Azure AI Language
Sentiment analysis with Azure AI Language (API-key auth).
OCNORA ships 1 typed Azure AI Language operation. Each node has a schema-driven form, input and output tables beside its settings, and is pre-flighted by Workflow Health before your first real run.
Before you connect Azure AI Language
- Authentication
- API key
- Credential
- the Azure AI Language API key
- Connection test
- Available: the stored credential can be checked against the provider when you add it. This is not a record that a test was run or passed.
What you can do with Azure AI Language
Operations, grouped by what they do to your data.
Other operations 1
A sample Azure AI Language workflow
- 1A core triggerStart the run from a chat, form, manual, schedule, webhook, workflow trigger — no Azure AI Language trigger is needed.
- 2Analyze Sentimentazure_language.analyze_sentimentClassify the sentiment of text with Azure AI Language.
An outline built from this provider’s node contracts, not a recorded run. Each step’s output fields are available to the next in the field picker.
Every node below has a reference page: what it does, the connection it needs, its config fields with types, constraints and examples, and the shapes it emits.
Azure AI Language questions
- How does OCNORA authenticate with Azure AI Language?
- With a stored API key credential, shaped the Azure AI Language API key. A connection test can check it when you add it.
- What can I automate with Azure AI Language?
- 1 typed operation, each with a reference page listing its config fields and the shapes it emits.
- What if the Azure AI Language operation I need is not listed?
- Where Azure AI Language has an HTTP API, call it from the HTTP node with the same credential, or describe the step to the AI builder, which asks our team for a typed node when one is missing.
- Are there templates that use Azure AI Language?
- Not yet. Start from a blank workflow, or describe the workflow to Build with AI.
- How are Azure AI Language calls controlled?
- Every call and every run step is audited, runs count against the execution budget, and Workflow Health pre-flights the workflow when you save it.
See your first Azure AI Language workflow run.
Book a technical demo. We add the connection, pick a template or describe the workflow to Build with AI, and Workflow Health checks it before it runs.