Apps need sensitive-data collection.
Skyflow fits app data privacy workflows where sensitive fields are known up front, sent to a privacy vault, tokenized, and revealed later through governed APIs or SDKs.
Skyflow Alternative
Skyflow privacy vault alternative for redacting sensitive text and files.
Skyflow is a privacy vault for app data: collect known sensitive fields, store them in a vault, return tokens, and reveal values later through APIs or SDKs. Agent Mask is a private PII redaction workflow for sensitive data already embedded in text, documents, API payloads, and AI/ML training datasets.
Start a trial on Snowflake Marketplace, or get a self-hosted trial key for Docker.
SkyflowPrivacy vault for app dataCollect known fields, return tokens, reveal through APIs
Use case gapAPI handoffSnowflake UDF patterns call Skyflow REST APIs for tokenization and vault workflows
Agent MaskPrivate redactionDetect and de-identify PII in text, files, documents, and private API payloads.
1SELECT agent_mask_en.app_public.mask(
2 [ticket_note, chat_log]
3) AS redacted
4FROM support_tickets;
Input column
Text
ticket_note
Billing question from
Maya Chen
PERSON_1
about invoice INV-1042. Assigned to
Alex Patel
PERSON_2
. Contact:
maya.chen@example.com
EMAIL_ADDRESS_1
or
415-555-0198
PHONE_NUMBER_1
chat_log
10:42
Alex
PERSON_2
:
Maya
PERSON_1
never got the invoice email.
10:43 Maya Chen PERSON_1 replied from maya.chen@example.com EMAIL_ADDRESS_1 and asked Alex Patel PERSON_2 to call 415-555-0198 PHONE_NUMBER_1
10:43 Maya Chen PERSON_1 replied from maya.chen@example.com EMAIL_ADDRESS_1 and asked Alex Patel PERSON_2 to call 415-555-0198 PHONE_NUMBER_1
Different workflows: vault app data, redact sensitive text and files.
Skyflow fits the application layer, where known sensitive fields can be collected, tokenized, and revealed later through a privacy vault. Agent Mask fits downstream PII redaction workflows, where PII is already embedded in private API payloads, documents, warehouse text, and AI/ML training datasets.
Messy text needs private PII redaction.
Agent Mask finds and redacts PII in notes, tickets, transcripts, private API payloads, PDFs, images, DICOM, DOCX, RTF, and ZIP archives, with custom identifier detection when built-in entities are not enough.
A privacy vault is not downstream PII redaction.
Skyflow is built around application collection and tokenization. Warehouse redaction starts later, after sensitive values have already accumulated in messy content.
App collection comes first
A Skyflow vault works best when applications know which fields are sensitive and route app data through the vault before those values spread across systems.
Warehouse integrations still call Skyflow APIs
Skyflow's docs describe UDF patterns from Snowflake, Databricks, and BigQuery that invoke Skyflow REST APIs for insert and tokenize workflows. That is an API handoff to a Skyflow vault endpoint, not private redaction inside the warehouse or your own runtime.
Free text arrives messy
Support notes, transcripts, PDFs, images, and AI/ML training datasets can contain PII nobody modeled as a sensitive field. Agent Mask detects and de-identifies that content in Snowflake or a self-hosted runtime.
Skyflow vs Agent Mask.
Compare privacy vault workflows for app data with private PII redaction for sensitive text and files across starting point, API routing, data shape, and output.
Dimension
Skyflow
Agent Mask
Best use case
SkyflowProtecting app data at collection time with tokenization, governance, and reveal flows for known sensitive fields.
Agent MaskFinding, redacting, and de-identifying PII already stored in warehouse text, files, or private application workflows.
Starting point
SkyflowApp data flows where known fields can be sent to a vault before they spread.
Agent MaskMessy text and files: notes, tickets, transcripts, PDFs, images, and AI/ML training datasets.
Private data path
SkyflowWarehouse UDF patterns can invoke Skyflow REST APIs, sending values to a Skyflow vault/API endpoint for tokenization.
Agent MaskKeeps redaction inside the deployment boundary you choose: Snowflake for the native app, or your infrastructure for self-hosted.
