AI workflows · Local / self-hosted
Ollama Local for B2B teams
Run a model locally to experiment with a repeatable text task on your own hardware.
By Ollama · Plan information checked 2026-10-12
A practical example
Technical teams exploring local draft classification or structured extraction.
When to choose something else
Assuming local deployment automatically guarantees security, accuracy or suitability for confidential data.
Your first useful workflow
Step 1
Check hardware requirements and the model’s commercial-use licence.
Step 2
Run a small non-sensitive example through a narrowly defined task.
Step 3
Compare output with manually labelled examples and document errors before considering a live workflow.
How to know the setup works
The chosen model fits the machine and meets a defined accuracy threshold on your examples. Keep a human fallback.
Compare before adding another subscription
Compare the job, required access, data handling and the cost of your expected volume. Two tools solving the same job often create more work.
All ai workflows tools ↗Make the tool part of a working system.
Tool choice is one decision. Ownership, measurement and follow-up make it useful.
Explore the related capability ↗Talk through your setup ↗