Protection That Follows the Data
A zero-trust vault and runtime tokenization protect PII wherever it flows, including into AI, not just at the database edge.
Your most sensitive data, from customer PII to payment details and health records, is copied across warehouses, apps, logs and now AI pipelines. Every copy is exposure, and AI multiplies it. Skyflow is a data privacy vault that isolates and tokenizes sensitive data and controls it at runtime, so analytics and AI run on protected data, not raw PII. Flentas integrates it across your AWS data platform, applications and AI.
Data protection used to be about the database. Now sensitive data spreads across every system and flows into AI, where a single prompt or agent can expose it.
PII sits in warehouses, applications, logs, analytics platforms and SaaS tools. Every copy widens the blast radius of a breach and the scope of an audit.
Feeding real customer data to models, agents, retrieval and MCP servers can leak PII in ways traditional controls never anticipated, which stalls AI projects at the security review.
The DPDP Act, GDPR, HIPAA and PCI each make demands on the same data, and residency rules add where it may live. Enforcing all of that by hand does not scale.
Keep sensitive data in a vault, let the rest of your systems work with tokens, and control access at the moment data is used.
A zero-trust vault and runtime tokenization protect PII wherever it flows, including into AI, not just at the database edge.
Teams can build on real data safely, so AI projects clear security review instead of dying in it.
A dedicated vault replaces months of in-house engineering, and Flentas integrates it into your stack quickly.
AWS Advanced Consulting Partner and AWS APJ Partner of the Year 2025, with the data engineering and security experience to make protection real.
We start by finding the exposure, then vault the sensitive data, then keep it protected as new apps and AI use cases arrive. Protection follows the data, not the perimeter.
We discover where sensitive data lives and how it is exposed, especially to analytics and AI, map it to your compliance obligations and design the vault architecture.
We stand up the Skyflow vault, tokenize PII, integrate it with your applications, data platform and AI pipelines on AWS, and set field-level, role-based runtime access policies.
We run it, extend protection to new AI and analytics use cases, monitor data flows, and keep residency and compliance intact as you grow.
Skyflow isolates sensitive data in a zero-trust vault with polymorphic encryption and field-level, role-based access. Flentas weaves it through your real systems and operates it so protection keeps pace as you scale.
Find PII across structured and unstructured sources, then isolate and tokenize it so downstream systems hold tokens, not raw data.
Build and deploy models, agents, retrieval and MCP servers on real data without leaking PII, with access controlled at runtime by role and field.
Govern how data moves through agents and multi-agent workflows, so context sharing does not become data leakage as your agent estate grows.
Run analytics on Databricks, Snowflake and similar platforms using tokenized data, so teams get insight without direct exposure to PII.
Meet localization requirements under laws such as the DPDP Act and GDPR without spinning up and maintaining separate regional stacks.
Reduce the scope and cost of HIPAA, PCI, GDPR and DPDP obligations by shrinking where sensitive data actually lives.
Protecting data at runtime sits where data engineering meets security, which is where Flentas works. Skyflow customers such as GoodRx already use its vault to govern PII inside platforms like Databricks and BigQuery; the Flentas engagements below show the data and security foundations we bring to that integration.
Protecting sensitive data starts with seeing and governing data across the whole estate.
A cloud-agnostic, centrally governed data platform across roughly 2,500 accounts on AWS, Azure and GCP, processing more than 500 million events per day with full audit logging.
Payments data is exactly the kind of sensitive data a vault is built to protect.
A governed data lake on AWS fed by change-data capture, with a clear audit trail and reporting moved off the production database onto an auditable foundation.
Sensitive data protection and AI are converging fast, and the partnership is investing where the exposure is growing.
Governing PII across agents, multi-agent workflows and MCP servers so the agentic enterprise does not leak sensitive data.
Retrieval and analytics that run on tokenized data, so AI features and dashboards never touch raw PII.
Architectures that keep data in region and under control, so AI stays compliant with residency and sovereignty requirements.
Making tokenization a default step in ingestion, so new data is protected the moment it lands.
Skyflow is the data-layer vault. It pairs with consent and compliance tooling rather than replacing it.
Consent, data protection and Data Principal rights ahead of the deadline.
Explore DPDPOur consent-management delivery partner for DPDP rollouts.
Explore GoTrust PartnershipOne governed copy of your data, ready for BI and AI.
Explore Data EngineeringYou cannot protect what you cannot see. A Flentas sensitive data assessment shows where your PII lives, where it is exposed, especially to analytics and AI, and how to bring it under control. You get a prioritized exposure and risk report, a vault architecture for your applications, data platform and AI, and a roadmap to protect sensitive data and unblock safe AI. No obligation.