Data shape
SkyflowStrong for structured app data that applications intentionally collect and vault.
Agent MaskBuilt for free text, documents, transcripts, tickets, and custom identifiers.
Primary output
SkyflowTokens, vault records, reveal controls, and governed application access.
Agent MaskDe-identified text, redacted files, entity metadata, and configurable replacements.
Reference material
This page uses Skyflow product and documentation pages for vault architecture, deployment models, Snowflake UDF patterns, and integrations.
Skyflow product overview
Skyflow documentation for Data Privacy Vault architecture, governance, encryption, tokenization, APIs, SDKs, and integrations.
Getting data into Skyflow
Skyflow documentation for using UDFs from Snowflake, Databricks, and BigQuery to call Skyflow REST APIs.
Skyflow Data API
Skyflow API reference showing vault API base URIs for inserting, retrieving, and managing data in a vault.
Skyflow Connections
Skyflow documentation for sending data between first- and third-party services.
Skyflow security
Skyflow public security page for privacy vault controls and compliance posture.
Agent Mask zero-egress architecture
Agent Mask documentation explaining how Snowflake Native App and self-hosted Docker processing stay inside your chosen runtime without sending payloads to Agent Mask.
Agent Mask self-hosted security
Agent Mask documentation for self-hosted data flow, network requirements, offline license verification, retention, and hardening.
Related comparisons
Keep evaluating redaction options across the same private-runtime, data movement, pricing, and implementation questions.
Protegrity protects mapped fields. Agent Mask de-identifies PII buried in text.
Compare Agent Mask with Protegrity as an enterprise data protection alternative for PII discovery, field-level protection gaps, and private de-identification across text and files.
Alternative to LLM-based PII redaction without token costs or data egress.
Stop paying per-token LLM prices to redact sensitive text at scale. See how Agent Mask compares with OpenAI, Claude, Gemini, and Bedrock when sensitive-text redaction needs to run in Snowflake or a self-hosted deployment.
Agent Mask beat OpenAI Privacy Filter in a 50,000-example PII detection benchmark.
Agent Mask reached 96.9% F1 vs 74.2% for OpenAI Privacy Filter on a 50,000-example English PII benchmark, while also returning redacted output and review metadata.
Skyflow alternative FAQ
Answers for teams comparing privacy vault workflows for app data with PII redaction for sensitive text and files.
When is Skyflow the right choice?
Skyflow is a strong fit when applications need to collect known sensitive fields, store that app data in a vault, return tokens, and reveal or use those values through governed APIs and SDKs.
Does Skyflow solve PII already sitting in warehouse data?
A vault works best when applications route known sensitive fields into it early. Your warehouse and downstream pipelines can already have PII from third-party systems, SaaS tools, uploads, and workflows the vault never saw. Agent Mask detects, redacts, and de-identifies that content after it lands.
How does Agent Mask supplement a data vault?
A data vault helps applications control known fields before they spread. Agent Mask complements it downstream by scanning sensitive text the vault never saw, then returning redacted output and entity evidence for review.
Can Skyflow work with Snowflake?
Yes, but Skyflow's documented Snowflake pattern is an API handoff: use a UDF to invoke Skyflow REST APIs for insert and tokenize workflows, sending values to a Skyflow vault/API endpoint. That can make sense for vaulting known fields, but it is still a vault API integration, not a redaction workflow running in the customer's private runtime. Agent Mask covers that workflow with Snowflake-native processing or self-hosted deployment.
Is Skyflow built for messy text and documents?
Skyflow is strongest for known fields routed through application collection, tokenization, and reveal flows. Agent Mask is built for unstructured text, supported file formats, and custom identifiers in Snowflake or self-hosted workflows.
When is Agent Mask the better fit than a Skyflow vault?
Use Agent Mask when the problem starts after collection: PII is already buried in warehouse text, support notes, transcripts, documents, or AI/ML datasets, and you need private redaction in Snowflake or self-hosted infrastructure instead of routing known fields into a vault API.
Redact messy text without adding an app data vault.
Use Agent Mask as a privacy vault alternative when the job is finding, redacting, and de-identifying sensitive text and documents already stored in Snowflake or private infrastructure.