals from first-party, second-party, and third-party sources flow in continuously

02 • Resolve

Identities are matched and unified (person to account, signal to contact)

03 • Enrich

Records are enhanced with firmographic, technographic, and contact data

04 • Activate

Unified context powers real-time actions through Inbound Agent and TAM Agent

Key capabilities

Real-time processing

Signals resolve in seconds, not hours

Identity resolution

Person-level matching across sources

Deduplication

Single source of truth for each account/contact

Bidirectional sync

Writes back to CRM with full attribution

What makes it different

Not a data warehouse (it's real-time, not batch)

Not a CDP (it's purpose-built for B2B GTM)

Not just enrichment (it connects and activates)

Your GTM Data Is Scattered

The typical B2B stack

Intent data in one tool

Website analytics in another

CRM with incomplete records

Enrichment vendor for firmographics

Marketing automation with its own contacts

Sales engagement with sequence data

Not just enrichment (it connects and activates)

The problems

No unified view

Same contact exists in 5 systems, none complete

Manual reconciliation

Ops spends hours connecting dots

Stale data

Batch processing means yesterday's signals

Broken attribution

Can't connect touchpoints to outcomes

Siloed actions

Marketing nurtures while sales sequences — same person

Context Graph solves this by being the connective layer.

Continuous Signal Ingestion

Context Graph ingests data continuously from multiple sources:

Key design

Real-time streaming (not batch)

Normalized to common schema

Full event history retained

Source tracking for attribution

Identity Resolution at Scale

Matching signals to people and people to accounts:

Resolution methods

IP-to-company matching

Cookie identity persistence

Email pixel matching

LinkedIn data graph

CRM contact matching

Deterministic + probabilistic matching

Complete Records, Not Partial

Once resolved, Context Graph enriches:

Account enrichment

Firmographics (industry, size, revenue)

Technographics (current tech stack)

Social presence

Funding and financial data

Contact enrichment

Title and seniority

Email and phone

LinkedIn profile

Role classification (persona)

Enrichment approach

Multi-vendor waterfall (best data wins)

Continuous refresh (not one-time)

Human-verified critical data

Confidence scoring

Learn about Full Enrichment

Context Powers Action

The unified context immediately activates:

Inbound Agent uses context to:

Personalize chat by account and persona

Route conversations to the right rep

Trigger warm experiences

Book meetings with context

TAM Agent uses context to:

Score intent accurately

Build dynamic audiences

Trigger outbound at the right moment

Sync targeting to LinkedIn Ads

CRM receives:

Unified activity timeline

Updated contact records

Intent scores

Attribution data

Why Seconds Matter (Not Hours)

Why real-time matters

Chat needs context NOW (visitor is on-site)

Hot signals cool quickly

First-responder advantage is real

Batch processing = missed opportunities

One Account, One Contact, One Truth

Context Graph maintains a single record per entity:

Account deduplication

Domain normalization (www., subdomains)

Name matching (Acme Inc = Acme = ACME Corp)

Hierarchy handling (subsidiaries, parents)

Merge logic for acquisitions

Contact deduplication

Email as primary key

Name + company fuzzy matching

LinkedIn profile deduplication

Job change handling (same person, new company)

Result

No more "which record is right?"

Single timeline per account/contact

Clean data flows to CRM

Attribution connects to real entities

Bidirectional, Not Just Push

Context Graph syncs with your CRM both ways:

Pull from CRM

Existing contacts and accounts

Opportunity data

Custom fields and properties

Owner assignments

Push to CRM

New contacts discovered

Activity timeline

Intent scores

Engagement events

Sync design

Real-time (not scheduled)

Conflict resolution rules

Field mapping customization

Full history retained

What Context Graph Enables

Single source of truth for all GTM data

Real-time context for every action

Full attribution across all touchpoints

One Source of Truth

"We had 5 different 'versions' of the same account across tools. Context Graph unified everything — now sales, marketing, and ops all see the same data, updated in real-time."

— VP Revenue Operations, Enterprise SaaS