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Ethyca Fides

ethyca.com

Free plan WebWindowsmacOSLinuxAPISelf-hosted

What it is

Ethyca Fides is an open-source privacy engineering toolkit for governing data categories, purposes, and use cases across fragmented systems. It turns regulatory obligations into machine-readable definitions that can be enforced within infrastructure. APIs and tooling connect Fides to development workflows, where teams can classify and authorize data entering AI training and inference pipelines. A sample deployment provides a webserver and Admin UI for privacy requests, a Privacy Center, and an example e-commerce project. The Cookie House sample uses MongoDB and Postgres; listed integrations also include Salesforce, Shopify, Segment by Twilio, Google Analytics, Slack Enterprise, and Zendesk. Local setup requires Python 3.8–3.10 and Docker 20.10.11 or higher. Fides is free and supports data inventory, automated discovery, privacy requests, and retention management. It is listed for API, Linux, macOS, self-hosted, web, and Windows environments, with hybrid deployment. The onboarding guide points users who need setup help to the Fides Slack community.

Spec sheet

Purpose
Fides defines a shared ontology for data categories, purposes, and use cases to govern data across fragmented systems.Read 3 Oct 2026 · ethyca.com
Intended users
Ethyca says Fides is built for developers and identifies engineers and data scientists as teams that need tools to operationalize privacy.Read 3 Oct 2026 · ethyca.com
Security
Ethyca describes its security protections as enterprise-grade, but the security page’s detailed control descriptions contain placeholder text.Read 3 Oct 2026 · ethyca.com
Support
The onboarding guide directs users who need setup help to the Fides Slack community.Read 3 Oct 2026 · ethyca.com
Headquarters
New York, New York, United StatesRead 28 Sep 2026 · ethyca.com
Founded
2018Read 28 Sep 2026 · ethyca.com
AI governance
Fides integrates with development workflows through APIs and tooling to classify and authorize data entering AI training and inference pipelines.Read 3 Oct 2026 · ethyca.com
Company history
Ethyca says it was founded in 2018 to operationalize GDPR as code and released Fides 1.0 in 2021.Read 3 Oct 2026 · ethyca.com
Database integrations
The sample Cookie House project uses MongoDB and Postgres databases managed through Fides.Read 3 Oct 2026 · ethyca.com
Hosted service terms
Ethyca’s hosted Fides agreement says service fees are specified in an Order Form and support and maintenance obligations are generally the customer’s responsibility, subject to the agreement.Read 3 Oct 2026 · ethyca.com
Install requirements
The onboarding guide specifies Python versions 3.8–3.10 and Docker version 20.10.11 or higher to run Fides locally.Read 3 Oct 2026 · ethyca.com
Open source
Ethyca describes Fides as an open-source privacy engineering standard that teams can inspect and contribute to.Read 3 Oct 2026 · ethyca.com
Other integrations
Ethyca lists integrations including Salesforce, Shopify, Segment by Twilio, Google Analytics, Slack Enterprise, and Zendesk.Read 3 Oct 2026 · ethyca.com
Policy enforcement
Fides translates regulatory obligations into machine-readable definitions that can be enforced within infrastructure.Read 3 Oct 2026 · ethyca.com
Privacy requests
The Fides sample deployment includes a webserver and Admin UI for administering privacy requests, a Privacy Center, and a sample e-commerce project.Read 3 Oct 2026 · ethyca.com

Plans and prices

Fides Free Open-source privacy engineering toolkit Read 3 Oct 2026 · ethyca.com

Every Ethyca Fides plan and price →

Strong points and limits

Strong points

  • Open-source toolkit teams can inspect and contribute to
  • Translates obligations into enforceable machine-readable definitions
  • Connects privacy controls to AI workflows
  • Includes a sample Admin UI and Privacy Center
  • Free to use

Limits

  • Local setup requires Python 3.8–3.10
  • Docker 20.10.11 or higher is required
  • Setup help is directed to the Fides Slack community

Who it suits

Fides suits developers, engineers, and data scientists who need to operationalize privacy in infrastructure and AI workflows. Local users need compatible Python and Docker versions.

Ethyca Fides in depth

Read the full write-up

Overview

Ethyca Fides is an open-source toolkit for putting privacy rules into data infrastructure and development workflows. It suits engineering teams that can work directly with those systems. Its appeal is an inspectable foundation for privacy controls; running it locally requires specific software and setup help is community-based.

