Messagebird APIs

5 APIs16 Endpoints2 Categories

API Catalog(4 of 5)

Intent

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.

4 endpoints

LanguageDetection

Jentic publishes the only available OpenAPI specification for LanguageDetection, keeping it validated and agent-ready. The MessageBird Language Detection API identifies the natural language of a short text snippet, returning a language code that downstream services can use to route, translate, or classify the message correctly. It exposes the predict endpoint and a list of supported languages, making it a small focused building block for multilingual messaging pipelines. Predictions are designed for the kinds of short utterances seen in SMS, WhatsApp, and chat traffic.

2 endpoints

MessageBird FAQ

Jentic publishes the only available OpenAPI specification for MessageBird FAQ, keeping it validated and agent-ready. The MessageBird FAQ API hosts curated question-and-answer datasets and predicts the best matching answer for an end-user question against a chosen dataset. It exposes dataset listing and retrieval, an answer-prediction endpoint that scores candidate answers from the dataset, and a supported-languages lookup, making it a focused building block for FAQ-driven chat and IVR experiences inside the wider MessageBird platform.

4 endpoints

NamedEntityRecognition

Jentic publishes the only available OpenAPI specification for NamedEntityRecognition, keeping it validated and agent-ready. The MessageBird Named Entity Recognition API extracts structured entities (names, locations, dates, organisations) from short text inputs, turning unstructured customer messages into machine-readable slots. The predict-entities endpoint accepts a phrase and returns each detected entity with its type, while the supported-languages endpoint indicates which locales the model recognises. NER is the natural pairing for intent classification when an agent needs both 'what does the customer want' and 'what specific values did they mention'.

2 endpoints

Connect Your Agent

Step 1: 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

Step 2: 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.