Intent

Name: Intent API
Brand: Intent
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLMl InferenceapiKey4 EndpointsREST

For Agents

Classify customer messages into trained intent labels by calling a MessageBird Intent dataset, with confidence scores returned per prediction.

Connect the Intent to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Intent, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Install Jentic One Beta (Self-Hosted)

Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Intent API.

Classify an inbound SMS phrase into a trained intent label and read its confidence score

List all intent classification datasets available on the account before choosing one for prediction

Inspect a single dataset to confirm its training status before sending production traffic

Look up the languages supported by the Intent service to gate predictions on unsupported locales

GET STARTED

Start building with Intent API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI document for Intent, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for Intent, keeping it validated and agent-ready. The MessageBird Intent API classifies short text utterances into customer-defined intents using trained classification models that live in datasets. Agents send a phrase to a chosen dataset and receive predicted intent labels with confidence scores, which is useful for routing inbound SMS, WhatsApp messages, or chatbot turns to the right workflow. Supported languages are exposed via a dedicated endpoint, and dataset metadata reveals training status before predictions are attempted.

Use Cases

Patterns agents use Intent API for, with concrete tasks.

★ Inbound Support Triage

Classify inbound SMS or chat messages into a fixed set of support intents (billing, cancellation, technical issue) so each conversation is routed to the correct queue or automated reply. The Intent API runs the prediction against a dataset that was previously trained on labelled examples and returns the top intent label with a confidence score, letting the workflow fall back to a human when confidence is low. Triage decisions can be made in milliseconds before the message ever reaches an agent.

POST a customer message to /api/v1/datasets/{datasetId}/predict on the support classifier dataset and forward it to the billing queue when the predicted intent is 'billing_question' with confidence above 0.8

Chatbot Disambiguation

Use predicted intents to drive branching logic inside an automated chat flow. When a user replies in free text, the bot calls the Intent API with the user's phrase and uses the returned label to pick the next step, instead of relying on brittle keyword matching. Datasets can be retrained as new intents emerge without changing the bot code, and the supported-languages endpoint lets the bot decline gracefully on unsupported locales.

Call POST /api/v1/datasets/{datasetId}/predict with the user's chat reply and branch the flow based on the predicted intent label

Dataset Readiness Monitoring

Before promoting a new classifier into production traffic, agents can list all datasets and inspect each one individually to confirm training has finished. The dataset detail endpoint exposes status information so a deployment workflow can wait for training to complete before flipping traffic. This avoids the failure mode of sending live messages to a half-trained model.

GET /api/v1/datasets and then GET /api/v1/datasets/{datasetId} to verify training has completed before routing live traffic to the classifier

AI Agent Integration via Jentic

An AI agent uses Jentic to discover the Intent API by intent search ('classify a customer message') without needing to read MessageBird's documentation. Jentic returns the predict operation with its input schema, so the agent can submit a phrase and receive a structured intent prediction in a single load-and-execute step. Credentials are isolated in the Jentic vault and never enter the agent's prompt.

Use Jentic to search 'classify a customer message into intents', load the Intent predict operation schema, and execute it against the production support dataset

Key Endpoints

4 endpoints — jentic publishes the only available openapi specification for intent, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

GET

/api/v1/datasets

List all intent datasets

GET

/api/v1/datasets/{datasetId}

Get a single dataset including training status

POST

/api/v1/datasets/{datasetId}/predict

Predict the intent of a phrase against a dataset

GET

/api/v1/supported-languages

List supported classification languages

GET

/api/v1/datasets

List all intent datasets

GET

/api/v1/datasets/{datasetId}

Get a single dataset including training status

POST

/api/v1/datasets/{datasetId}/predict

Predict the intent of a phrase against a dataset

GET

/api/v1/supported-languages

List supported classification languages

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

MessageBird AccessKey API keys are stored encrypted in the Jentic vault (MAXsystem). Agents receive scoped tokens — the raw `AccessKey` value never enters the agent's prompt or logs.

Intent-based discovery

Agents search by intent (e.g. 'classify a customer message') and Jentic returns the Intent predict operation with its input schema, so the agent calls the right endpoint without browsing MessageBird docs.

Time to first call

Direct MessageBird Intent integration: 1-2 days for auth, dataset wiring, and error handling. Through Jentic: under 30 minutes — search, load schema, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

MessageBird Language Detection

Detect the language of a phrase before passing it to the Intent classifier

Use Language Detection first when inbound messages may arrive in any locale, then route to a language-specific Intent dataset

Complementary

MessageBird Named Entity Recognition

Extract entities like names, dates, and locations from the same message after intent classification

Choose NER when the intent is known and the agent now needs to pull structured slots from the message body

Alternative

OpenAI API

General-purpose LLM that can classify intents via prompting instead of a trained MessageBird dataset

Pick OpenAI when you do not have labelled training data or need flexible zero-shot classification across many intents

Alternative

Cohere

Hosted classifier and embedding API for building intent classifiers without managing infrastructure

Pick Cohere when you want to train a custom classifier endpoint outside the MessageBird messaging stack

FAQs

Specific to using Intent API through Jentic.

Why is there no official OpenAPI spec for Intent?

MessageBird does not publish an OpenAPI specification for the Intent API. Jentic generates and maintains this spec so that AI agents and developers can call Intent via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the MessageBird Intent API use?

The Intent API uses an API key sent in the `Authorization` header, prefixed with the literal word `AccessKey`. Through Jentic, the access key is stored in the MAXsystem vault and injected at request time, so the raw key never enters the agent's context.

Can I list available intent datasets before running predictions?

Yes. Call GET /api/v1/datasets to enumerate every dataset on the account, then GET /api/v1/datasets/{datasetId} for full details on a specific one. This is how you confirm a model has finished training before sending live traffic to it.

What languages does the Intent API support?

Call GET /api/v1/supported-languages to retrieve the full list at runtime rather than hardcoding it. The set evolves as MessageBird adds language coverage to the underlying classifier.

How do I classify a message through Jentic?

Search Jentic for `classify a customer message into intents`, load the POST /api/v1/datasets/{datasetId}/predict operation, and execute it with your phrase and target dataset. Jentic returns the predicted intent label plus confidence in a structured response.

Are there rate limits on the Intent API?

The OpenAPI spec does not document specific quantitative rate limits, so check your MessageBird account dashboard or contact MessageBird support for the limits attached to your plan before bulk-classifying traffic.