FAQ
Quick answers to the most frequent HiveFlow questions: keys, models, exporting, teams, API access, unsupported services, languages and failures.
Short answers with pointers to the full guides.
Do I need my own AI provider API keys?
No. Managed by HiveFlow providers work out of the box and bill in credits. You can bring your own keys — see BYOK.
Which models does HiveFlow support?
Models from OpenAI, Anthropic, Gemini, Google Vertex, Azure OpenAI, AWS Bedrock, Groq, Mistral, HuggingFace, Friendli and Perplexity — selectable per LLM node, so different steps can use different models.
Can I self-host HiveFlow?
Not today — HiveFlow is a cloud platform (app.hiveflow.ai). The pieces that run on your machines are the desktop device agents.
Are Agents different from flows?
No — an Agent is a flow with the pattern chat_input → llm → chat_output, plus a chat UI, sessions, tasks and reminders.
Can I export my flows?
Yes: Export in the editor toolbar produces a JSON you can re-Import anywhere (including another account).
Does HiveFlow have an API?
Yes — a full REST API with an OpenAPI 3.0 spec. Start at the API guide; triggering a flow is one curl away.
How do I integrate a service you don't list?
Use Generic MCP to register any MCP server package with its env vars — see Connecting integrations.
What languages does HiveFlow speak?
The dashboard and this documentation are available in English and Spanish. Your agents speak whatever languages their model supports.
How do I work with my team?
Create an organization: members, roles and permissions, workspaces and team billing.
What happens when a node fails?
The run marks the node red; its Console has the error. Wrap risky branches with Error Handler and see Troubleshooting.
How do I control spending?
Watch Analytics for expensive flows, choose cheaper models per node, and rely on plan limits — execution and LLM-call caps are per month.
Where do I report bugs or ask for help?
The community Discord, or ask Genius to open a support ticket from inside the app.