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Protecto

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Privacy TechnologySoftwareprotecto.aiUpdated

Protecto provides a unified AI data control plane that protects enterprise data across AI workflows, enabling secure, compliant AI use.

Overview

Protecto provides an AI data control plane that guards enterprise data as it moves through AI systems. The platform detects sensitive information in real time, applies context-preserving masking and tokenization, and enforces who can access data through policy-driven controls embedded in the AI stack. It supports data governance, audit trails, and regulatory compliance across diverse workflows, including LLMs, retrieval-augmented generation, and AI agents. Built with an engineering-first mindset, Protecto aims to preserve AI accuracy while delivering enterprise-grade security and privacy. The company serves regulated industries and helps customers meet privacy and security requirements while enabling safe, responsible AI adoption.

Mission statement

Our purpose is to safeguard data security and privacy while unleashing the power of AI to drive global progress.

One of 10 AI agents in Privacy TechnologyRead recently byOpenAIAmazon

What we offer

Privacy Vault

Safeguard sensitive data while ensuring AI accuracy through isolation and tokenization.

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GPTGuard

Ensures secure AI operations by masking sensitive data and filtering harmful content.

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Context-Based Access Control for AI

Provides real-time access control and data protection for AI workflows, ensuring compliance and security.

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Privacy Gateway for AI Chat

Protects sensitive data during AI chat interactions, ensuring privacy and compliance.

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Protecto DeepSight

Enhance data protection with advanced context-aware detection for AI systems.

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High-volume Masking

Efficiently mask high volumes of sensitive data while maintaining compliance and AI accuracy.

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Secure RAG

Enhances AI security while maintaining data accuracy across retrieval-augmented generation applications.

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Market segments

Market size by segment

Growth potential (CAGR)

Inference-time access control

1.5 Billion USD24% CAGR

Controls and enforces who can see or unmask data during AI model inference, including dynamic masking, policy-driven decisions, and audit logging for compliance.

Products: Context-Based Access Control for AI, Privacy Gateway for AI Chat, GPTGuard

Data discovery and classification

2.3 Billion USD20% CAGR

Capabilities to locate, inventory, and apply context-aware classification to structured and unstructured sensitive data across on‑premises, cloud, and SaaS sources to support mapping and access controls.

Products: Protecto DeepSight, GPTGuard, Context-Based Access Control for AI

Data tokenization and vaulting

13 Billion USD26% CAGR

Techniques to isolate, tokenize or mask sensitive values in a centralized, auditable vault to minimize exposure while preserving context for AI workflows.

Products: Privacy Vault, High-volume Masking, Secure RAG

Retrieval-augmented generation protection

0.19 Billion USD40% CAGR

Controls applied to RAG pipelines and vector stores such as pre-embedding tokenization, retrieval-time authorization, tenant isolation, and compliance logging to prevent sensitive data leakage.

Products: Secure RAG, GPTGuard, High-volume Masking

More information about our offering

Privacy Vault

A dedicated data privacy vault that isolates sensitive data in one hardened system and replaces that data everywhere else with tokens. It combines isolation, masking or tokenization, policy-based access control, and audit logging to protect data across AI workflows, including prompts, RAG pipelines, and AI agents.

  • Track Data Access
    Ensures compliance by providing a detailed log of all access events related to sensitive data.
  • Centralize Data Protection
    Reduces breach risk by storing sensitive information in a secure, isolated system.
  • Preserve AI Accuracy
    Enables the use of sensitive data without exposing it, maintaining both security and AI model performance.
  • Control Data Access
    Gives organizations strict control over who accesses sensitive data, enforcing compliance through role-based permissions.
  • Ensure Compliance
    Helps enterprises meet mandatory privacy and data protection requirements, reducing legal risks.
  • Enable Smart Masking
    Maintains the integrity of AI model outputs by ensuring that context is preserved when masking sensitive information.

GPTGuard

Protects generative AI pipelines with context-preserving masking and toxic content filtering, enabling safe AI interactions while preserving model accuracy.

  • Enables Safe AI Interactions
    Maintains the integrity of AI outputs by ensuring sensitive information is masked without losing contextual meaning.
  • High Precision Data Detection
    Utilizes advanced algorithms to detect sensitive data types accurately, ensuring comprehensive coverage for diverse datasets.
  • Instant Data Protection
    Automatically enforces compliance policies as data is processed, ensuring immediate protection of sensitive information.
  • Enhances Safety of AI Outputs
    Prevents the generation and dissemination of inappropriate or harmful content, ensuring a safer AI interaction environment.
  • Boosts AI Efficiency
    Enables seamless integration of vast document resources, enhancing the context and relevance of AI-assisted interactions.

Context-Based Access Control for AI

Context-Based Access Control (CBAC) enforces policies for AI data at inference time, controlling who sees what data as agents reason and act, with dynamic masking and a complete audit trail.

  • Logs Every Decision
    Comprehensive logs support compliance audits by detailing who accessed what data and when.
  • Controls Data Access In Real-Time
    Ensures that only authorized data is used during AI reasoning, enhancing security and compliance.
  • Enforces Fine-Grained Permissions
    Access is granted based on user roles and specific contexts, ensuring data integrity and reducing exposure risks.
  • Masks Unnecessary Data
    Sensitive information is masked based on user context, preserving important data visibility without exposing sensitive details.
  • Streamlines Compliance Reporting
    Easily meets compliance requirements for HIPAA, GDPR, and more through built-in policy management.
  • Identifies Sensitive Data
    Accurately classifies sensitive information, ensuring only appropriate access based on context.

Privacy Gateway for AI Chat

A privacy gateway that allows running AI models on sensitive data in AI chat contexts without exposing real values, reducing data exposure during interactions.

