CogniCrest — Privacy Engineering for Regulated Data

Name	Phone	National ID	Balance
Jordan BlakeCUST_8841X	(415) 552-0146(415) 55•-••46	4471-2290-8834••••-••••-8834	$18,430$10K–20K band
Priya ShahCUST_2207Q	(206) 883-0071(206) 88•-••71	6612-4409-1187••••-••••-1187	$4,290$0–5K band
Marcus IlićCUST_5563M	(312) 470-9982(312) 47•-••82	2298-7701-3345••••-••••-3345	$67,105$50K–100K band

Why now

Data protection law is tightening across every major market. Most data estates can't yet prove they comply.

120+

Jurisdictions with active data protection law

Typical maximum penalty, global revenue

72h

Common breach notification window

Architecture

One pipeline, five layers, every field accounted for.

Data enters as-is from your existing stores and leaves anonymized, policy-checked, and logged — without a parallel system for your engineers to maintain.

01 / 05

Discovery & Classification

Scans structured and unstructured stores to locate personal and sensitive fields automatically, no manual data-mapping spreadsheet required.

02 / 05

Anonymization Engine

Applies tokenization, k-anonymity, and field-level masking based on data sensitivity — tuned per column, not blanket-applied across the table.

03 / 05

Policy Engine

Core differentiator

Regulatory clauses are mapped directly to enforcement rules, so a policy change in the law becomes a configuration update, not a re-architecture.

04 / 05

Consent & Audit Layer

Tracks consent lineage per data subject and produces audit-ready logs your compliance team can hand to any regulator without translation.

05 / 05

Reporting Dashboard

Live visibility into anonymization coverage, residual re-identification risk, and open policy gaps across every connected data store.

"Anonymization built on lab-grade privacy math, not a find-and-replace on your PII columns."

— Engineering principle, CogniCrest platform

k ≥ 5

Minimum anonymity set size enforced by default across every table field

API-first

Every layer callable independently, so you adopt the pipeline stage by stage

Hybrid

Deploy in your VPC, ours, or split across both — data residency stays your call

API-first

Every pipeline stage is a callable endpoint, built to sit inside your existing data flow.

Hybrid deployment

Run inside your VPC, ours, or a split of both depending on residency needs.

Regulation-mapped policy

Rules trace back to specific statutory clauses, kept current as regulations evolve.

Audit-ready logs

Consent lineage and anonymization events exported in regulator-legible form.

Built for

Where personal data carries the most regulatory weight.

We're onboarding a first wave of design partners in the three sectors where regulatory exposure is highest and data volume is largest.

Fintech

Lending, payments & wealth platforms

KYC records, transaction histories, and credit data anonymized without breaking fraud models or regulatory reporting.

Bureau data pipelines
Transaction monitoring feeds
Customer analytics warehouses

Healthtech

Providers & diagnostics

Patient records and lab data de-identified to research-grade standards while staying usable for clinical analytics.

EHR exports
Diagnostic imaging metadata
Clinical trial datasets

Insurtech

Underwriting, claims & policy platforms

Policyholder records and claims data anonymized without degrading the actuarial and fraud-detection models built on top of them.

Claims processing pipelines
Underwriting risk datasets
Policyholder record stores

Get your data pipeline compliance-ready before an audit does it for you.

Tell us about your data estate and where you are on compliance. We'll follow up with a walkthrough scoped to your stack.