The outcome
Use the platform productively without giving it unnecessary access or authority.
Cohere is a enterprise language model, embedding, reranking, and retrieval platform. Building enterprise text generation and retrieval systems with Chat, multilingual embeddings, semantic Rerank, tool use, and grounded generation. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.
Before you begin
Set the boundary before the tool starts.
Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.
AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.
Step by step
A workflow you can repeat.
- 01
Classify the task and its data before uploading or connecting anything.
- 02
Review the current product, account, organization, retention, and training settings that apply to you.
- 03
Grant the narrowest file, repository, workspace, microphone, screen, or integration permissions needed.
- 04
Remove secrets and personal or regulated information unless your approved policy explicitly permits it.
- 05
Review the output and revoke permissions or disconnect sources that are no longer needed.
Working standard
What good use looks like.
- Generated text and semantic rankings can be wrong, biased, or insufficiently grounded. Protect API keys, minimize sensitive context, preserve document permissions and identity, use the correct embedding input types, validate response and citation support, evaluate multilingual and adversarial cases, and monitor model versions, rate limits, billed units, and production-key usage.
- Follow your organization’s approved-use policy.
- Never treat fluent output as authorization to act.
Generated text and semantic rankings can be wrong, biased, or insufficiently grounded. Protect API keys, minimize sensitive context, preserve document permissions and identity, use the correct embedding input types, validate response and citation support, evaluate multilingual and adversarial cases, and monitor model versions, rate limits, billed units, and production-key usage.
Official references
Check the current product documentation.
Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.