AI Defense Stack

GenAI data-leak prevention & privacy

Tonic Textual: PII redaction and synthesis tool for free text

Tonic Textual is a PII redaction and synthesis tool for free text from Tonic.ai. It is a commercial product offered as: SaaS, On-prem, API, Library. Pricing model: usage-based.

  • Last reviewed
Visit Tonic Textual (opens in a new tab) Documentation (opens in a new tab)
Commercial Layer 5: Data protection

Best for

Teams preparing free text, documents or call audio for LLM training, RAG or testing that need entity-level redaction or synthetic replacement

Consider instead if

  • You want a free open-source library for PII detection and anonymization that you run yourself. See Presidio.

What Tonic Textual does

Tonic Textual is a commercial service from Tonic.ai that detects sensitive entities in unstructured data such as free text and audio, then redacts them or replaces them with synthetic values. The product page says its models detect common entities out of the box, spanning 50+ languages, and that you can train custom entity types through a UI. It can redact sensitive information before it enters LLM prompts. You can use it as a cloud-hosted service, deploy it on premises with Kubernetes or Docker, or call it through a Python SDK that is MIT licensed. Pay-as-you-go pricing is billed per 1,000 words processed with no amount listed, and Enterprise pricing is custom.

This summary is our own wording of the sourced facts on this page.

Key facts

Each value links to the page that states it, with the date we checked it.

Vendor
Tonic.ai Source, checked October 21, 2026: tonic.ai (opens in a new tab)
Status
Active Source, checked October 21, 2026: docs.tonic.ai (opens in a new tab)
Open source
No: closed source (proprietary) Source, checked October 21, 2026: tonic.ai (opens in a new tab)
Latest release
Not documented in the sources we checked
Deployment
SaaS, On-prem, API, Library Source, checked October 21, 2026: tonic.ai (opens in a new tab)
Pricing model
Usage-based: Pay-as-you-go is billed at a flat rate per 1,000 words processed, with no amount listed. Enterprise is custom pricing with a contact sales button. (as listed on October 21, 2026; check the vendor for current pricing) Source, checked October 21, 2026: tonic.ai (opens in a new tab)
Website
tonic.ai Source, checked October 21, 2026: tonic.ai (opens in a new tab)
Documentation
docs.tonic.ai Source, checked October 21, 2026: docs.tonic.ai (opens in a new tab)
API reference
docs.tonic.ai Source, checked October 21, 2026: docs.tonic.ai (opens in a new tab)
Quickstart
docs.tonic.ai Source, checked October 21, 2026: docs.tonic.ai (opens in a new tab)
Security page
docs.tonic.ai Source, checked October 21, 2026: docs.tonic.ai (opens in a new tab)
Attestations or disclosure
Maintains a SOC 2 report through an independent auditor Source, checked October 21, 2026: docs.tonic.ai (opens in a new tab)

Capabilities

As documented by the vendor or project. The tag is our label from a controlled vocabulary.

Integrations

Where Tonic Textual fits in our AI security layers

Our analysis

Our editorial model, not a standard. The primary layer follows the category, except for tools whose main documented job is detection and response; other layers rest on a capability the sources document. How the model works.

AI security layers that Tonic Textual covers, with the role, how each applies and what it rests on
LayerRoleHow it appliesBased on
L5 Data Data protection Primary Keep sensitive data out of prompts, uploads, retrieval and training data, or remove and tokenize it first. Follows its category, GenAI data-leak prevention & privacy

OWASP LLM Top 10 mapping

Our analysis

The risk list is OWASP's (Top 10 for LLM Applications, 2025). The mapping is our analysis, and each row rests on a capability the sources document.

OWASP LLM risks mapped to Tonic Textual, with the capabilities each mapping rests on
RiskHow it appliesBased on
LLM02 Sensitive Information Disclosure Detects and redacts sensitive entities, including before text enters LLM prompts. Detects common sensitive entities out of the box, with support spanning 50+ languages; Redacts sensitive entities consistently; Redacts sensitive information before it enters LLM prompts

Not mapped in our analysis: LLM07, LLM08. These are risks we expect tools in this category to cover; the sources we checked do not document a matching capability.

Alternatives and related tools

More in GenAI data-leak prevention & privacy, ranked within the category by Coverage Score.

Protecto

Protecto

Commercial
  • SaaS
  • On-prem
  • API

Detects sensitive data and tokenizes or masks it before it reaches LLMs, RAG pipelines and agents.

Best for: Teams that want an API that tokenizes or masks sensitive data before it reaches LLMs and RAG pipelines and restores it afterwards

Coverage Score 70 out of 100
  • LLM02 Sensitive Information Disclosure
  • LLM08 Vector and Embedding Weaknesses

Reviewed

Presidio

Data Privacy Stack

Open sourceMIT
  • Library
  • Self-hosted

Finds and masks personal data in text, images and structured data, and you run it yourself.

Best for: Engineering teams that want a free, self-hosted library to detect and anonymize PII before text reaches a model or a log

Coverage Score 67 out of 100
  • LLM02 Sensitive Information Disclosure

Reviewed

Limina (Private AI)

Limina

Commercial Freemium Now Limina
  • Self-hosted
  • On-prem
  • API

Detects PII, PHI and PCI in text, files, images and audio in a container you run in your own environment.

Best for: Teams that need PII, PHI and PCI de-identification of text, files and audio that runs inside their own VPC or on-premises

Coverage Score 64 out of 100
  • LLM02 Sensitive Information Disclosure

Reviewed

Tonic Textual FAQ

Is Tonic Textual open source?

The Python SDK in the TonicAI/textual repository is MIT licensed. The platform itself is commercial, and we found no public source repository for it.

Is there a free trial?

The getting-started guide says the free trial scans up to 100,000 words, after which a pay-as-you-go subscription is needed to add files to a dataset.

Where can Textual run?

The product page describes a cloud-hosted service and an on-premises deployment that uses Kubernetes or Docker.

Key facts you can cite

We have no commercial relationship with Tonic.ai.

Sources & last reviewed

Last reviewed . We compile from the vendors' own public pages and repositories and we do not run the products. Source links open in a new tab. Found a mistake? Report a correction.