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Make Data Governance Enforceable

Automate control, enforce policies, and protect privacy at the source

Identity Control at the Source

Identity Control at the Source

Data is analyzed locally for cardinality, k-anonymity thresholds, and attribute distributions to detect re-identification risk.

Based on data type and observed patterns, governance policies are generated or applied, and transformations are executed iteratively until required thresholds are met.

A Distributed, Autonomous Network

           

Independent nodes operate within their own environments, coordinating across an autonomous network to match, transform, and exchange data without exposing underlying information.

Each node executes locally, using a shared protocol to align data across systems without revealing raw data or local keys.

Coordination is designed to prevent identity reconstruction during matching and exchange, even across multiple parties.

No single party has the information required to reconstruct identity or decrypt the data used for matching.

A Distributed, Autonomous Network

Operate Across Sources Without Exposure

Prepare data at the source and enforce governance by automatically applying transformations that reduce re-identification risk before it enters any workflow. 

Control

Prepare data at the source and enforce governance by automatically applying transformations that reduce re-identification risk before it enters any workflow. 

Match and align data across sources using coordinated cryptographic processes that prevent identity reconstruction during interaction, without sharing identifiers or exposing underlying data.

Link

Match and align data across sources using coordinated cryptographic processes that prevent identity reconstruction during interaction, without sharing identifiers or exposing underlying data.          

Deliver data in protected form, so it can be used across systems and environments without reintroducing identity or enabling re-identification risk. 

Deliver

Deliver data in protected form, so it can be used across systems and environments without reintroducing identity or enabling re-identification risk. 

 AI-Powered Governance, Built Into the Workflow 

AI-Powered Governance, Built Into the Workflow

KIE functions as a Model Context Protocol (MCP), enabling AI agents to generate governance policies without accessing raw data or identifiers.

AI agents operate on structured metadata and statistical signals, never interacting with underlying data.

Policies are generated based on observed data patterns and executed directly within workflows, ensuring governance is continuously enforced.

Our Unique Approach

A Distributed Network of Autonomous Nodes

A Distributed Network of Autonomous Nodes

The Karlsgate Identity Exchange (KIE) operates as a distributed network of nodes. Each node operates independently, within its own environment, coordinating across a network without sharing identifiers or exposing data in reusable form.

Patented Coordination Model (T-BLIMP)

Patented Coordination Model (T‑BLIMP)

A triple-blind protocol ensures that no single party has access to all components required to reconstruct identity.

Single-Use Cryptographic Representations

Single-Use Cryptographic Representations

Data is aligned using representations that are generated for a specific interaction and cannot be reused or reversed.

Identity Control and Governance at the Source

Identity Control and Governance at the Source

Data is prepared and governed before it enters any workflow, ensuring consistent enforcement across systems, teams, and environments

Resource Center

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Turning GDPR Compliance into Everyday Practice

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Data Breaches Double Each Year. Exposure Doesn’t Have To.

Data Breaches Double Each Year. Exposure Doesn’t Have To.

It’s time to rethink how data is shared.

As data breaches double each year, it's time to rethink how data is shared.
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Centralized Analytics Without the Centralized Risk

Centralized Analytics Without the Centralized Risk

Safely & compliantly use real-world, individual-level data, without risk or delay

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FAQs

Frequently Asked Questions

How long does it take to process a trade?

It depends on the size of the files and the number of match passes and attributes appended. In general, 1 million records can be processed in 11 seconds (simple match pass) whilst 100 million records with 10 match passes and 600+ attributes appended would be processed in less than 18 hours.

Does Karlsgate do fuzzy matching?

We define fuzzy matching as loose matching rules based on probabilities. Our matching is fully deterministic—you will always have clarity over a match versus a non-match. To ensure that all potential matches are found, our software performs “soft matching,” or matching on equivalent alternatives, for examples “1 MAIN ST. APT. 2” = “1 Main Street #2”. Soft matching does not need direct access to PII to work and automatically rectifies differences in standardization, whitespace, punctuation, abbreviations, and phonetically similar words.

How does Karlsgate optimize matching to ensure high-quality match rates?

While the ultimate matching is deterministic due to the nature of the cryptoidentities being matched, Karlsgate’s node software performs robust data normalization and standardization processes to align identifying data elements prior to creating the cryptoidentities, which boosts match rates without over-matching.

How many match passes can I use?

For a single trade, you can have up to 10 different match passes, cascading down.

Is the protection resistant to both classical and quantum computing attacks?

Yes, FIPS-compliant cryptographic algorithms are available for each exchange that range from traditional Elliptic-curve Diffie–Hellman key exchange (e.g., X25519) to post-quantum cryptography Module-lattice key encapsulation (e.g., ML-KEM-1024).