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AndiIndia
Transparency

Data Policy

A plain-language, field-by-field summary of how AndiIndia handles inference data.

Last updated: June 21, 2026

FieldPolicy
Prompt retentionNot retained by default

Prompts (text inputs) are processed transiently in memory to serve a request and are not written to durable storage. During active debugging or incident investigation, limited content may be captured temporarily under access controls and deleted promptly afterwards (within 7 days).

Completion retentionNot retained by default

Generated completions are returned to the caller and are not persisted for analytics, evaluation, or training, except for limited, temporary capture during active debugging (deleted within 7 days).

Training usageNever

Customer prompts and completions are never used to train, fine-tune, re-train, or evaluate models, and are not added to any training corpus, benchmark, or dataset.

Primary inference regionIndia

Inference is served from GPU-backed infrastructure located in India. Certain supporting services (such as DNS, CDN, TLS termination, and monitoring) may process limited request metadata in other regions.

Operational logsUp to 30 days

Minimised request metadata (timestamps, model id, token counts, status codes, latency) is retained for up to 30 days for reliability and abuse prevention (unless a longer period is required by law), then deleted or aggregated into non-identifying statistics.

Data deletionOn request

You can request deletion of account-associated data at any time, subject to legal retention obligations.

Sale of dataNever

We do not sell, rent, or trade personal or customer data to any third party.

Scope

This Data Policy gives an explicit, field-by-field account of how AndiIndia handles data processed through the inference API. It is intended to give partners, marketplaces, and customers verifiable answers, and it complements our Privacy Policy and Terms of Service. Where there is a conflict on a data-handling specific, this page governs.

Definitions

  • Prompt / input: the text content and parameters you send to a model.
  • Completion / output: the content a model generates in response to a prompt.
  • Operational metadata: non-content information about a request, such as timestamps, model id, token counts, status codes, and latency.

Training and model improvement

We do not use customer prompts or completions to train, fine-tune, re-train, or evaluate any model, and we do not share such content with third parties for those purposes. Model improvements come from publicly available or properly licensed datasets, never from customer traffic.

Retention

By default, prompt and completion content is not persisted after a response is returned, and we do not maintain content logs of inference traffic. The only exception is limited, temporary capture during active debugging or incident investigation, which is access-controlled and deleted promptly afterwards (within 7 days).

Operational metadata (described above) is retained for up to 30 days for reliability, billing reconciliation, and abuse prevention, unless a longer period is required by law, after which it is deleted or aggregated into non-identifying statistics.

Regional processing and residency

Inference is served from infrastructure located in India, which supports data-residency needs for customers who require in-region model processing. Certain supporting services that are necessary to operate and protect the platform - such as DNS, content delivery (CDN), TLS termination, and monitoring - may process limited request metadata outside India. Prompt and completion content is processed by the inference infrastructure in India.

Subprocessors

We use a minimal set of infrastructure subprocessors (such as cloud GPU and hosting providers) strictly necessary to operate the Services. They are bound by confidentiality and security obligations and may not use customer data for their own purposes.

Security

We apply encryption in transit, access controls, the principle of least privilege, and monitoring appropriate to the sensitivity of the data. Access to systems is restricted to authorised personnel on a need-to-know basis.

Abuse prevention

To keep the platform safe and reliable, we may process operational metadata and apply automated safeguards to detect and prevent abuse, fraud, and security threats. These safeguards operate on metadata and signals rather than on retained content.

Requests and contact

For data deletion, residency, or processing questions, contact support@andiindia.in. We respond to verified requests within a reasonable period. See also our Privacy Policy and Terms of Service.