HoneyHive
AI observability and evaluation platform for LLM agents; the API returns sessions, events, datasets, experiment runs and metrics.
- Category
- Cloud & Data Platforms
- Type
- LLM observability
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- Access token
02Data
What you can sync.
- Sessions
- Events
- Datasets
- Experiment runs
- Metrics
Load HoneyHive sessions into your Lake and model it in the Warehouse with the rest of your stack.
Need more? Name any other HoneyHive data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- An access token
HoneyHive uses an access token. You add the credentials once, when the AI asks for them, and it tells you where to create them in HoneyHive if you need help.
04How it works
How it works in DataMind.
-
Pick HoneyHive.
Open Lake, pick HoneyHive in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the HoneyHive API docs.
-
Answer a few questions.
The AI reads the HoneyHive documentation, then asks which credentials you will use, which data to sync (for example sessions and events), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then HoneyHive data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
