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vs LinkedIn Sales Navigator
Go beyond LinkedIn data

LinkedIn shows profiles.
Fullinfo maps organizations.

LinkedIn Sales Navigator is useful for finding professionals and employee profiles. But it was never designed to model real-world organizations.

  • What companies actually do
  • Who leads them — structured by relevance
  • Where they operate globally
  • How they are structured across subsidiaries
  • How they connect to suppliers, customers, partners
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LinkedIn View
  • Duplicate company pages
  • Former employees attached
  • Regional directors above execs
  • Broad industry category
  • Disconnected subsidiaries
  • Scattered profiles
Fullinfo View
  • Unified organization profile
  • Structured exec hierarchy
  • Parent/subsidiary mapping
  • Operational locations
  • Granular industry layers
  • Supplier/customer graph
  • Source-backed intelligence
Core positioning

LinkedIn is people-first.
Fullinfo is company-first.

LinkedIn was designed as a professional networking platform. Its strength is identifying people — recruiters, employees, social relationships, personal networks.

But company intelligence is fundamentally different from profile intelligence. Many real-world organizations barely use LinkedIn, operate through fragmented subsidiaries, have duplicate pages, and exist entirely outside tech-centric ecosystems.

Fullinfo starts from the organization itself — analyzing company websites, leadership pages, operational descriptions, locations, customer references, partner signals, public sources, and domains. The result is a structured organizational layer, not a collection of disconnected profiles.

Company websites Leadership pages Public sources Domains & subsidiaries
Industry 2 ×
Any Location 1 ×
Keyword 3 ×
Company Employees Contacts HQ Industry
Tetra Pak
tetrapak.com
 10,001+ 44 🇸🇪 Sweden # Packaging Services +6
Körber Pharma
koerber-pharma.com
 10,001+ 70 🇩🇪 Germany # Packaging Services +6
Krones
krones.com
 10,001+ 56 🇩🇪 Germany # Packaging Services +5
Amcor
amcor.com
 1,001–5,000 86 🇨🇭 Switzerland # Packaging Services +6
SIG
sig.biz
 5,001–10,000 59 🇨🇭 Switzerland # Packaging Services +6
Entity resolution

LinkedIn profiles are fragmented.
Fullinfo builds unified entities.

LinkedIn was not designed to model real-world company structure. A single organization may appear across multiple company pages, local subsidiaries, regional offices, acquired brands, operating divisions, and country-specific domains.

This creates fragmented company intelligence that is difficult to work with at scale.

  • Maps parent companies, subsidiaries, and operating entities into one unified view
  • Connects shared domains, leadership overlap, locations, and legal entities
  • Models the organization behind the company page — not just the page itself
    • Entity Resolution — IBM Example Fullinfo
    Fragmented LinkedIn records
    IBM Netherlands IBM Consulting IBM Benelux IBM Research IBM Regional
    ↓ Signals connected · domains · leadership · locations
    Unified Organizational Graph
    IBM Corporation
    12 operating entities · 4 regions · verified from 23 public sources
    Leadership intelligence

    LinkedIn cannot reliably show who actually runs a company.

    At larger organizations, LinkedIn surfaces people based on keyword matching, profile activity, engagement, and network proximity — not actual executive hierarchy. The result is a misleading picture of who actually leads the organization.

    LinkedIn — People Results Profile-driven
    SR
    Sarah Reynolds
    Regional Sales Director, APAC
    Regional
    MK
    Marcus Klein
    VP Partnerships (former)
    Former
    JP
    James Park
    APAC Country Manager
    Regional
    ⚠ No clear executive hierarchy · former employees present · regional directors appearing above C-suite
    Fullinfo — Leadership View Org-structured
    Executive Leadership
    AW
    Andrea Wilson
    Chief Executive Officer
    CEO
    RB
    Robert Baxter
    Chief Financial Officer
    CFO
    Regional Leadership
    LC
    Lisa Chen
    MD, Europe
    Regional
    Board & Advisory (collapsed) · All source-linked
    Industry classification

    LinkedIn industry tags are too broad for serious market discovery.

