HumanGraph is designed for environments where data sovereignty, regulatory exposure, and integration complexity are real constraints. It works from pseudonymised inputs, supports on-premise or hosted deployment, and returns outputs that fit inside systems you already operate.
How Pilots WorkMost environments do not need more raw data complexity. They need early intelligence that can be deployed responsibly, using the data already available in operational systems, without forcing major architectural change.
HumanGraph is designed around that principle. It generates early signals from minimal, pseudonymised roll-up data and returns those signals in formats that teams can review, test, and activate inside the systems they already use.
These are the concrete controls in place today — not aspirational claims.
All data transmitted to HumanGraph infrastructure uses TLS 1.2+. Data stored on our servers is encrypted at rest using AES-256.
Cloud-hosted deployments run on AWS (EU region by default). On-premise deployments operate entirely within your own infrastructure — no data leaves your environment.
Role-based access controls limit who can view, export, or modify data and model outputs. Access logs are maintained for all data operations.
Input data is retained only for the duration required to generate predictions. We do not build persistent player profiles beyond the operational window defined with the operator.
HumanGraph is designed for lightweight deployment in real environments. Integration does not require major system changes, complex data pipelines, or long implementation cycles. teams can start with limited scope and expand gradually as value is proven.
Use secure REST API integration for real-time ingestion or aggregated operational data exchange.
Start with simple file-based uploads for pilots, evaluations, or staged rollout.
Full deployment within your own infrastructure. No data leaves your environment. Supported for operators in MGA, UKGC, and other regulated jurisdictions.
HumanGraph is built to work with a limited set of transactional and behavioural signals already available in systems. It does not depend on a perfect historical data environment to begin producing useful early intelligence.
That makes it well suited to environments where data access is constrained, infrastructure is uneven, or privacy requirements are high.
HumanGraph ingests pseudonymised, time-stamped operational activity. It does not require raw player identifiers, full event streams, or direct database access. Outputs are returned in formats that integrate with your existing tools — not stored or processed beyond the agreed operational window.
A HumanGraph pilot is a short, structured deployment designed to validate early player intelligence in your environment quickly, with minimal integration effort and no long-term commitment. Teams can begin with one focused product, evaluate signal quality against observed outcomes, and expand only once operational fit is clear. All pilot data handling is governed by a signed DPA before any integration begins.
The pilot approach is especially useful where strict privacy constraints, weak historical availability, or inconsistent data infrastructure would otherwise slow adoption. HumanGraph is designed to degrade gracefully when data is limited and sharpen as fresh operational evidence arrives.
HumanGraph follows a privacy-safe operating model aligned with data minimisation and privacy-by-design principles. Its approach is intentionally practical: pseudonymised inputs, limited required data scope, modular deployment, and controlled activation inside existing systems. This helps teams move faster without treating trust as an afterthought.
We believe transparency about our compliance posture is more useful than empty badge displays.
We will update this section as milestones are reached. Last reviewed: April 2026.
Test signal quality and operational fit in a controlled environment before broader deployment. Use practical inputs, validate real outcomes, and expand with confidence.
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