Protecto
UnclaimedProtecto 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.
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Claim ProtectoUse your email at protecto.ai.What we offer
Privacy Vault
Safeguard sensitive data while ensuring AI accuracy through isolation and tokenization.
protecto.ai →GPTGuard
Ensures secure AI operations by masking sensitive data and filtering harmful content.
protecto.ai →Context-Based Access Control for AI
Provides real-time access control and data protection for AI workflows, ensuring compliance and security.
protecto.ai →Privacy Gateway for AI Chat
Protects sensitive data during AI chat interactions, ensuring privacy and compliance.
protecto.ai →Protecto DeepSight
Enhance data protection with advanced context-aware detection for AI systems.
protecto.ai →High-volume Masking
Efficiently mask high volumes of sensitive data while maintaining compliance and AI accuracy.
protecto.ai →Secure RAG
Enhances AI security while maintaining data accuracy across retrieval-augmented generation applications.
protecto.ai →Market segments
Market size by segment
Growth potential (CAGR)
Inference-time access control
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
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
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
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 AccessEnsures compliance by providing a detailed log of all access events related to sensitive data.
- Centralize Data ProtectionReduces breach risk by storing sensitive information in a secure, isolated system.
- Preserve AI AccuracyEnables the use of sensitive data without exposing it, maintaining both security and AI model performance.
- Control Data AccessGives organizations strict control over who accesses sensitive data, enforcing compliance through role-based permissions.
- Ensure ComplianceHelps enterprises meet mandatory privacy and data protection requirements, reducing legal risks.
- Enable Smart MaskingMaintains 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 InteractionsMaintains the integrity of AI outputs by ensuring sensitive information is masked without losing contextual meaning.
- High Precision Data DetectionUtilizes advanced algorithms to detect sensitive data types accurately, ensuring comprehensive coverage for diverse datasets.
- Instant Data ProtectionAutomatically enforces compliance policies as data is processed, ensuring immediate protection of sensitive information.
- Enhances Safety of AI OutputsPrevents the generation and dissemination of inappropriate or harmful content, ensuring a safer AI interaction environment.
- Boosts AI EfficiencyEnables 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 DecisionComprehensive logs support compliance audits by detailing who accessed what data and when.
- Controls Data Access In Real-TimeEnsures that only authorized data is used during AI reasoning, enhancing security and compliance.
- Enforces Fine-Grained PermissionsAccess is granted based on user roles and specific contexts, ensuring data integrity and reducing exposure risks.
- Masks Unnecessary DataSensitive information is masked based on user context, preserving important data visibility without exposing sensitive details.
- Streamlines Compliance ReportingEasily meets compliance requirements for HIPAA, GDPR, and more through built-in policy management.
- Identifies Sensitive DataAccurately 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 DataThis feature allows organizations to use AI models safely by masking sensitive information, ensuring that actual sensitive data is never exposed during interactions.
- Streamline Compliance EffortsIntegrates robust auditing features with compliance policies to ensure adherence to data protection regulations, enhancing trust and security.
- Ensure Conversation PrivacyThe Gateway keeps sensitive conversation contexts secure, preventing data retention and unauthorized access by third-party providers.
- Enable Accurate Model ResponsesEnsures that while tool calls are made with masked data, authorized users have access to real values when necessary for operational purposes.
- Utilize The Best ModelsAllows 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 TraceabilityProtecto DeepSight provides API access with complete metadata for all actions, ensuring regulatory compliance and detailed traceability, essential for audits.
- Identify Hidden Sensitive InformationLeveraging 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 InfrastructureSupport diverse deployment scenarios, whether in the cloud or on-premises, enabling organizations to integrate with existing systems seamlessly.
- Handle Complex Data SecurelyDeepSight excels in managing unstructured and noisy data, providing effective detection capabilities in challenging environments.
- Tailor Detection to Your NeedsDeepSight 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 ManagementReduces costs by scaling resources only when necessary, ensuring optimal performance.
- Handle Intensive WorkloadsSupports vigorous data processing without compromising speed or efficiency.
- Optimize Data HandlingEnsures timely processing by handling large volumes without sacrificing performance.
- Preserve AI AccuracyEnsures that sensitive data masks do not impair the AI's ability to deliver accurate responses.
- Streamline Data FlowsMinimize bottlenecks and maintain smooth operations when processing large data volumes.
- Ensure ComplianceFacilitate 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 ComplianceEvery data access event is logged, ensuring compliance with GDPR, HIPAA, and other regulations.
- Masks Sensitive Data Before UseSensitive information is masked prior to being processed or stored, maintaining context.
- Dynamic Data Access ControlEnsures that users only have access to authorized content during data retrieval.
- Ensures Data Privacy Between ClientsStrict namespace boundaries prevent unauthorized access to sensitive data among different tenants.
- Access Original Data When NeededEnsures 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.
- The global data classification market size was valued at USD 2.3 Billion in 2025.
- The global data classification market size was valued at USD 2.28 Billion in 2025 and is projected to grow... at a CAGR of 21.42% (2026-2034).
- Global Data Discovery Market reached a valuation of US$ 18.78 Billion in 2026 and is anticipated to grow at a CAGR of 16.62%.
- In 2023, the Data Discovery And Classification Industry was valued at $2.5 billion and is expanding at a 12.8% CAGR between 2024 and 2033.
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 $13B by 2030 with ~26% CAGR to 2030. Data tokenization and vaulting (the specified segment) are a component of this broader tokenization market; industry content in the results indicates rising demand for tokenization/vaulting for data protection and AI workflows, supporting high growth aligned with the cited CAGR.
Retrieval-augmented generation protection
Estimation based on reported global RAG market sizes (≈USD 1.2–1.94B base years) and forecast CAGRs (≈38–49%). RAG protection (pre-embedding tokenization, retrieval-time auth, tenant isolation, logging) is a subset of RAG infrastructure and services; conservatively assumed ~10% share of total RAG spend, yielding ~USD 0.19B. Growth potential aligned with overall RAG CAGR (regulatory pressure and enterprise security needs could sustain similar or slightly higher growth), estimated at ~40% CAGR.
- Protecto
- Privacy Vault
- GPTGuard
- Context-Based Access Control for AI
- Privacy Gateway for AI Chat
- Protecto DeepSight
- High-volume Masking
- Secure RAG
- The Inference-as-a-Service market was valued at USD 2.93 Billion in 2024
- expected to be valued at US$ 18.2 billion in 2026
- Market Size, 2024 $97.2B
- USD 317.39 BN MARKET SIZE, 2031 CAGR 23.3%
- The global data classification market size was valued at USD 2.3 Billion in 2025.
- The global data classification market size was valued at USD 2.28 Billion in 2025 and is projected to grow... at a CAGR of 21.42% (2026-2034).
- Global Data Discovery Market reached a valuation of US$ 18.78 Billion in 2026 and is anticipated to grow at a CAGR of 16.62%.
- In 2023, the Data Discovery And Classification Industry was valued at $2.5 billion and is expanding at a 12.8% CAGR between 2024 and 2033.
- forecasted to reach a valuation exceeding $13 billion by 2030; anticipated to grow at a CAGR of 26% through to 2030.
- Market Size, 2024 $1.2B; CAGR, 2025–2030 49.1%.
- Market Size (2025) USD 1.92 Billion; Growth Rate (2025 - 2030) 39.66%.
- Market Size Base Year ~USD 1.94 (2025); Revenue Forecast ~USD 9.84 (2030); CAGR of 38.4%.
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