    LinkedIn company classification is shallow. A company can choose only one primary industry category — self-declared, broad, inconsistent, and often marketing-oriented.

    Fullinfo supports up to 7 structured industry layers per organization, representing different operational aspects of the business.

    LinkedIn
    Manufacturing
    That tells you almost nothing operationally.
    Fullinfo Industry Layers
    Packaging Manufacturing Food Processing Industrial Equip. Medical Packaging Contract Mfg. Sterile Solutions
    Precision search example AI Search
    Your query
    Industry: Packaging + Manufacturing
    Keywords: bag-in-box · sterile · aseptic filling
    Match explanation
    Matched because: aseptic filling systems · sterile liquid packaging · pharmaceutical packaging workflows · food-grade bag-in-box production — not because of incidental mentions.
    Result precision High relevance
    Marketing noise filtered ✓ Yes
    Objective classification

    Self-declared data creates distorted results.

    Most professional databases rely heavily on self-declared information. Companies describe themselves the way they want to be perceived — not necessarily the way they actually operate.

    Fullinfo focuses on observable evidence: operational descriptions, products and services, infrastructure, certifications, customer references, and geographic footprint.

    Website claim
    "A sustainable future-ready mining innovator."
    Fullinfo operational interpretation
    Copper mining Mineral extraction Ore processing Open-pit operations ESG language detected
    Industry 2 ×
    Any Location 1 ×
    Keyword 4 ×
    Elos Medtech
    elosmedtech.com
    Contacts 69
    Locations 13
    Relationships
    Timeline
    🇸🇪 Timmersdala Office
    Bäckedalsvägen 5
    Timmersdala, SE-541 71
    Sweden
    info.skara@elosmedtech.com
    +46 511 25700
    🇺🇸 Force Milling Solutions
    8075 North Point Blvd
    Winston Salem, NC 27106
    United States
    🇺🇸 Memphis Office
    1800 North Shelby Oaks Dr
    Memphis, TN 38134
    United States
    dental.orders@elosmedtech.com
    🇨🇳 Tianjin China
    D5-3, Rong Cheng San Zhi Lu
    Xiqing Economic Dev. Area
    Tianjin, 300385
    info.tianjin@elosmedtech.com
    Locations 1 – 4 of 13  ·  Next →
    AI-powered search

    Search companies the way humans think.

    Most databases force users into rigid filters and static categories. Fullinfo supports natural market exploration — combining open-web data, normalized concepts, relationship signals, location intelligence, and AI-assisted search.

    → Horse riding resorts in Southern France
    → Industrial valve suppliers for offshore energy
    → Regional medical imaging distributors
    → Organic food manufacturers supplying retailers
    → Marine engineering firms in the Caribbean
    → Agritourism estates with equestrian facilities
    Relationship intelligence

    Relationship intelligence beyond company pages.

    Organizations do not exist in isolation. Fullinfo maps relationships between parent companies, subsidiaries, suppliers, distributors, customers, partners, operating locations, and related domains.

    A construction engineering company may connect to holding companies, fabrication facilities, regional operating entities, subcontractors, manufacturing plants, project partners, and customer references. LinkedIn typically surfaces whichever page employees use most. Fullinfo models the broader organizational structure.

    Explore Relationship Graph Supplier Discovery
    Parent HQ Subsidiary A Regional Office Supplier Distributor Manufacturing Plant Customer Ref. Partner Acme Industries GmbH
    Source transparency

    Explainable company intelligence.

    Many databases operate as black boxes. Fullinfo emphasizes traceability and observable evidence. Users can inspect source pages, extracted snippets, timestamps, relationship evidence, and confidence indicators.

    Users should understand why a company appears, how it was classified, where the information came from, and what evidence supports relationships. No guesswork.

