Cohere Integration Overview
Areebi integrates with Cohere to govern the full retrieval-augmented generation lifecycle - from embedding documents with Embed v3, to reranking search results, to generating responses with Command R+. Cohere's platform is purpose-built for enterprise search and RAG, which makes governance more complex than a simple prompt-response model. When a user query triggers a RAG pipeline, sensitive data can enter the system at multiple points: the original query, the retrieved documents, the reranked context, and the generated response. Areebi's DLP engine inspects each stage, ensuring that PII, PHI, and proprietary data are caught regardless of where they surface in the pipeline.
Cohere differentiates itself with a strong privacy stance - the company does not train on customer data by default and offers single-tenant deployment options. Areebi complements this by adding organisation-specific controls that Cohere's platform does not provide: per-user audit trails, workspace-level isolation between departments, custom DLP rules for industry-specific data patterns, and granular model access policies. A legal team using Command R+ for contract analysis operates in a different workspace from a marketing team using Embed v3 for content search, each with governance rules tailored to their data sensitivity.
The integration supports all Cohere model families through a single configuration in Areebi's admin console. API keys are encrypted at rest and managed centrally. Cohere's RAG connectors - which pull documents from external sources like databases, web crawlers, and file stores - are governed by Areebi's connector-level access policies, so administrators control which data sources feed into which workspaces.
Governance Capabilities for Cohere
RAG governance is fundamentally different from governing a simple chat model. When a user asks a question, Command R+ retrieves relevant documents, reranks them, and weaves the context into its response. Sensitive data can leak at any point in this chain. Areebi addresses this with pipeline-aware governance: the DLP engine scans the user's original query, the retrieved document chunks, and the final generated response as separate inspection points. If a retrieved document contains a customer's Social Security number, Areebi catches it before it is injected into the prompt context - not after it appears in the model's output.
Audit logging for Cohere interactions captures the full RAG lifecycle. Each log entry records the user identity, the query, which documents were retrieved and from which connector, the rerank scores, and the final response. This level of detail is essential for SOC 2 audits where organisations must demonstrate not just that AI responses were logged, but that the data sources feeding those responses were authorised and tracked. For HIPAA-regulated environments, the audit trail proves that protected health information was intercepted at the retrieval stage, not merely at the output stage.
Governing Embeddings and Vector Data
Embed v3 generates vector representations of text that persist in vector databases long after the original API call. Areebi logs every embedding request with metadata about the source content, workspace, and user who initiated it. This creates a chain of custody for vector data - critical when an organisation needs to prove which documents were embedded, when, and by whom. If a data retention policy requires purging certain records, the audit trail identifies exactly which embeddings correspond to the affected content.
Compliance Considerations
Cohere's enterprise data policies are among the strongest in the industry: no training on customer data, SOC 2 Type II certification, and options for single-tenant deployment. Areebi layers additional compliance controls on top of this foundation. For organisations handling protected health information, Areebi's PHI masking ensures that medical records, patient identifiers, and clinical terminology are redacted before reaching Cohere's API, regardless of whether they appear in the user query or in documents retrieved by RAG connectors. This is particularly important for healthcare organisations using Cohere's search capabilities to query clinical knowledge bases where HIPAA obligations extend to the retrieval layer.
Financial services teams benefit from Areebi's connector-level governance. When Cohere's RAG connectors pull data from internal databases or document stores, Areebi enforces access policies that mirror your organisation's existing data classification. A junior analyst cannot trigger a RAG query that retrieves board-level financial documents, even if the underlying vector database contains those embeddings. Combined with workspace isolation, Areebi ensures that each business unit's RAG pipeline operates within defined data boundaries. Visit the trust centre for security documentation, or request a demo to see RAG governance in action with your Cohere deployment. Review pricing for plans that include connector-level policy controls.