Enterprise privacy at OpenAI
The primary source: API data is not used for training by default, with retention controls explained.
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Is it safe to send customer data to AI APIs, and what about privacy laws like India's DPDP Act?
The major API providers (OpenAI, Anthropic) do not train on your API data by default and offer short or zero retention, so the common fear is mostly solved by reading the actual policies and signing the right agreement. Your real risks are elsewhere: prompt injection and data leakage in your own app (see the OWASP LLM Top 10), and your legal duties as a data fiduciary under India's DPDP Act or GDPR, including consent, purpose limitation, and deletion. Minimise what you send, redact PII where you can, and put your provider's terms in your own privacy policy.
Go deeper
18 resources.
Data controls in the OpenAI platform
The developer-facing detail on what is stored, for how long, and how to reduce it.
Open developers.openai.com →How your data is used to improve model performance
The policy to quote when a customer asks whether their data trains the model.
Open openai.com →Is my data used for model training? (Anthropic Privacy Center)
Anthropic's equivalent answer, including the commercial-products carve-out.
Open privacy.claude.com →API and data retention (Claude docs)
Covers the 7-day default retention and zero-data-retention arrangements.
Open platform.claude.com →Anthropic's Transparency Hub
Where to pull compliance artifacts when an enterprise customer sends a security questionnaire.
Open anthropic.com →OWASP Top 10 for LLM Applications, explained
The ten security risks unique to LLM apps, with prompt injection at number one.
Open aembit.io →OWASP Top 10 LLM: Examples and Mitigation Strategies
Concrete examples of each attack and the layered defences OWASP recommends.
Open oligo.security →OWASP LLM Top 10 red-teaming with Promptfoo
Automatically probe your own app for injection and PII leaks before attackers do.
Open promptfoo.dev →Deep Dive into OWASP LLM Top 10 and Prompt Injection
A practitioner's walkthrough of how injections actually happen in RAG and agent apps.
Open paulmduvall.com →Compliance Blueprint for AI Startups and SMEs: DPDPA 2023 and DPDP Rules 2025
A startup-sized DPDP compliance checklist from an Indian privacy consultancy.
Open tsaaro.com →DPDP Handbook for AI Developers
One of India's top tech law firms translating DPDP obligations for AI builders specifically.
Open ikigailaw.com →How To Comply With Final DPDP Rules For Agentic AI
The 2025 final rules applied to AI products, including the significant data fiduciary trap.
Open protecto.ai →India in focus: Data protection and AI in India
A global law firm's view for founders serving both Indian and international customers.
Open reedsmith.com →AI Training Data under India's DPDP Regime
Covers the hard problem: deleting a user whose data is baked into model weights.
Open khuranaandkhurana.com →OpenAI Data Retention Policy: Does OpenAI Train on Your API Data?
An independent plain-English summary to cross-check the official policies.
Open meetily.ai →LLM and data privacy: are they training on your data?
Compares training and retention defaults across providers in one table.
Open spartner.software →OWASP Top 10 for LLM Applications: A Quick Guide
The fast version of the OWASP list for a founder who needs the gist today.
Open mend.io →Terms in this answer
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