Protecto lets AI agents, models and MCP tools work with sensitive data without exposing the real values. It finds PII, PHI, payment data and business confidential information as data flows into AI systems, replaces it with consistent tokens, and decides at runtime which user, agent or task is allowed to see the original.
It is built for organisations that want to put customer, patient or financial data in front of large language models, retrieval pipelines and agents while staying within privacy rules.
At A Glance
| Vendor | Protecto |
|---|---|
| Category | Data security and privacy for AI agents, LLMs and RAG |
| Identities covered | Human users, roles and groups, AI agents and MCP tool calls |
| Deployment | SaaS, on premises, private cloud or air gapped; gateway or API |
| Agentic AI | Runtime masking and access control for agents, agent handoffs and MCP tool calls |
| Certifications | SOC 2 Type II, ISO 27001, HIPAA compliant (BAA available) |
| Customers | Bank Muscat, Automation Anywhere |
| Market classification | AI Data Security; also Privacy & Decentralised Identity |
What Protecto Does
The company’s stated purpose is “to safeguard data security and privacy while AI drives global progress.” The tension it resolves is that AI is only useful with real data, yet real data is exactly what privacy and security teams must keep from leaking into prompts, logs and third-party models.
Tokenisation is the core technique. Sensitive values become secure, consistent tokens, so the data stays usable for analytics, logging, debugging and AI inference, and authorised readers can have values unmasked when they need them. The second half of the approach is deciding, request by request, who may see what, so the same masked data can serve many users and agents with different rights.
Products
Privacy Vault
Privacy Vault scans, masks and stores sensitive data without degrading AI accuracy. Because the same value always gets the same token, in any session and at any time, joins, analytics and model behaviour still work on masked data.
- Format preserving, context preserving and entropy based token strategies for structured and unstructured data
- Access control, audit logs, multi tenancy and data retention APIs
- Real time, async and bulk APIs
GPTGuard
GPTGuard is a protected AI chat and document workspace for employees. It masks sensitive data before any model sees it and applies CBAC policy to every answer. Users can upload files and chat through HyperSearch RAG, with each answer listing its source passages, and OCR handles scanned documents; web grounded chat is optional.
Context Based Access Control (CBAC)
CBAC tackles a problem traditional permissions miss: once documents are ingested for AI, a single file can contain sections different people should not all see. CBAC enforces access at section or sentence level at runtime, on every retrieval, agent handoff, MCP tool call and model input, and logs every decision. Secure RAG applies the same masking and policy to retrieval augmented answers.
Privacy Gateway For AI Chat
The gateway lets teams run any AI model on sensitive data while the model only ever receives tokens. It sits between applications and the models and tools they call, so protection does not have to be built into each application.
DeepSight
DeepSight is the detection and classification engine behind the other products. It recognises more than 50 PII, PHI and PCI entity types out of the box, plus business confidential context such as deal terms and legal strategy, supports custom entities and healthcare and banking add ons, and is tested in seven languages.
How It Works
| API flow | Protecto is an API-first platform. Customers call the API where data enters or leaves their system, and Protecto handles detection, masking and optional unmasking. |
|---|---|
| Private deployment | On premises and private cloud deployments, including air gapped setups, run inside the customer environment, and external models receive only tokens. |
| Policy binding | Access policy is bound to users and applications in the customer’s own Active Directory or access control system. |
Identities And Systems Covered
| Human users | Users, roles and groups defined in the customer’s directory. |
|---|---|
| AI agents | Policy applies at the moment an agent asks for data, and tenant or team rules carry across agent to agent handoffs. Each decision is logged with who asked, for which task and which values each reader received, giving a trail across whole chains of agents. |
| MCP tools | MCP tool calls are checked at runtime. |
| Data | PII, PHI, PCI and business confidential content in structured and unstructured sources. |
Integrations
| Area | Integrations |
|---|---|
| Data platforms | Snowflake UDF, Databricks, Kafka, Spark |
| AI frameworks | LangChain, LlamaIndex |
Company Background
| Founded | 2021. |
|---|---|
| Leadership | Amar Kanagaraj (Founder and CEO), Baskaran Alagarsamy (Co-founder and CTO). |
| Funding | $5 million seed round in November 2023, with backers including Together, Arali Ventures, Better Capital, Special Invest, FortyTwo VC and Zapier. |
| Recognition | Selected for Google’s AI First Accelerator 2025, one of 20 startups chosen from more than 1,600 applications. |
Note: This overview is compiled from Protecto’s publicly available information as of 4 November 2026. It is provided for information only. NHI Mgmt Group does not endorse any vendor, and nothing on this page represents the opinions of NHI Mgmt Group.