Key features

Fides gives teams a shared way to describe data categories, purposes, and use cases across fragmented systems. It can turn regulatory obligations into machine-readable definitions for enforcement in infrastructure. That makes it a practical choice when privacy rules need to affect how systems use data, but less suitable for organizations looking mainly for a policy-documentation workspace.

APIs and tooling bring data classification and authorization into AI development workflows, covering data entering training and inference pipelines. This can help engineers and data scientists operationalize privacy as data moves toward AI use. The open-source standard can be inspected and contributed to, an advantage for teams that want visibility into the approach and the ability to participate in its development.

The sample deployment includes a webserver and Admin UI for privacy requests, a Privacy Center, and a sample e-commerce project. That project uses MongoDB and Postgres databases managed through Fides. Other listed integrations include Salesforce, Shopify, Segment by Twilio, Google Analytics, Slack Enterprise, and Zendesk. The sample makes the product’s privacy-request workflow concrete, though the setup still calls for engineering involvement.

Pricing

The Fides plan costs nothing and is described as an open-source privacy engineering toolkit. It is the fit for teams that want to inspect and run the toolkit without a plan fee. The free plan does not remove the operational work: local use requires Python 3.8–3.10 and Docker 20.10.11 or higher, and setup guidance points users to the Fides Slack community.

Ethyca also has a hosted Fides agreement. Service fees are specified in an Order Form, and support and maintenance obligations are generally the customer’s responsibility, subject to the agreement. Teams considering that arrangement should account for those responsibilities rather than assume the hosted service includes support obligations from Ethyca.

Platforms

Fides supports API, Linux, macOS, self-hosted, web, and Windows platforms. Its deployment model is hybrid, giving technically capable teams a choice that includes local and hosted use. The specified local requirements make it a more natural fit for teams able to manage a Python and Docker environment than for users seeking a setup-free application.

Who it's for

Fides is built for developers, with engineers and data scientists called out as teams that need to operationalize privacy. It is strongest for organizations connecting privacy policy to data systems and AI pipelines. A team without engineering capacity, or one wanting setup assistance beyond a community channel, may prefer a more guided privacy-management product.

Pros and cons

Inspectability: The open-source standard can be examined and contributed to, useful for teams that want visibility into their privacy engineering foundation.

Policy enforcement: Machine-readable definitions can carry regulatory obligations into infrastructure rather than leaving them only as written policy.

AI workflow coverage: APIs and tooling address data entering training and inference pipelines, relevant to engineers and data scientists building AI workflows.

Setup burden: Local use requires particular Python and Docker versions, and setup help is directed to a Slack community.

Security assurance: Ethyca describes protections as enterprise-grade, but detailed control descriptions contain placeholder text, limiting how much the security claims can establish.

Alternatives

For a broader set of options, browse Data Privacy Management Software.

DPDP.ai offers a free cookie-consent tier with 10,000 consents per month, no credit card, no trial expiry, and no feature restrictions; choose it when that consent-management allowance is the priority.

DataShyre has a free tier capped at 500 unique users for cookie banners and consent management, plus a Starter plan at $99 a month; choose it when those consent controls and a defined user cap match the need.

PrivacyEngine runs on the web and has free plans with caps including five staff and five records in several compliance categories; choose it when a capped compliance workspace is preferable to an engineering toolkit.

ComplyDP offers a free 10-control diagnostic scan with a compliance score, risk rating, identified gaps, and shareable report; choose it for a quick diagnostic rather than ongoing infrastructure controls.

dcomply is built and operated by Decipher Consultancy Services, established in Noida, Uttar Pradesh in 2014.

Nonym has a free non-commercial self-hosted Community plan with community support, and a Cloud plan at $49 a month plus $0.50 per 10K requests; choose it when those terms suit the deployment.

Relyance AI is a paid option with a free trial for teams comparing commercial products.

EasyDP has a free plan capped at 100 new customers per month, 1,000 total customers, and one user, plus a Starter plan at ₹299 a month; choose it when those customer limits and pricing fit.

Verdict

Choose Fides if your engineers or data scientists need an inspectable, open-source way to bring privacy controls into data and AI workflows. Its strongest reason to choose it is that policy can become machine-readable infrastructure enforcement. Look elsewhere if your team needs a more guided setup or stronger, detailed security-control assurances.

Verdict

Fides offers a free, inspectable toolkit for teams implementing privacy controls in systems and development workflows. Its local runtime requirements and community-based setup guidance are important considerations.

Where Specifiction places it

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