The Science Behind Warm Connections

WarmConnect analyzes 56+ touchpoint types across 8 dimensions to find the warmest path to anyone in the world.

We're continuously expanding our analysis to deliver even greater connection accuracy.

Deep
Connection Analysis
56+
Touchpoint Types
& Growing Daily
87%
Success Rate
Warm
Connections Only

Building the World's Most Sophisticated Connection Graph

While others show you if people are connected, WarmConnect understands the strength, context, and warmth of every relationship. Our AI-driven platform doesn't just find connectionsβ€”it predicts which introductions will actually succeed.

By analyzing professional histories, educational backgrounds, board positions, investment relationships, cultural affinities, and dozens of other factors, we've built the world's most comprehensive understanding of how people are truly connected.

🎯

Beyond Binary Connections

We score relationships from 0-100 based on multiple dimensions, not just "connected" or "not connected"

⏰

Temporal Intelligence

Relationships decay over time. We track recency and duration to ensure introductions happen at the right moment

πŸ”

Hidden Networks

We uncover non-obvious connections through sports teams, military service, shared adversity, and cultural bonds

Our 56+ Touchpoint Analysis Framework (Continuously Expanding)

Every relationship is unique. Our proprietary algorithms analyze connections across eight major dimensions, with each dimension containing multiple touchpoint types that contribute to the overall connection strength.

πŸš€ Always Improving: We're actively expanding our touchpoint analysis beyond the current 56+ types. Our research team continuously identifies new relationship indicators and patterns to provide you with even more accurate and valuable connection insights.

Professional Touchpoints (11 types)

Direct Working Relationships

  • β€’ Manager/Direct Report: Tracks reporting relationships with temporal decay
  • β€’ Peer Executives: C-suite and VP-level lateral relationships
  • β€’ Cross-functional Projects: Collaborated on specific initiatives
  • β€’ Same Department: Worked in same functional area

Extended Professional Networks

  • β€’ Same Company: Overlapping employment with location analysis
  • β€’ Media Production Teams: Film, TV, digital content collaborations
  • β€’ Writers Rooms: Creative collaboration environments
  • β€’ Collaborative Team Projects: Product launches, research teams

Temporal Analysis: Each professional relationship includes "overlap_type" conditions that adjust scores based on whether people worked together concurrently or years apart

Educational Touchpoints (7 types)

Academic Connections

  • β€’ Same University: Alumni networks with temporal overlap
  • β€’ Overlapping Years: Actual campus overlap vs. different eras
  • β€’ Same Degree Program: MBA, engineering, medical school bonds
  • β€’ Elite MBA Programs: Harvard, Stanford, Wharton special scoring

Campus Life Bonds

  • β€’ Greek Life: Fraternity/sorority connections across chapters
  • β€’ University Leadership: Student government, club officers
  • β€’ School Spirit Bonds: Mascot affiliations (Ducks, Aggies, etc.)

Board & Investment Touchpoints (8 types)

Board Relationships

  • β€’ Corporate Boards: Directors serving together
  • β€’ Board Committees: Audit, compensation, governance
  • β€’ Advisory Boards: Strategic advisors
  • β€’ Nonprofit Boards: Charitable organizations

Investment Networks

  • β€’ Co-investors: Same round timing analysis
  • β€’ Investor-Founder: Direct investment relationships
  • β€’ LP/GP Relationships: Fund participation
  • β€’ Syndicate Partners: Deal collaboration frequency

Social & Cultural Touchpoints (17 types)

Sports & Competition

  • β€’ Sports teammates
  • β€’ Championship winners
  • β€’ Coach-player bonds
  • β€’ Olympic teammates
  • β€’ Sailing crews

Military & Service

  • β€’ Military service
  • β€’ Combat veterans
  • β€’ Officer-enlisted
  • β€’ Academy classmates
  • β€’ Same unit bonds

Political & Social

  • β€’ Campaign staff
  • β€’ Political donors
  • β€’ PAC boards
  • β€’ Convention delegates
  • β€’ Social clubs
  • β€’ Cultural organizations

Geographic (6 types)

  • β€’ Same hometown
  • β€’ Expat communities
  • β€’ Diaspora networks
  • β€’ Language abroad
  • β€’ Cultural organizations
  • β€’ Hometown + industry

Events (4 types)

  • β€’ Conference speakers
  • β€’ Panel participants
  • β€’ Event organizers
  • β€’ Exclusive gatherings

Strength Indicators (3 types)

  • β€’ Mutual connections
  • β€’ Endorsements given
  • β€’ Introduction success

AI-Powered Data Collection & Analysis

Our proprietary AI systems continuously gather and analyze relationship data from hundreds of sources, uncovering connections that others miss:

Data Sources We Analyze

These are just some of the hundreds of sources we continuously monitor:

  • βœ“ Professional Networks: LinkedIn, company directories, org charts
  • βœ“ Company Websites: Executive bios, team pages, about sections
  • βœ“ Press Releases: Company announcements, executive appointments
  • βœ“ SEC Databases: EDGAR filings, proxy statements, insider trading
  • βœ“ Government Registrations: State and federal company registrations
  • βœ“ News & Media: Articles, interviews, podcast appearances
  • βœ“ Event Data: Conference speakers, attendee lists
  • βœ“ Financial Records: Board appointments, investments
  • βœ“ Academic Records: Alumni databases, research papers
  • βœ“ Sports & Military: Team rosters, service records
  • βœ“ Patent Filings: Co-inventors and research teams
  • βœ“ Cultural Data: Philanthropic activities, social clubs

