Privacy-Safe Synthetic Intelligence, plus Data Refinement & Investigations
High-fidelity datasets with validation and de-duplication — and a hands-on refinery that cleans, links, enriches, and investigates your data end-to-end.
Current value generation rate of our proprietary Data Refinery
The Real Problem: You Don’t Have the Data (Yet)
Teams stall because of data scarcity, compliance bottlenecks, stale snapshots, schema chaos, and biased samples. Zalingo solves each one with privacy-safe synthetic data that’s realistic, governed, and production-ready.
Cold Starts & Scarcity
No data to train or test? We generate domain-specific synthetic datasets that match your schemas and volumes.
cold startdata generationschema-alignedCompliance & Privacy
Skip risky real-user data. Our outputs are synthetic and support GDPR/HIPAA-aligned workflows.
GDPRHIPAAprivacy-safeQuality & Bias
We balance cohorts, stress rare events, and ship audits, drift metrics, and fairness options.
bias controldrift monitoringscorecardsIntegration Friction
Consistent keys, time semantics, and file formats; delivered to S3/Blob/SFTP with docs and samples.
Parquet/CSVtime-awareplug-in-readyWhy Zalingo Data Refinery Stands Apart
Beyond raw data: we deliver production-ready intelligence designed for model performance and time-to-value.
Realistic by Design
Relational integrity across tables, temporal realism (seasonality, burstiness), and cohort dynamics that mirror real markets and behaviors.
Cryptographic De-duplication
Every record is fingerprinted to minimize duplicates across drops—pay only for unique intelligence.
Actionable Signals
Built-in scoring (intent, engagement, value estimates) and correlation matrices for immediate use in targeting, fraud, and forecasting.
Packaging for Production
Consistent schemas, sample slices, documentation, and versioned releases—marketplace-ready deliverables without the marketplace lock-in.
Privacy-Safe by Design
Outputs are synthetic and support GDPR/HIPAA-aligned workflows. No real PII/PHI in delivered datasets.
Flexible Delivery
Parquet/CSV/JSON Lines to your preferred secure destination, with optional daily/weekly/monthly refreshes.
Company Data Refinement — Clean, Link, Enrich, Govern
We turn messy internal data into trustworthy, analytics-ready assets. Keep your systems of record intact while we build a clean, versioned, and explainable layer for AI and BI.
Entity Resolution & De-Duplication
Fingerprinting + fuzzy matching (names, addresses, phones, emails, device IDs) to merge duplicates across CRMs, ERPs, DWHs. Golden records with lineage.
- Cross-source linking (B2C & B2B)
- Survivorship rules & confidence scoring
- Audit trails and rollback snapshots
Data Quality & MDM
Validation rules, referential checks, and stewardship workflows. Conform to canonical schemas without disrupting production systems.
- Standardization (names, dates, addresses)
- Business rule enforcement & KPIs
- Master/Reference data curation
Enrichment & Feature Engineering
Augment with external signals (licensed, public) and generate features for churn, CLV, fraud, and personalization. Ship as Feature Store tables.
- Behavioral features & propensity scores
- Household/Account roll-ups
- Time-aware aggregates & cohorts
Governance & Compliance
Data maps, catalogs, lineage, and DPIA support. We work privacy-first and can keep PII in your VPC; our deliverables can exclude or tokenize identifiers.
- Access controls & logging
- Schema and contract tests
- Lifecycle policies & retention
Investigations & Forensic Analytics
We conduct full investigations using data: OSINT + internal telemetry + graph analysis to surface entities, timelines, relationships, and anomalies.
Due Diligence & KYB/KYC (Non-PII Deliverables)
Corporate linkages, beneficial ownership inference, adverse media clustering, geographic exposure, and sanctions adjacency analysis.
KYB/KYCPEP/AMLadverse mediaFraud & AML Patterns
Temporal and network anomalies: bursty activity, smurfing-like sequences, funnel accounts, and device/identity reuse across systems.
network graphsdevice reusesequence outliersTimeline Reconstruction
Unify logs, emails, tickets, and financial traces to create defensible event timelines with confidence scores and source provenance.
provenancechain-of-custodyforensic triageOSINT & Local Language Coverage
South African languages supported for search/normalization (11 official languages), plus cross-border corpora for Pan-African work.
multilingualZA focusPan-AfricanProducts & Domain Packs
Representative bundles; all packs can be customized to match your downstream schemas.
Behavioral Intelligence Suite
User & session tables (B2C) with event streams; B2B account activity; conversion/churn/LTV scaffolds; propensity & intent scores.
Market & Trend Suite
Multi-asset time-series with seasonality & momentum; derived technical factors; behavior-to-trend correlation matrices.
E-commerce & Retail Pack
Product interactions, baskets, orders, returns, CLV features; RFM segments and persona archetypes.
Financial Services Pack
Risk, fraud and credit-like behavior scaffolds; transaction sequences & merchant/category features; anomaly challenge sets.
Healthcare R&D Pack
Synthetic patient journeys for modeling (non-clinical); age-aware scaffolds; intervention timelines.
AI/ML Platform Pack
Training datasets, feature libraries, and validation sets to populate lower environments.
How Our Algorithm Is Trained
We gather structures and signals, not identities; then pre-train self-supervised models to emulate distributions safely.
