OpenAI / GPT + Areebi

Areebi provides a complete governance layer for OpenAI's GPT models, enabling organisations to use GPT-4o, GPT-4, and the full OpenAI model family with enterprise-grade security and compliance controls. Every prompt sent through Areebi is scanned by the DLP engine in real time, ensuring sensitive data such as PII, PHI, financial records, and proprietary code never reaches OpenAI's API without being redacted or blocked according to your organisation's policies.

Unlike direct OpenAI API access, Areebi acts as a governed proxy that sits between your users and the model. This means your security team retains full visibility into how GPT models are being used across the organisation - who is prompting, what data is being shared, and which models are being accessed - without slowing down the end-user experience. The integration supports all OpenAI capabilities including function calling, embeddings generation, fine-tuned model access, and multimodal vision inputs.

For teams already using OpenAI, Areebi requires no changes to existing workflows. Users interact with GPT models through Areebi's workspace interface, and administrators manage governance policies from a centralised policy builder. API keys are stored securely at the platform level, never exposed to individual users, eliminating the risk of key leakage or misuse.

Areebi's governance layer for OpenAI covers three critical areas: data loss prevention, audit logging, and policy enforcement. The DLP engine inspects every prompt and response in real time, applying over 50 built-in detectors for PII categories including names, email addresses, phone numbers, Social Security numbers, credit card numbers, and medical record identifiers. Custom detectors can be configured for organisation-specific data patterns such as internal project codes or proprietary terminology.

Audit logging captures the full lifecycle of every interaction - the user identity, workspace, timestamp, model selected, token count, prompt content (or a redacted version per policy), and the response. These logs are immutable, tamper-evident, and exportable to your SIEM or compliance tooling. For organisations pursuing SOC 2 or HIPAA compliance, the audit trail provides the evidence required for AI usage controls.

Policy enforcement allows administrators to define granular rules: which user groups can access which models, maximum token budgets per user or department, permitted use cases, and blocked prompt patterns. Rate limiting prevents runaway costs, and cost allocation tags every API call to a user and workspace for accurate chargeback reporting. These controls are configured through Areebi's policy builder and apply instantly without redeployment.

Using OpenAI in regulated industries requires careful attention to data residency, retention, and access controls. Areebi helps organisations meet these requirements by ensuring sensitive data is intercepted before it reaches OpenAI's infrastructure. For healthcare organisations subject to HIPAA, Areebi's PHI masking ensures that protected health information is never sent to the model in identifiable form.

For financial services and legal teams, the audit trail provides a defensible record of AI usage that satisfies examiner and regulator inquiries. Combined with workspace isolation, organisations can create separate environments for different business units, each with tailored governance policies - a strict configuration for legal, a more permissive one for marketing, all managed from one console.

Areebi's trust centre provides documentation of all security controls, and the platform undergoes regular third-party penetration testing. To see how Areebi's governance layer works with your OpenAI deployment, request a demo or review our pricing plans.