AI Extraction Capabilities

  • ⚑ Entity Recognition: Identifies people, companies, and relationships in unstructured text
  • ⚑ Temporal Analysis: Extracts dates and durations to understand overlap
  • ⚑ Context Understanding: Determines relationship type and strength
  • ⚑ Graph Construction: Builds multi-dimensional connection networks
  • ⚑ Anomaly Detection: Identifies unusual but strong connections
  • ⚑ Quality Scoring: Validates and weights data sources
  • ⚑ Privacy Protection: Anonymizes and aggregates sensitive data

Real-Time Processing Pipeline

Data Ingestion β†’ Entity Extraction β†’ Relationship Mapping β†’ Temporal Analysis β†’ Score Calculation β†’ Graph Update

Temporal Intelligence: Relationships Change Over Time

One of our key innovations is understanding that relationships are dynamic. Two people who worked closely together five years ago have a different connection strength than current colleagues. Our temporal analysis ensures you're leveraging relationships at their peak effectiveness.

How We Track Relationship Decay

Current Relationships (Score: 100%)

Active colleagues, current board members, ongoing projects

Recent Past (1-2 years) (Score: 75%)

Former direct colleagues, recent shared experiences

Moderate Past (3-5 years) (Score: 50%)

Past colleagues, older shared experiences

Distant Past (5+ years) (Score: 25%)

Historical connections requiring reactivation

Overlap Analysis Examples

Board Service Together

  • β€’ Concurrent service: 4.0 score
  • β€’ 1 year gap: 3.0 score
  • β€’ 2-3 years gap: 2.0 score
  • β€’ 5+ years gap: 1.0 score

University Attendance

  • β€’ Same years on campus: 3.0 score
  • β€’ 1 year overlap: 2.5 score
  • β€’ 2 years apart: 2.0 score
  • β€’ 10+ years apart: 0.5 score

Manager-Report Relationship

  • β€’ Currently managing: 5.5 score
  • β€’ Past year: 4.5 score
  • β€’ 2-3 years ago: 3.5 score
  • β€’ 5+ years ago: 2.5 score

Finding the Warmest Path, Not Just the Shortest

Our path-finding algorithms optimize for introduction success, not just degrees of separation. We analyze extensive networks of potential paths to find the ones most likely to result in meaningful connections.

Path Scoring Example: Reaching a Fortune 500 CEO

πŸ† Warmest Path (Score: 92/100)

High Success Rate

You β†’ Former Colleague (current board member) β†’ Fellow Board Member β†’ Target CEO

βœ“ Step 1: Strong professional bond + current relationship
βœ“ Step 2: Active board collaboration (quarterly meetings)
βœ“ Step 3: Peer CEOs in complementary industries

⚑ Shortest Path (Score: 41/100)

23% Success Rate

You β†’ LinkedIn Connection β†’ Target CEO

⚠️ Weak first-degree connection (met once at conference)
⚠️ Large seniority gap and different industries
❌ Likely to be ignored or delegated to assistant

Path Quality Factors

  • β€’ Strength of each connection
  • β€’ Recency of interactions
  • β€’ Mutual benefit potential
  • β€’ Seniority alignment
  • β€’ Geographic feasibility
  • β€’ Industry relevance

Introduction Context

  • β€’ Shared interests identified
  • β€’ Mutual connections highlighted
  • β€’ Timing recommendations
  • β€’ Conversation starters
  • β€’ Follow-up suggestions

Success Predictors

  • β€’ Introducer's track record
  • β€’ Recipient's openness
  • β€’ Request specificity
  • β€’ Value proposition clarity
  • β€’ Cultural alignment

Continuous Learning & Improvement

Our algorithms get smarter with every introduction. By tracking outcomes and gathering feedback, we continuously refine our scoring models to improve success rates.

Machine Learning Models

  • 🧠 Graph Neural Networks: Analyze network structures to find optimal paths
  • 🎯 XGBoost Classifiers: Predict introduction success probability
  • πŸ“Š Time Series Analysis: Model relationship decay patterns
  • πŸ”€ NLP Models: Extract context from unstructured data
  • πŸ” Anomaly Detection: Identify unusual but valuable connections

Feedback Loop Integration

  • πŸ“ˆ Introduction Outcomes: Track meeting acceptance, follow-ups, deals closed
  • ⭐ User Ratings: Gather feedback on connection quality
  • πŸ”„ A/B Testing: Continuously test scoring improvements
  • πŸ“Š Cohort Analysis: Understand patterns across user segments
  • πŸŽ“ Model Retraining: Weekly updates based on new data

Why WarmConnect Finds Connections Others Miss

πŸ”—

LinkedIn

Shows who's connected

Binary connections only

πŸ“§

Sales Tools

Provide contact info

No relationship context

πŸš€

WarmConnect

Understands relationships

56+ touchpoints analyzed

Connections We Find That Others Miss

  • βœ“ Championship teammates from 20 years ago who still help each other
  • βœ“ Military unit members who transition to business together
  • βœ“ Board members who served on committees together
  • βœ“ Diaspora networks in specific industries
  • βœ“ Co-investors who backed the same companies
  • βœ“ Crisis management teams with unbreakable bonds
  • βœ“ Political campaign staff who launch businesses together
  • βœ“ Entertainment industry alumni in tech

Experience the Power of Warm Connections

Stop sending cold emails. Start leveraging the world's most sophisticated connection intelligence platform.