Cohere in AGNT
Enterprise-focused models with first-class RAG. Every AGNT workflow is provider-portable, so the same agents run here or anywhere else you point them.
Why teams pick it
Models
- Command R+
- Embed
- Rerank
Strengths
- retrieval-optimised stack
- enterprise deployment options
- strong embeddings
In AGNT
Agents, workflows and tools use Cohere like any other provider — same nodes, same receipts, swap models per step if you want.
Retrieval as a first-class product
Cohere is unusual in treating the whole retrieval stack — embeddings, reranking and generation — as one coherent offering rather than a generation model with retrieval bolted on. For teams whose main problem is answering accurately over a large private corpus, the rerank step in particular is often a bigger quality win than changing the generation model.
What to watch
The enterprise focus shows in deployment options and support rather than in leaderboard positions, which is exactly the right trade for some organisations and irrelevant for others. If your workload is not retrieval-shaped, the differentiator largely does not apply.
Using Cohere in a workflow
In practice you rarely commit a whole workflow to one model. A common arrangement puts Command R+ on the steps where retrieval-optimised stack genuinely decides the outcome, and something cheaper and faster on the routine classification around it. Because AGNT normalises tool calling, that split is configuration per step rather than two separate builds.
Connect Cohere in two minutes
- Download AGNT Community Core — free, local-first, no account needed to run.
- Open Settings → Providers, choose Cohere, and paste your API key. Connect by pasting an API key into AGNT’s vault — stored encrypted on your machine, never uploaded.
- Give an agent a job — or install one from the marketplace — and watch the first receipt come back.
Cohere in AGNT — common questions
What does a reranker actually do?
It reorders retrieved candidates by true relevance before they reach the model, which usually improves answers more than a larger generation model would.
Is Cohere a good fit for RAG?
It is one of the more complete stacks for it, since embeddings, reranking and generation are designed together.
Does AGNT support Cohere embeddings?
Yes — retrieval steps can use Cohere alongside any other provider in the same workflow.