CherryIN
AIReach CherryIN's multi-provider model catalog through one OpenAI-compatible connection. Agents switch models without rewriting the flow or adding another credential.
What This Integration Enables
CherryIN is narrow on purpose, and the narrowness is the point. It exposes two operations, and both send text to a model. What it actually sells is the account underneath: one key, one plan, one invoice, and access to Claude, Gemini, GPT, DeepSeek, and other providers behind a single OpenAI-compatible interface. Model IDs take a provider/model form, so the vendor is visible in the value your flow carries rather than buried in a connection setting.
The detail worth knowing before you build on it is that CherryIN's model picker reads the models your key is entitled to, not a global catalog. That is a better default than a marketing list, because the picker cannot offer a model the plan does not cover. It also means the roster moves when your plan moves. Build for that and the connectors in your flows stay honest about what they can call. Ignore it and you find out through a failed request in a customer-facing path.
One more thing that will bite if nobody tells you: OpenAI's GPT-5.x series does not accept chat completions requests. Those models go through Create Model Response, which takes a plain text input instead of a messages array. Same key, same account, different action.
Without FlowRunner
With FlowRunner
Use Case Scenarios
Provider consolidation without a rebuild
A team has four flows, each calling a different vendor directly, each with its own key sitting in a different place. Migrating them to CherryIN replaces four credentials with one and leaves the flow logic where it is, because the request shape is OpenAI-compatible in every case. The model ID moves from a hard-coded string in each flow to a value the flow reads, which means the next vendor change is a field edit rather than a project.
Cost tiering inside one flow
An inbound email triage flow does not need the same model for every step. The agent uses a small, cheap model to classify intent and detect language, then routes only the messages that need drafting to a stronger model, then writes the result into HubSpot. Both calls go through Create Chat Completion against the same key. The tiering is a decision in the flow, not a second contract.
Adopting a GPT-5.x model without breaking the existing path
A summarization step is moving to a GPT-5.x model. Because that series does not accept chat completions requests, the agent branches: the new model runs through Create Model Response with a plain text input, and the previous model stays on Create Chat Completion until the new output has been checked against the old on real traffic. The team compares the two in Notion before retiring the original branch.
Human-in-Loop Highlight
The moment this connector needs a person is entitlement drift. Because the picker reflects what your key can call rather than a fixed catalog, a plan change or a roster change on CherryIN's side can remove the exact model a live flow depends on. An agent that quietly substitutes the nearest available model has just changed the voice, the refusal behavior, and the policy posture of every customer-facing message that flow produces, and nobody approved that. So the agent does not substitute. When a referenced model stops appearing in the entitled list, it holds the affected flows and asks the owner in Slack: "The customer reply flow calls anthropic/claude-sonnet-4.5, which is no longer in this key's entitlement. Three flows are affected and are paused. Which model should replace it, or should the plan be restored?" A person names the replacement, the agent resumes, and no customer receives a message from a model that was never chosen for them. That is human-in-the-loop doing the job it exists for: the agent knows the boundary of what it is allowed to decide.
Agent Capabilities
2 actionsChat Completions
1- Create Chat Completion Sends a conversation to any model your CherryIN key is entitled to, through an OpenAI-compatible interface covering Claude, Gemini, GPT, DeepSeek, and other providers. Supply a Prompt for single-turn work or a full Messages array to carry multi-turn context. This is the default path for every model except OpenAI's GPT-5.x series, which requires Create Model Response instead.
Responses
1- Create Model Response Sends a single text input to a model through the CherryIN Responses endpoint and returns its reply. This is the endpoint OpenAI's GPT-5.x series requires, since those models do not accept chat completions requests. It takes plain text rather than a messages array, so a step moving to a GPT-5.x model changes action as well as model ID.
Frequently Asked Questions
What can FlowRunner do with CherryIN?
FlowRunner agents can run Create Chat Completion and Create Model Response in CherryIN.
Does connecting CherryIN to FlowRunner require OAuth?
No. CherryIN connects to FlowRunner with an API key, no OAuth flow required.
Can CherryIN trigger a FlowRunner workflow automatically?
CherryIN doesn't currently expose triggers in FlowRunner. It connects as an action step inside workflows started by another trigger.
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