Frequently Asked Questions
19 questions about privacy-as-a-service partner program — answered with data.
Token-Based Pricing
Why do enterprise PII tools cost $50,000+ per year? We're a 10-person startup that just needs to anonymize customer support tickets before sending them to our AI vendor.
The free tier provides functional PII anonymization with no credit card required. The €3/month Starter plan covers most SMB use cases. The €15/month Professional plan handles high-volume processing. No six-figure contract, no implementation fees, no vendor lock-in. ISO 27001 certification and GDPR compliance ensure enterprise-grade security at SMB-friendly prices. Example: A 5-person legal tech startup needs to anonymize client intake forms before logging them in their CRM. They cannot afford $30K/year enterprise tools. anonym.legal's free tier covers their 500 monthly documents. As they scale to 50 clients, the €15/month Professional plan handles 5,000 monthly documents — total annual cost €180 vs. $30,000 for alternatives.
I tried Microsoft Presidio but after 3 days of setup I still can't get it to run reliably. I just want something that works without DevOps overhead. Is there a hosted option?
anonym.legal is built on the Presidio engine but delivered as a fully managed SaaS and desktop product. Zero setup, zero DevOps, zero dependency management. The same ML accuracy (Presidio + XLM-RoBERTa enhancement) is available at €3/month. Users get Presidio-level detection without touching a terminal. Example: A small HR consulting firm wants to anonymize candidate CVs before sharing with clients. Their team has no engineers. Presidio setup is impossible without hiring a contractor (€2,000-5,000). anonym.legal Professional at €180/year provides the same ML accuracy through a web interface their HR team can use immediately.
Our NGO handles sensitive refugee data — we need strong anonymization but have literally no budget. Is there any GDPR-compliant tool that's actually free?
The perpetually free tier (not a trial) provides real anonymization capability. For NGOs, academic institutions, and public interest organizations, the free tier covers foundational use cases. The €3/month Starter plan is accessible even on shoestring budgets. EU data residency and GDPR compliance ensure the tool itself meets the regulatory requirements these organizations face. Example: A refugee support NGO in Germany processes intake interviews containing names, nationalities, family details, and medical information. GDPR compliance is mandatory but their tech budget is €0. anonym.legal's free tier allows their caseworkers to anonymize case files before sharing with partner organizations, achieving GDPR compliance at zero cost.
Why do all the enterprise data anonymization tools start at $800/month? I'm a solo lawyer who needs to redact client documents occasionally.
The token-based pricing model (Free: 200 tokens, Basic: €3, Pro: €15, Business: €29) is specifically designed for this segment. A solo lawyer doing occasional document redaction uses the Basic plan at €3/month. A small law firm with regular document processing uses the Business plan at €29/month. This is 30-100x less expensive than enterprise alternatives.
I'm a freelance data analyst — I occasionally need to anonymize datasets for clients. Do I really need to pay $500/month for a tool I use twice a week?
The free tier with token allocation covers light freelance use at zero cost. The €3/month Starter plan serves most freelance data work. The token model is transparent — users understand exactly what they're paying for. No annual commitments, no minimum seats. Example: A freelance GDPR consultant processes 20-30 client document sets per month, each requiring anonymization before sharing findings. At €3/month (Starter), total annual cost is €36. The alternative — a per-seat enterprise tool — would require convincing each client to purchase their own license, creating friction in every engagement.
Our company evaluated 8 PII tools — half had no public pricing and required 'contact sales.' What are they hiding? Why can't I just sign up and test it?
All pricing is publicly listed on the pricing page. Users can sign up for the free tier instantly, test the product fully, and upgrade without ever talking to a salesperson. No "contact sales" gate. Token allocation is clearly explained. This self-serve model is particularly appealing to developer and technical buyer audiences who distrust opaque pricing. Example: A compliance manager at a mid-size fintech needs to evaluate 5 PII tools in one week. Three require "contact sales" — they're immediately deprioritized. anonym.legal is on the short list because the manager can sign up, test on real data, and confirm the tool works in under an hour. Transparent pricing at €15/month closes the evaluation without procurement delays.
Presets System
Different people on our team anonymize documents differently — some redact names, others don't. We need a way to standardize our anonymization process across the whole department.
Named presets encode the full configuration: which entity types to detect, which anonymization method to apply, language settings, custom entities, and confidence thresholds. Presets can be shared with the entire team or organization. New team members start with the approved preset rather than configuring from scratch. Compliance templates (GDPR Minimum, HIPAA Safe Harbor, FOIA Exemption 6) are pre-built starting points. Example: A legal department processes client documents with 8 different paralegals. Without presets, each paralegal's approach to anonymization varied. After an audit finding that inconsistent redaction created liability, the department's privacy counsel creates a "Client Document Review" preset (names, addresses, phone numbers, national IDs — all Redact method). All 8 paralegals apply this preset by default. Inconsistency eliminated. Audit trail shows consistent application.
