Statistical fidelity, privacy budgets, and shareable datasets—unlocking ML without shipping raw PII.
Train on data you can share—synthetic rows with privacy metrics that reviewers understand
We implement tabular and time-series generators with constraint solvers so marginals and seasonality survive synthesis. Differential privacy hooks expose epsilon budgets per release; downstream teams see utility vs privacy trade-offs before generating gigabytes. Access workflows issue time-bound synthetic extracts—watermarking optional—so partners test integrations without VPNs into production databases.
01 // THE MANDATE
Statistical fidelity, privacy budgets, and shareable datasets—unlocking ML without shipping raw PII.
We implement tabular and time-series generators with constraint solvers so marginals and seasonality survive synthesis. Differential privacy hooks expose epsilon budgets per release; downstream teams see utility vs privacy trade-offs before generating gigabytes.
Access workflows issue time-bound synthetic extracts—watermarking optional—so partners test integrations without VPNs into production databases.
02 // ENGINEERING
Development process
Structured phases—from discovery to launch—with clear ownership and handoff points.
Data sensitivity review (weeks 1–4)
MVP (weeks 4–14)
Validation (weeks 12–18)
Scale (weeks 16–24)
Operate (ongoing)
03 // CAPABILITIES
Core Capability Matrix
The building blocks of your solution
Profiling
schema; distributions; rare category handling.
Generation
GAN/CTGAN-class; autoregressive optional.
Validation
TSTR tests; disclosure risk metrics.
Privacy
DP noise; k-anonymity checks optional.
Time series
AR patterns; entity continuity optional.
Bias
fairness checks on synthetic labels optional.
Export
Parquet; Snowflake/BQ load optional.
Lineage
seed; version; reproducibility.
API
batch jobs; quotas.
Governance
approvals; audit log.
04 // DELIVERY LIFECYCLE
The strategic roadmap
Milestones and checkpoints—each phase has a clear outcome before the next begins.
Weeks 1–4: DPIA and legal sign-off.
Weeks 5–10: First synthetic dataset delivered.
Weeks 11–18: Downstream model validation.
Weeks 19–24: Partner sharing workflows.
Ongoing: New tables; privacy regulator updates.
05 // PRODUCT SCOPING
Choosing your path
Two engagement models—start lean and iterate, or commit to a full platform build from day one.
MVP
Speed & essentialism
Full product
Enterprise maturity
06 // PARTNERSHIP
Why work together
A single accountable partner across strategy, build, and go-live—not a revolving door of vendors.
End-to-end ownership: discovery, architecture, implementation, and launch—with clear communication and production-grade engineering.
- Discovery & alignment
- Systems that scale
- Implementation depth
- Clear comms
07 // CLARITY
Frequently asked
Benchmarks on downstream tasks; we document where synthesis fails and keep human review gates.
08 // MORE SOLUTIONS
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