1) AI-Assisted Data Gathering
Public, licensed, and client schema/constraints. Extract non-identifying statistics, distributions, and relationships.
- Schema discovery & ontology mapping
- Entity/relationship extraction
- Time semantics
2) Foundation Pre-Training
Representation learning for tables, time series, and events. We capture constraints and business rules.
- Tabular & temporal embeddings
- Causal dependencies
- Schema-conditioned learning
3) Generative Synthesis with Guards
Constraint engine enforces keys/ranges/joins; privacy filters reject near-matches; fairness knobs balance cohorts.
- Programmable validators
- k-similarity checks
- Bias controls
4) Human-in-the-Loop & Scoring
Use-case scorecards (lift, precision/recall). Ship built-in intent/engagement/value signals.
- Utility evaluation
- Quality gates
- Cryptographic de-duplication
{
"training_config": {
"schema":"customer-provided",
"privacy":{"k_sim":5,"max_match":0.10},
"constraints":["keys","ranges","joins","temporal"],
"fairness":{"parity_checks":true,"cohort_balancing":"opt-in"},
"scoring":["intent","engagement","value_estimate"],
"dedup":{"fingerprint":"sha256"}
}
}
Who Needs Synthetic Data
Startups with no data, enterprises blocked by privacy, QA for lower envs, risk teams chasing rare events, retail personalization, and non-clinical health analytics.
Quality, Governance & Security
Validation, observability, and delivery practices engineered for enterprise adoption.
Validation Pipeline
Schema conformance, distribution checks, cross-table integrity, temporal audits, drift monitoring.
Bias & Fairness
Configurable cohort distributions with optional parity checks and adverse-impact probes.
Security & Delivery
Encrypted at rest/in transit, least-privilege, signed artifacts. Parquet, CSV, JSONL to SFTP or your object storage.
Observability
Release scorecards, dedupe reports, drift metrics, and freshness/complete-ness SLIs.
Case Studies & Outcomes
What clients achieved after running the refinery and, when needed, investigations.
| Scenario | Before | After Zalingo |
|---|---|---|
| Retail CRM Unification | 7% duplicate rate; broken journeys; low personalization | ✅ 0.9% dupes; 18% uplift in CLV model lift; faster campaign iteration |
| FinServ Fraud Spike | Unexplained chargeback clusters | ✅ Device reuse graph + sequence outliers → 32% reduction in false negatives |
| Vendor Due Diligence | Manual checks; missed media signals | ✅ Automated adverse media + ownership links; decision in 48h with audit pack |
Premium Data Refinery
Enterprise-grade behavioral intelligence datasets with marketplace-ready output—delivered directly to you.
Real-time valuation of generated data assets.
High-quality behavioral and trend records.
Multi-stage validation and enrichment process.
Premium Data Packages
Specialized datasets for industry-specific applications.
Financial Services
Algorithmic trading signals, risk modeling, fraud detection.
Products: High-Intent Profiles, Trend Correlations, AI-Ready Training Sets.
Healthcare & Pharma
Treatment adherence prediction; market expansion analysis (non-clinical).
Products: Behavioral Intelligence, Predictive Analytics, Compliance Signals.
E-commerce & Retail
CLV prediction, churn reduction, personalization at scale.
Products: Purchase Intent Scores, Behavioral Clusters, Trend Analysis.
AI/ML Development
Model training, feature engineering, synthetic event streams.
Products: Training Datasets, Feature Libraries, Validation Sets.
Refinery Operations Log
Real-time monitoring of data generation processes.
Engagement Models
Pick the path that fits your evaluation and deployment timeline.
Starter Evaluation (2–4 weeks)
Sample bundle (10–50 MB), schema docs, benchmarks notebook; optional guided workshop.
Subscription Feeds
Fixed schema with scheduled refresh; SLIs for freshness and completeness.
Custom Programs
Co-designed features/distributions, co-developed scoring, integration support.
Download the Client Whitepaper
Deep-dive into architecture, quality controls, product catalog, and engagement options.
FAQ: Synthetic Data, Refinement & Compliance
Short answers to the most searched questions teams ask when evaluating providers.
Do you use real user data?
No. We learn from structures and patterns and generate synthetic records. Deliverables contain no real PII/PHI.
Can you refine our messy datasets?
Yes. We de-duplicate, resolve entities, standardize, enrich, and govern—shipped as versioned tables with lineage.
Do you run investigations for us?
Yes. We combine OSINT with your internal telemetry to map entities, timelines, and risks, with defensible reporting.
How is quality measured?
Distributional tests, cross-table integrity checks, temporal audits, model lift, fairness probes, and human sign-off.
Compliance & Legal Notes
Outputs are synthetic and intended for research, development, analytics, and testing. No real PII/PHI in delivered datasets. Customers remain responsible for end-use compliance. Healthcare pack is not clinical data or medical advice.
Perfect For AI & ML
Training recommendation engines, risk & fraud models, forecasting, and scenario testing.
Market Intelligence
Trend analysis, competitive intelligence, and A/B scenario stress-tests without production exposure.
Data Engineering
Populate lower environments with production-like volumes and patterns to accelerate delivery.
Enterprise Analytics
Business intelligence, customer insights, and strategic decision support.