We work with multiple regulatory frameworks — GDPR for EU clients, HIPAA for US healthcare, CCPA for California. Managing different anonymization requirements for each is a nightmare. Is there a way to save different configurations?
Presets can be named and organized by regulatory framework. A "GDPR Standard" preset detects EU-relevant entity types. A "HIPAA Safe Harbor" preset includes all 18 identifier categories including dates and geographic data. A "CCPA Consumer Data" preset focuses on consumer PII categories. Each preset is one click to apply, and presets can be shared with the compliance team to ensure consistent framework application across the organization. Example: A multinational SaaS company's privacy team processes documents for EU customers (GDPR), US healthcare clients (HIPAA), and California consumers (CCPA) in the same workflow. Three saved presets — applied based on client type — ensure the right entities are detected and redacted for each regulatory context. Error rate from manual reconfiguration drops from ~15% to near zero. Annual compliance audit passes without findings related to inconsistent anonymization.
Our data science team needs to anonymize training data consistently — the same PII categories removed every time, regardless of who runs the process. How do we prevent people from accidentally including PII in training sets?
Saved presets with the exact entity selection, anonymization method (Replace is preferred for ML training data to preserve statistical properties), and language settings create a reproducible anonymization pipeline. The preset acts as a compliance guardrail — users apply the preset without being able to accidentally deviate from approved settings. This supports both GDPR compliance and ML reproducibility requirements. Example: A European fintech company's ML team uses a "Training Data - GDPR" preset for all training dataset preparation. The preset is created and approved by the DPO, then used by 12 data scientists without modification ability. Audit trail shows every dataset preparation used the approved configuration. The annual AI compliance audit passes without findings. Previously, inconsistent anonymization across 12 team members had generated 3 audit findings in the prior year.
Different team members are anonymizing the same document types differently — some replace names, others redact them. How do we enforce consistency?
The Presets System allows compliance managers to create named configurations (e.g., "GDPR Standard," "HIPAA Clinical Notes," "Financial Reports") with per-entity method settings (e.g., replace names, hash SSNs, redact bank accounts). These presets are shared to all Basic+ team members. Built-in compliance presets (GDPR, HIPAA, PCI-DSS, SOX) encode regulatory best practices out of the box, reducing the compliance manager's configuration burden.
We're a managed services provider handling compliance for 50 small businesses. Can we create standardized configurations for our clients and deploy them easily?
Presets can be exported and imported across accounts, enabling MSPs to build a library of compliance configurations (GDPR Starter, HIPAA Safe Harbor, FOIA Standard, etc.) and deploy them to client organizations efficiently. Industry-specific presets (healthcare, legal, financial services) can be built once and shared. This makes anonym.legal an enabling tool for compliance consulting practices. Example: A GDPR consulting firm serves 35 SMB clients in Germany. They've built a "German SMB GDPR Baseline" preset covering the entity types most commonly encountered in their clients' document workflows. Each new client receives this preset on day one of engagement. Configuration time per client drops from 3 hours to 15 minutes. The firm can onboard 4x more clients with the same team.
We just onboarded a new privacy tool — training our team of 20 to use it correctly took 3 weeks. Every time someone doesn't configure it right, we have a compliance incident. Is there a way to reduce configuration errors?
Presets encode the organization's approved configurations as named, shareable objects. New team members are given access to the team's preset library and instructed to use specific presets for specific workflows. The learning curve compresses from weeks to hours. Configuration errors drop because new users apply tested, approved presets rather than configuring from scratch. Institutional knowledge persists even through team turnover. Example: A legal process outsourcing firm onboards 50 new document review staff annually. Previous onboarding required 3 weeks of PII tool configuration training. With presets, new staff are trained in 1 day: "For European documents, use the GDPR Standard preset. For US medical records, use the HIPAA Safe Harbor preset." First-week configuration error rate drops from 22% to 3%. Annual training cost savings: approximately €45,000 in staff time.
Cross-Platform Consistency
We want to use AI coding assistants for our development work but our codebase contains customer data in tests and logs. How do we ensure PII is removed before code goes to AI tools?
The MCP Server integration brings anonym.legal's PII detection directly into Claude Desktop and Cursor AI IDE. Developers can process code files, test data, and log excerpts through the anonymization pipeline before sharing with their AI assistant. Custom entities for internal identifiers (customer IDs, account numbers) work alongside standard PII types. The same engine available in all other contexts means consistent detection whether reviewing code in the IDE or documents in the web app. Example: A SaaS engineering team uses Cursor (AI IDE) for development. After discovering production customer email addresses in unit test fixtures, their CTO mandated PII review before all AI-assisted code review. anonym.legal's MCP Server integration in Cursor enables developers to anonymize test data in-workflow: select file, run anonymization, paste anonymized version to AI assistant for review. Zero new external tools; same anonym.legal account they use for other PII work. Production customer dat
We use different tools for different contexts — one for web, one for desktop, one for Word documents. The results are inconsistent and we can't demonstrate systematic compliance. How do other organizations handle tool fragmentation?
