Use the API

Create an API key

To obtain an API key to use with your Fastino model, log in to the Fastino platform. Once logged in, navigate to the "Keys" section on the sidebar. From this section, you can create keys as needed to suit your requirements.

The ID visible in your account is not the API key itself; it is merely an identifier. Store your keys in a safe place, you will not be able to retrieve them again after creating.

When generating a new API key please wait for 60 seconds for the key to propagate

Create a model key

Set up a custom API endpoint

To get the most out of your model, we recommend setting up a custom endpoint. This ensures consistent, high-quality outputs without having to re-specify prompts or schemas on every API call. It also helps us understand your use case and optimize future model versions for your needs.

To set up an endpoint:

1. Navigate to the Models screen and click Create Endpoint for the model you'd like to use

2. Describe your use case – Explain what you’re trying to accomplish with the model.

3. Define the expected output – Add entities, classification labels, structured output schemas, or function signatures depending on the model type.

4. Provide few-shot examples – Show representative inputs to help guide the model’s behavior.

5. Review auto-generated outputs – Accept or refine them to improve alignment.

6. Confirm your setup – Finalize the configuration to create your reusable, purpose-built endpoint.

Call the API

Fastino's inference API is designed to provide a seamless integration for deploying and running AI models with ease. With a simple POST request to the endpoint https://api.fastino.com/run, users can efficiently execute their AI models in real-time. The API requires standard authentication, utilizing a bearer token for security, and operates with a straightforward JSON payload that includes essential user details. Suitable for a wide range of AI applications, Fastino's platform ensures quick and reliable model inference, making it an ideal solution for developers looking to leverage powerful AI capabilities into their applications effortlessly.

Endpoint

POST https://api.fastino.com/run

Headers

Name	Value
x-api-key	Your API key generated on the platform (see Create an API key)
Content-Type	application/json

Body

Name	Type	Description
model_id	string	Unique identifier for the model. This value can be copied from the Endpoints screen on the platform UI.
input	array of objects	An array where each object represents a single model inference call. For PRO and TEAM plans, multiple objects can be included to perform batch inference in a single request.
input > text	string	The text being processed by the language model
input > parameters	object	The parameters specifying how the model should process the text. Parameters vary depending on the expected input format of the specific model being used. If not specified, the inference parameters default to the parameters that were specified when setting up your custom endpoint (see Set up a custom API endpoint)

Example Body

{
  "model_id": "fastino-pii-••••••••••",
  "input": [
    {
      "text": "9 AM for a Sedan for Jamie Derran",
      "parameters": {
        "entity_types": [
          "full_name",
          "car",
          "time"
        ],
        "threshold": 0.3
      }
    }
  ]
}

Response

Name	Type	Description
input	string	Original user-provided string.
latency_ms	number	Model inference time (excludes network and API gateway latency)
output	object	The output of the model. Structure varies depending on the model being used.
status	string	Overall request status (e.g., success, error)

Example Response

[{
  "input": "9 AM for a Sedan for Jamie Derran",
  "latency_ms": 77.31,
  "message": "Responses from endpoint.",
  "output": {
    "entities": [
      {
        "start": 0,
        "end": 4,
        "label": "time",
        "text": "9 AM",
        "score": 0.5893954038619995
      },
      {
        "start": 11,
        "end": 16,
        "label": "car",
        "text": "Sedan",
        "score": 0.8889331817626953
      },
      {
        "start": 21,
        "end": 33,
        "label": "full_name",
        "text": "Jamie Derran",
        "score": 0.9932531714439392
      }
    ],
    "redacted_text": "<TIME> for a <CAR> for <FULL_NAME>"
  },
  "status": "success"
}]