    Leadership · CEO Verified 12 Mar 2026
    Found on company about page: "Our CEO Andrea Wilson joined in 2019 and leads our global expansion strategy across European and APAC markets."
    Confidence
    92%
    Industry classification Verified 8 Apr 2026
    Matched to aseptic filling from product page: "We provide sterile liquid packaging solutions for pharmaceutical and food-grade applications."
    Confidence
    87%
    Subsidiary relationship Verified 1 May 2026
    Shared domain registrant and overlapping legal entity registration with parent across 3 jurisdictions.
    Confidence
    78%
    100M+
    Organizations mapped from 300M+ domains analyzed monthly
    7
    Industry layers per organization — vs LinkedIn's single self-selected tag
    100%
    Source-backed intelligence with traceability on every data point
    0
    Reliance on LinkedIn data — built entirely from open-web intelligence
    Feature comparison

    Fullinfo vs LinkedIn Sales Navigator

    Capability
    Fullinfo
    LinkedIn Sales Nav.
    Company model
    Core model
    Organization graph
    People graph
    Unified company profiles
    ✓ Core feature
    ✗ Limited
    Parent / subsidiary mapping
    ✓ Core capability
    ✗ Weak
    Company relationship mapping
    ✓ Core direction
    ✗ Limited
    Leadership
    C-suite coverage
    Structured from multiple sources
    Incomplete
    Leadership ranking
    Organizationally structured
    Social / profile-driven
    Regional vs executive separation
    Structured by relevance
    Frequently mixed
    Board vs executive separation
    Structured separately
    ✗ Weak
    Industry & classification
    Industry model
    Up to 7 structured layers
    One self-selected category
    Industry granularity
    Operationally granular
    Broad
    Objective classification
    Observable evidence
    Self-declared
    Local-language normalization
    Normalized & translated
    ✗ Weak
    Search & discovery
    Keyword search precision
    Normalized operational search
    Often noisy
    Natural-language company search
    ✓ Core feature
    ✗ Limited
    Marketing-language filtering
    Operationally interpreted
    ✗ Weak
    Supplier / customer discovery
    Relationship-focused
    ✗ Weak
    Multi-location mapping
    ✓ Core capability
    ✗ Weak
    Data quality
    Source transparency
    Source-backed with timestamps
    ✗ Limited
    Best for
    Understanding organizations
    Finding people
    Industry 2 ×
    Any Location 1 ×
    Keyword 3 ×
    SIG
    🇨🇭 Neuhausen am Rheinfall · 5,001–10,000 Employees
    SIG provides leading sustainable packaging solutions for food and beverages, enhancing safety and affordability for global markets across dairy, juice, and plant-based products.
    Contacts 59
    Locations 1
    Relationships
    Timeline
    MK
    Mikko Keto
    Chief Executive Officer
    🇨🇭 Switzerland
    ✉ Reveal
    AE
    Ann-Kristin Erkens
    Chief Financial Officer
    🇨🇭 Switzerland
    ✉ Reveal
    FG
    Fabio Grazioli
    Chief Supply Chain Officer
    🇨🇭 Switzerland
    ✉ Reveal
    GS
    Gavin Steiner
    Chief Technology Officer
    🇨🇭 Vevey, Switzerland
    ✉ Reveal
    Industry tags 7
    # Administrative Services # Food and Beverages # Packaging Services # Health and Safety # Food Production # Global Trade
    Third generation data

    The next step in company intelligence.

    1

    Registry data

    The first generation came from official registries — structured but slow, out of date, and missing operational context.

    2

    Professional networks

    The second generation came from professional networks — more useful for sales, but flat, people-centric, and incomplete for organizations.

    3

    Fullinfo — Open-web intelligence

    Connecting multiple datasets, cross-checking every data point, and delivering richer organizational profiles that reflect the real economy.

    Ready to explore?

    Discover organizations the rest
    of the market overlooks.

    Map fragmented markets. Understand organizational structure. Discover hidden operators. Build better company intelligence from observable evidence.

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