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Graph & AI Platform

We're changing the status quo of how you answer your questions.

The first single state, high-performance analytics across billions of connected entities and relationships — built on a governed, adaptive picture of your world. For humans and AI to investigate, explore, and act with confidence.

Trusted by top banks & government agencies worldwide

From Data to Knowledge

Turn scattered data into enterprise knowledge

DataWalk pulls records from every silo — CRM, transactions, watchlists, documents — and connects them into one governed graph. No copying, no re-modeling: your whole world, linked and ready to query.

CRM Transactions Watchlists Documents Open data
  • Auditability
  • Performance
  • Lineage
  • Monitoring
  • Access Control
How it Works

From scattered records to answers you can act on

  1. 01

    Match your entities with high confidence

    Scattered data points fall into place and connect into a living network — then duplicate records collapse into a single, resolved entity.

  2. 02

    Find new patterns and reveal hidden connections

    Hidden relationships surface across the graph, highlighted as new links you would never spot in siloed tables.

  3. 03

    Answer your deep questions with enormous speed

    Impulses race through the network as DataWalk traverses millions of connections in real time.

  4. 04

    Adapt fast to new questions and new data

    Fresh records stream in and connect on the fly — the graph reshapes itself so your picture stays current, without re-modeling.

Person 11.1M records

1 identity: Martin Schmidt

4 SOURCE RECORDS
  • M. Schmidt89
  • Martin Schmitt88
  • Schmidt, Martin79
  • SCHMIDT, Martin79
3 DATABASES
HIDDEN LINKS FOUND 24

new relationships across 6 entity types — invisible in siloed tables.

See the paths
200B records

multihop queries in 1.5 sec

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NEW

A new use case in under 24 hours

Check the case study
01 / 04
Agentic AI

Everyone offers a context layer. Few make it answer at scale.

AI Agent
Find people behind this suspicious transfer network
AUDIT TRAIL verifiable intermediate steps
  • People 11.1M → 2
  • Bank 20.4M → 6
  • Tx 27.3B → 782
  • Bank → 156
  • Tx → 60.6k
Ask a follow-up…
People Bank accounts Transactions Addresses Phones BTS stations 11.1M 2 20.4M 156 27.3B 782 8.7M 14.2M 62.5k querying..

An analyst asks five questions and stops. An agent asks five thousand — and each one walks eight hops deep before it knows what it was looking for.

DataWalk answers those questions on 100B+ records without a person re-tuning anything, and shows every step it took to get there.

A modeled ontology, not a guess
Someone maps the domain once. The agent walks that map and can't step off it — no invented joins, no query nobody sanctioned. The same question returns the same answer, today and in six months.
Links resolved at load, not per query
Connections are persisted in the knowledge graph up front, so a path nobody anticipated costs the same as one you planned for. Eight hops across 200B transactions — no pipeline built for that specific route.
Counts before the next hop, not after
Traversals can explode — one city node touches millions of people. Every hop returns its cardinality before the next runs, so a runaway path is caught mid-query, not in a timeout. The agent narrows, backtracks, or stops. Then the same trail reads as your audit record: 27.3B → 782 → 156 → 60.6k → 7.
Use Cases

Solution for your industry

Risk & Investigation Intelligence

  • Use context and AI to understand complex customer behavior
  • Analyze financial crime networks
  • Identify emerging risk patterns
  • Adapt investigations as threats evolve
AWARDS & RECOGNITION

Recognized as a disruptor in
the technology sector

G 4.9/5 on Gartner

Award-winning Graph + AI platform enabling faster, smarter investigations.

annual fraud losses prevented
$40M
accelerated results
10×
patents
11
RESOURCES

Whitepapers & research

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5 Reasons Why Disparate Data Blocks AI Investigation Agents
WHITEPAPER

5 Reasons Why Disparate Data Blocks AI Investigation Agents

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Seeing the Unseen: Why Good AI Begins With Connected Data
WHITEPAPER

Seeing the Unseen: Why Good AI Begins With Connected Data

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RESOURCES

The latest news, cases
and releases

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Relational databases — data model diagram
RESEARCH & INSIGHTS

Palantir Products and Competitors

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What is a context — data model diagram
ARTICLE

AMLD6: Comfort in Your AML Controls or 10% Turnover Fines?

Read more
FAQ

Everything You Need to Know

Find your answer

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Why use DataWalk?
DataWalk transforms siloed enterprise data into contextual intelligence — enabling investigators, analysts and operators to act with clarity and speed.
Who is DataWalk for?
Banks, government agencies, defense, intelligence, law enforcement, and insurance carriers running regulated operations at scale.
How to test DataWalk?
Book a demo with the team — proof-of-concept deployments typically run in 4-8 weeks on a pilot use case.
What are the benefits of an enterprise-class system?
Sovereign deployment, role-based access, audit trails, ontology versioning, and SLA-backed support.
What is Ask AI?
Composite AI assistant grounded in your organizational ontology — answers cite the knowledge graph, not the model.