All five platforms run the same detection engine. Presets sync across platforms. Custom entities defined on one platform are available on all. Audit trails show consistent entity detection and anonymization across all platforms used by the organization. A "GDPR Standard" preset applies identically whether a team member uses the web app, the Word add-in, or the Chrome Extension. This provides the systematic, consistent approach that compliance audits require. Example: A compliance consulting firm's 15-person team used 4 different tools: a web scraper tool for online data, a standalone Windows desktop tool for bulk files, a Word macro for legal documents, and a Chrome extension for AI tools. After an ISO 27001 audit finding on "inconsistent data anonymization procedures across platforms," they consolidated to anonym.legal for all use cases. Single vendor, single engine, single audit trail. ISO 27001 finding closed.
I use Claude Desktop for AI work and Microsoft Word for document drafting — I need the same PII detection in both places. Is there a tool that works across both simultaneously?
All five platforms (Web, Desktop, Office Add-in, Chrome Extension, MCP Server) share the same engine and configuration. A user who works in Word (Office Add-in), Chrome AI tools (Chrome Extension), and Claude Desktop (MCP Server) has the same PII protection in all three environments with one subscription and one configuration. Presets configured once apply everywhere. The worker's full workflow is protected by a single consistent tool. Example: A legal researcher uses three tools daily: Microsoft Word for drafting legal opinions, Chrome for researching case law (using Claude via browser), and Claude Desktop for AI-assisted legal research. With anonym.legal's Office Add-in, Chrome Extension, and MCP Server all configured with the same "Legal Research" preset, client names and case references are consistently anonymized regardless of which application they're working in. No workflow interruption, consistent protection, single tool subscription.
We're a remote-first company with team members in the EU, US, and APAC. Data privacy laws differ by region — can one tool handle compliance across all our regions without requiring different tools for each jurisdiction?
260+ entity types with regional variants cover the major global jurisdictions' PII categories. EU data residency satisfies GDPR data sovereignty. Region-specific presets encode different regulatory frameworks (GDPR Standard, HIPAA Safe Harbor, APAC Privacy). All five platforms available globally with the same engine. Cross-border team members use the same tool with jurisdiction-appropriate presets, enabling global compliance from a single vendor. Example: A remote-first SaaS company with 50 employees across Germany (GDPR), California (CCPA/CPRA), and Singapore (PDPA) needed a single PII anonymization solution for their globally distributed customer data operations. Individual regional tools created 3-tool fragmentation and inconsistent compliance posture. anonym.legal with EU data residency, GDPR preset for German team, CCPA preset for California team, and PDPA preset for Singapore team provided consistent global coverage. The company's 2025 privacy audit — covering all three jurisdict
Our team uses different PII tools depending on their workflow — web app, Word plugin, Excel, browser extension. How do we prove consistent compliance in an audit?
The same Microsoft Presidio-based engine (extended to 267 entities, 48 languages) operates in the Web App, Desktop Application, Office Add-in, Chrome Extension, and MCP Server. Configuration presets ensure consistent settings across platforms. The compliance narrative is clean: one engine, five access points, consistent results everywhere.
Some team members work in the office with full tool access; remote workers use web apps. How do we ensure they're applying the same PII standards?
Whether a team member uses the Web App at home, the Desktop App in a secure facility, the Office Add-in in Microsoft 365, or the Chrome Extension on a personal device for approved AI use — all platforms use the same detection engine. Presets synchronized across accounts ensure consistent configuration. The MCP Server provides consistent filtering for all AI tool usage.
Our team members work on different OS — some on Windows, some on Mac, some Linux. Do PII tools work consistently across all operating systems or do we get different results on different machines?
The Desktop App (built on Tauri + Rust) runs natively on Windows, macOS, and Linux with the same underlying engine across all platforms. The web app is OS-agnostic by design. The Chrome Extension works on Chrome across all OS platforms. The MCP Server is OS-agnostic. This ensures that a Windows user and a Mac user processing the same document with the same preset get identical results — OS is not a variable. Example: A global technology company's privacy team operates on Mac (privacy officers), Windows (legal team), and Linux (data engineering team). Their previous PII tool (Windows-only desktop application) meant Mac and Linux users used different web tools, producing inconsistent results. After consolidating to anonym.legal's cross-platform suite, all three teams use the same engine (Desktop App for Mac/Windows/Linux or Web App) with the same presets. Cross-OS compliance inconsistency eliminated; single audit trail covers all team platforms.