Synthetic Data.
Custom ML Models.
Any Industry.
We build the data and AI models your team needs — without touching real records. FinTech, MedTech, enterprise. Production-ready in 3–6 weeks.
Trusted by
Coloplast
Norwood Point Ventures
Synthetic Datasets
Statistically faithful data at any scale — no real records ever used. We preserve distributions, correlations, and edge cases so your models train on data that behaves like the real thing, without exposing anyone’s private information.
Custom ML Models
Models trained on synthetic data, deployed to your infrastructure. From fraud detection and credit scoring to medical diagnostics — every model ships with full explainability reports, benchmarks, and no vendor lock-in.
Validation & Advisory
Model performance testing, dataset integrity checks, and regulatory alignment across GDPR, HIPAA, SR 11-7, and the EU AI Act. We integrate into your existing pipelines so your compliance teams can sign off with confidence.
Northhaven
Hub.
Deploy a complete, enterprise-grade AI infrastructure in minutes. Go beyond just synthetic data — instantly spin up custom predictive ML models tailored to your sector. No code required, zero PII exposure, and full compliance proof included.
1M+
Records generated per run
13+
Supported industry sectors
Zero
Real data exposure risk
API
Direct system integration
COMING SOON
Platform Features
Beta
Token-Based Generation
Purchase a token package where 1 token equals 1 generated record. Unused tokens roll over indefinitely.
Industry Templates
Choose from predefined sector templates or define a custom data schema that matches your exact needs.
High-Fidelity Synthesis
Our proprietary engines produce statistically perfect data, preserving complex relationships and edge cases.
Seamless Export
Download as CSV, JSON, or Parquet. Each export includes an automated PDF Compliance Report.
Production-Ready
Live Systems.
Already Deployed.
Credit Risk Scoring &
Explainable AI Engine
Upload a bank statement CSV. Get a full credit assessment in under 3 minutes — no code required. XGBoost scoring, transparent PDF reports, configurable risk policy.
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SCORING ENGINE
LIVE
782
SCORE
Revenue Stability
Debt Service Ratio
Market Exposure
Payment History
APPROVE — LOW RISK
Private Debt Exit Risk
Simulator
Simulates exit and refinancing probability for illiquid corporate debt — 3–5 years forward, under macro stress. Built for mid-cap and institutional complexity.
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EXIT SIMULATOR
RUNNING
Y1Y2Y3Y4Y5
Exit Prob. Y3
61.4%
Refi Prob. Y5
82.1%
Stress Case
34.8%
MODERATE CONFIDENCE
Frequently
Asked
Questions
Straight answers on synthetic data, security, and how we work — for any team building with AI.
How realistic is your synthetic data compared to real data?
Built using correlation matrices, behavioural logic, and domain-specific constraints. Predictive accuracy typically matches 90–95% of real data performance.
Can synthetic data replace real data for ML training?
In many cases — yes. Ideal for model development, stress testing, and edge case simulation. Faster iteration, zero regulatory friction.
How is privacy guaranteed?
We never access or transform real client databases. Every dataset is generated from statistical patterns — no record can be traced to a real person, patient, or user. Full GDPR and HIPAA compatibility by design.
Which industries do you work with?
FinTech, MedTech, energy, AI startups, enterprise SaaS, insurance, logistics, and beyond. Our core capability applies to any domain that needs to train AI without exposing sensitive records.
Do you operate under NDAs?
Always. Every engagement starts with a mutual NDA from day one. We adapt to each organisation’s internal compliance and data handling policies.
Get in Touch
Ready to Build
Something Real?
Whether you’re a FinTech scaling risk models, a MedTech team blocked by data privacy, or an AI startup that needs clean training data — let’s talk.