  • Safeguard Sensitive Data
    This feature allows organizations to use AI models safely by masking sensitive information, ensuring that actual sensitive data is never exposed during interactions.
  • Streamline Compliance Efforts
    Integrates robust auditing features with compliance policies to ensure adherence to data protection regulations, enhancing trust and security.
  • Ensure Conversation Privacy
    The Gateway keeps sensitive conversation contexts secure, preventing data retention and unauthorized access by third-party providers.
  • Enable Accurate Model Responses
    Ensures that while tool calls are made with masked data, authorized users have access to real values when necessary for operational purposes.
  • Utilize The Best Models
    Allows users to engage top-performing AI models without compromising on data security, enhancing the quality of AI interactions.

Protecto DeepSight

Protecto DeepSight provides context-aware detection for sensitive data, with custom entity recognition, handling of messy data, and flexible deployment. It offers API-first access and audit-ready metadata with enterprise-grade security.

  • Ensure Compliance and Traceability
    Protecto DeepSight provides API access with complete metadata for all actions, ensuring regulatory compliance and detailed traceability, essential for audits.
  • Identify Hidden Sensitive Information
    Leveraging context-aware detection, DeepSight can recognize sensitive data even when obscured by typos or mixed languages, enhancing protection and reducing compliance risk.
  • Adapt to Your Infrastructure
    Support diverse deployment scenarios, whether in the cloud or on-premises, enabling organizations to integrate with existing systems seamlessly.
  • Handle Complex Data Securely
    DeepSight excels in managing unstructured and noisy data, providing effective detection capabilities in challenging environments.
  • Tailor Detection to Your Needs
    DeepSight can be trained to recognize unique identifiers relevant to your organization, ensuring high precision in data detection.

High-volume Masking

High-volume masking for masking large data volumes efficiently, enabling scalable protection of sensitive information across AI workflows.

  • Efficient Resource Management
    Reduces costs by scaling resources only when necessary, ensuring optimal performance.
  • Handle Intensive Workloads
    Supports vigorous data processing without compromising speed or efficiency.
  • Optimize Data Handling
    Ensures timely processing by handling large volumes without sacrificing performance.
  • Preserve AI Accuracy
    Ensures that sensitive data masks do not impair the AI's ability to deliver accurate responses.
  • Streamline Data Flows
    Minimize bottlenecks and maintain smooth operations when processing large data volumes.
  • Ensure Compliance
    Facilitate regulatory compliance monitoring with detailed access logs.

Secure RAG

Secure RAG (SecRAG) embeds protection into retrieval-augmented generation pipelines, tokenizing sensitive data before embedding, enforcing retrieval-time access, and isolating tenants to prevent cross-tenant data leakage with built-in compliance logging.

  • Supports Regulatory Compliance
    Every data access event is logged, ensuring compliance with GDPR, HIPAA, and other regulations.
  • Masks Sensitive Data Before Use
    Sensitive information is masked prior to being processed or stored, maintaining context.
  • Dynamic Data Access Control
    Ensures that users only have access to authorized content during data retrieval.
  • Ensures Data Privacy Between Clients
    Strict namespace boundaries prevent unauthorized access to sensitive data among different tenants.
  • Access Original Data When Needed
    Ensures safety by allowing only authorized users to retrieve original values.

Sources

Methodology and sourcing behind the figures and links shown above.

Inference-time access control

No explicit market-size for "inference-time access control" was found in the provided results. I triangulated from related markets: inference-as-a-service (USD 2.93B in 2024, CAGR ~24.7%), AI inference/inference-accelerator markets (tens of billions, CAGRs ~17–24%), and edge computing (large market, CAGR ~23%). Inference-time access control is a specialized software/security subsegment of the broader inference and inference-as-a-service market; assuming it represents a small share (~1–3%) of the broader inference software/service opportunity yields an estimated market size of about USD 1.5B. Growth potential is aligned with inference and inference-as-a-service growth (roughly mid-20% CAGR); I estimate a CAGR of ~24% for this niche given rising regulatory and compliance demand.

Data discovery and classification

Search results for data classification consistently report a ~USD 2.3B market size in the mid-2020s (IMARC, Value Market Research). Several forecasts show strong growth: IMARC/VMR predict ~20–21% CAGR for data classification, while broader data-discovery reports (Econ Market Research) show a larger discovery market (~USD 18.8B) with ~16.6% CAGR. A VerifiedIndustry excerpt reports USD 2.5B in 2023 with a 12.8% CAGR to 2033. Combining classification-specific estimates and higher growth expectations from AI-driven automation, a conservative estimate for the combined data discovery & classification segment is ~USD 2.3B today with ~20% CAGR potential.

Data tokenization and vaulting

Estimate based on the cited tokenization market projection (Business Research Company) reported in the provided search result: the tokenization market is forecast to exceed $13B by 2030 with ~26% CAGR to 2030. Data tokenization and vaulting (the specified segment) are a component of this broader tokenization market; industry content in the results indicates rising demand for tokenization/vaulting for data protection and AI workflows, supporting high growth aligned with the cited CAGR.

Retrieval-augmented generation protection

Estimation based on reported global RAG market sizes (≈USD 1.2–1.94B base years) and forecast CAGRs (≈38–49%). RAG protection (pre-embedding tokenization, retrieval-time auth, tenant isolation, logging) is a subset of RAG infrastructure and services; conservatively assumed ~10% share of total RAG spend, yielding ~USD 0.19B. Growth potential aligned with overall RAG CAGR (regulatory pressure and enterprise security needs could sustain similar or slightly higher growth), estimated at ~40% CAGR.

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