Now accepting pilot users

Find your next
customer before
they find you

KGIntel transforms unstructured public documents into a Knowledge Graph that uses AI to predict which organisations need your B2B technology — ranked by likelihood, backed by evidence.

Request early access See how it works
10× faster prospecting
500+ sources monitored
GNN link prediction
The Problem

Finding customers for specialised tech is broken

Companies and researchers with niche B2B technology products spend weeks manually hunting for leads — and still miss most of them. The signals are out there. They just can't be seen without the right lens.

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Manual research is slow and incomplete
Browsing LinkedIn, Google Scholar, and procurement portals takes weeks — and still misses the most relevant signals buried in thousands of documents.
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Generic CRM tools don't understand your domain
ZoomInfo and Salesforce offer contact lists — but can't read a procurement tender, parse a research paper, or detect a demand signal before competitors do.
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No tool connects the dots across documents
The commercially valuable intelligence lies in cross-document relationships — an organisation that publishes simulation research AND issues training tenders AND hires simulation engineers. No existing tool sees this picture.
The Solution

From raw documents to ranked leads — automatically

KGIntel ingests public documents, builds a Knowledge Graph, runs Graph Neural Networks on it, and surfaces your best prospects with evidence-backed outreach rationales.

1
Multi-modal extraction
GPT-4o reads both text and visual elements — tables, charts, figures — from PDFs, extracting typed entities and relationships.
2
Knowledge Graph construction
Extracted triples populate a Neo4j graph. Every node and edge is anchored to its source document, date, and paragraph.
3
GNN link prediction
Graph Neural Networks predict the potential_customer_of relationship — ranking organisations by likelihood with full graph evidence.
4
Natural language answers
Ask questions in plain English. An LLM translates to Cypher, queries the graph, and returns sourced, traceable answers.
Why KGIntel is Different

Predictive intelligence,
not just retrieval

Every other tool tells you what exists. KGIntel predicts what will happen — ranking customers before they raise their hand.

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GNN-powered link prediction
Graph Neural Networks learn from the structural patterns of known customers and surface new organisations that match — before they ever express interest.
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Evidence-backed every time
Every lead recommendation comes with the exact public source that triggered it — the publication, tender, or job posting. Ready-made conversation starters.
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Sees text and visuals
Unlike text-only systems, KGIntel processes tables, charts, and figures directly — capturing structured data that flat text extraction misses entirely.
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Full provenance trail
Every node and edge in the Knowledge Graph is anchored to its source document, date, and paragraph. Fully auditable, hallucination-resistant.
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Domain-agnostic by design
Switch from driving simulators to ESG compliance or industrial robotics by updating the ontology alone. No code changes. Same pipeline.
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Plain English interface
No database expertise needed. Ask questions in plain English — the system translates to Neo4j Cypher and returns sourced natural language answers.
Market Opportunity

A $4B market growing at 11% per year

The global sales intelligence market is large and fast-growing — and the SME and research institution segment is the most underserved and fastest-expanding part of it.

$4.1B Global sales intelligence market 2025
11% Annual market growth rate (CAGR)
17.5% SME segment growth — fastest-growing
DACH Initial focus — Austria, Germany, Switzerland
Segment 1
B2B Technology Vendors and Research Teams
SMEs, university spin-offs, and research institutions commercialising specialised technology — driving simulators, industrial software, scientific instruments — who lack systematic business development capacity.
Segment 2
Business Development and Intelligence Teams
Professional BD and sales intelligence teams at technology companies in the DACH region who need domain-specific, evidence-based lead intelligence that ZoomInfo and LinkedIn Sales Navigator cannot provide.
Validation case
TU Graz — Driving Simulator Technology
KGIntel is being developed in formal research cooperation with the Institute of Automotive Engineering at TU Graz. The MVP is validated on driving simulator customer identification — a real domain expert, real data, real use case.
Early Access

Be the first to use KGIntel

Join the waitlist for early pilot access. We're onboarding a small number of technology vendors and research teams in the DACH region.