AI/ML-powered discovery
Continuous scans of SaaS applications, internal systems, data stores, code, and third-party technology updates classify data against regulatory and business definitions.
Always-on data discovery and classification for every system, app, and database
Ketch Data Discovery and Classification finds and labels the personal and sensitive data inside your SaaS applications, internal systems, code, and third-party platforms, then feeds those classifications into every part of your privacy program that regulators expect to see.
Classification that runs
inside your environment
Vendor integrations
Direct connections to enterprise systems and third-party platforms discover and classify personal data, with click-based setup and no coding required.
Data store visibility
Connections to databases, data warehouses, and data platforms show where personal and sensitive data lives, down to the individual field.
In-environment classification
Classification runs inside your own environment, labeling databases and warehouses like Snowflake, Postgres, and S3 without exposing or extracting raw data.
Summer 2026 Leader
Rated 4.6/5 on G2
165+ verified reviews from privacy, security, and marketing teams.
Read Customer StoriesWe went from project start to go-live in three weeks. Few vendors match Ketch on time-to-value
67.2B
Consent transactions per month
3,500+
Brands using Ketch CMP
30.8B
CDN requests per month
5+
Gartner Market Guides
1,000+
Systems, apps, and models
Discovery coverage
Always-on discovery across the systems you actually run
Running a privacy program means knowing where personal data lives, and that answer changes every time engineering ships a feature, marketing adopts a new tool, or a vendor updates its practices. Ketch Data Discovery and Classification keeps the answer current, scanning the warehouses, lakes, SaaS applications, and code where data actually lives, and re-classifying as schemas, pipelines, and AI workloads change.
Crawl complex enterprise systems
AI-powered discovery covers cloud, on-prem, and hybrid stacks, reaching the internal databases and third-party applications that survey-based approaches never fully capture.
Classification down to the cell
A four-phase discovery approach analyzes data from the system level down to individual cells, so sensitive data is labeled where it sits rather than inferred from a table name. Ketch classifies 100+ data categories, including communication, demographic, profile, financial, and location data, plus identifiers like names, emails, and SSNs.
Inference-based classification
Machine-driven classification labels sensitive and regulated data using responsive models rather than rules alone, so new fields and renamed columns are classified correctly without hand-tuned pattern libraries.
Contract scanning
Agents read data processing agreements, vendor contracts, and processing documentation, extracting the data categories, processing scope, residency, retention terms, security obligations, and sub-processor relationships a connector alone can't see.
Thank you for making software that lawyers can use. I can make adjustments quickly and confidently within Ketch without needing to speak code.
I love how easy it is to customize privacy notices for our brand voice and add new tags for our marketing campaigns. If you need a privacy solution that works seamlessly with your marketing activity, Ketch is the answer.
Ketch has the best customer support, ever. Their CX and engineering teams are fast, proactive, and communicative. They are serious about listening to customer feedback and translating it to product enhancements.
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In-place classification
Classification that runs in your environment
Discovery tools that copy records into a vendor cloud create the exact exposure a privacy team exists to prevent. Ketch classifies data in place and enriches what it finds with context about each system.
A security-first classification engine that runs inside your environment, classifying databases and warehouses like Snowflake, Postgres, and S3 without exposing or extracting raw data. The underlying records never leave your infrastructure.
Classification surfaces
What always-on classification covers
Five concrete classification surfaces for AI-era data permissioning.
Sensitive data labeling
Detect PII, PHI, payment, biometric, and other sensitive categories at the cell level, not the table level.
Schema drift
Re-classify automatically when columns are added, renamed, or repurposed across pipelines.
AI training data
Flag datasets that would feed AI models with non-permissioned or sensitive content before a training run starts.
Vendor sprawl
Map third-party SaaS and processor systems so vendor risk reviews start with evidence instead of a questionnaire.
Audit-ready evidence
Every classification decision is logged and queryable, which matters to legal, security, and any regulator who asks you to show your work.
From discovery to enforcement
Classified data feeds concrete next actions
01. Crawl
Discover systems and content across the enterprise.
02. Classify
Label sensitive, regulated, and permissioned data with inference-based classification.
03. Surface
Push findings into the Ketch data map, risk assessments, and to be used by the Agent Network.
04. Enforce
Use classified context to enforce purpose, jurisdiction, and consent at runtime.
Platform connections
Classification feeds the rest of the platform
A classification that sits in a report changes nothing. Ketch wires discovery output directly into the products that act on it.
Regulator-ready evidence
Prove what your data actually is when a regulator asks
U.S. enforcement has moved past privacy notices to technical reality. Regulators evaluate how data is actually collected, shared, and enforced across a brand's data ecosystem, and they increasingly expect brands to demonstrate compliant behavior through auditable evidence rather than written policies.
Integrations
Pre-built connections to the systems where your data lives
Ketch ships connectors and SDKs so discovery, consent, rights, and policy flow into your CDPs, warehouses, ad platforms, and AI stack without a custom data pipeline.
ROI
What teams ship when permissioning becomes infrastructure
Independent benchmarks and customer-reported gains across Discovery, Permissioning, and Growth.
12x
ROI vs. legacy, cookie-based privacy tools.
+95%
Productivity gain vs. manual DSR workflows.
+70%
Productivity gain vs. survey-based data discovery.
+38:1
ROI per $1 spent on preference & consent management.
Related reading
Expert insights from privacy leaders on data discovery
Frequently asked questions
Classify data before you govern or activate it
Book a demo to see Data Discovery & Classification in the Discovery layer.
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