Pinn AI API

Name: Pinn AI API
Brand: Pinn AI API
Availability: InStock

✓ Official Vendor SpecAI/MLConversational Aibearer45 EndpointsREST

For Agents

Build conversational AI applications with intent recognition, entity extraction, dialogue management, and voice synthesis. Supports 45 endpoints covering NLU, conversation flows, knowledge bases, and analytics.

Install Jentic One Beta

Connect the Pinn AI API to your agent

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

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

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.

Capabilities

What an agent can do with Pinn AI API.

Process natural language input with intent classification and entity extraction across multiple languages

Manage multi-turn conversations with context retention and dialogue state tracking

Generate contextual responses from knowledge bases, APIs, and custom content sources

GET STARTED

Start building with Pinn AI API

Explore with Jentic

View OpenAPI Document

Use Cases

Patterns agents use Pinn AI API for, with concrete tasks.

★ AI-Powered Customer Support Bot

Build intelligent customer support bots that understand user questions, retrieve answers from knowledge bases, and escalate to human agents when needed. The API provides intent recognition to route queries, entity extraction to capture customer details, and knowledge base search to find relevant help articles. Conversation analytics track resolution rates and common issues for continuous improvement.

Process incoming customer message 'I need to reset my password for account #12345', extract intent (password_reset) and entities (account_number: 12345), retrieve relevant help article from knowledge base, and generate a response with reset instructions

Voice-Enabled Virtual Assistant

Create voice assistants for mobile apps, smart speakers, or IVR systems with speech recognition, natural language understanding, and text-to-speech synthesis. The API handles multi-turn dialogue flows with context retention, allowing assistants to ask clarifying questions, remember user preferences, and complete complex tasks across multiple interactions. SSML support enables natural prosody and emphasis in speech output.

Start a voice conversation for 'Book a flight to New York', extract entities (destination: New York), prompt for date and passenger count across multiple turns while maintaining context, then synthesize speech response with flight options

Domain-Specific NLU Training

Train custom natural language understanding models for specialized domains like healthcare, finance, legal, or technical support. The API supports uploading training data with domain-specific intents, entities, and example utterances, then deploying the trained model for inference. Models can be versioned, A/B tested, and continuously improved based on production traffic.

Upload training data with 50 intents covering medical appointment scheduling, train a new NLU model, deploy it to staging environment, and test with sample patient queries

Conversational Analytics and Optimization

Analyze conversation patterns, intent confidence scores, user satisfaction, and drop-off points to optimize dialogue flows and improve bot performance. The API provides conversation transcripts, intent distribution, entity extraction accuracy, and response time metrics. Teams can identify common intents that lack good responses, detect confusion patterns, and measure bot-to-human handoff rates.

Retrieve conversation analytics for the last 7 days, identify intents with confidence scores below 70%, find conversations with user dissatisfaction signals, and export data for model retraining

Key Endpoints

45 endpoints — pinn ai provides conversational ai infrastructure for building voice and chat assistants with natural language understanding, speech synthesis, multi-turn dialogue management, and knowledge base integration.

METHOD

PATH

DESCRIPTION

POST

/v1/conversations

Create a new conversation session

POST

/v1/conversations/{id}/messages

Process user message and get response

POST

/v1/nlu/predict

Extract intent and entities from text

POST

/v1/knowledge/search

Query knowledge base for relevant content

POST

/v1/tts/synthesize

Synthesize speech from text

POST

/v1/models/train

Train a custom NLU model

GET

/v1/analytics/conversations

Retrieve conversation analytics

POST

/v1/conversations

Create a new conversation session

POST

/v1/conversations/{id}/messages

Process user message and get response

POST

/v1/nlu/predict

Extract intent and entities from text

POST

/v1/knowledge/search

Query knowledge base for relevant content

POST

/v1/tts/synthesize

Synthesize speech from text

Why Jentic?

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

Credential isolation

Pinn AI bearer tokens are stored encrypted in the Jentic vault and injected as Authorization headers at execution time. Raw tokens never appear in agent prompts, conversation transcripts, or analytics exports.

Intent-based discovery

Agents search by intent such as 'process user message with intent recognition' or 'synthesize speech from text' and Jentic returns the matching endpoint with its schema and required parameters.

Time to first call

Direct Pinn AI integration: 2-4 days for authentication, conversation flow design, and knowledge base setup. Through Jentic: under 1 hour — search, load schema, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

OpenAI Chat API

General-purpose LLM chat interface with broader capabilities but less conversational structure

Choose OpenAI for general-purpose language understanding and generation; choose Pinn AI for structured conversation flows, intent recognition, and voice synthesis in production support systems

Alternative

Dialogflow API

Google's conversational AI platform with intent recognition and dialogue management

Choose Dialogflow for deep Google ecosystem integration; choose Pinn AI for more flexible knowledge base integration and custom model training

Alternative

Rasa API

Open-source conversational AI platform with on-premise deployment options

Choose Rasa for self-hosted open-source deployments; choose Pinn AI for managed cloud infrastructure with faster time-to-production

FAQs

Specific to using Pinn AI API through Jentic.

What authentication does the Pinn AI API use?

The API uses bearer token authentication with API keys created in the Pinn AI dashboard. Each request includes an Authorization: Bearer {token} header. Through Jentic, bearer tokens are stored encrypted and injected automatically — they never appear in agent prompts or conversation logs.

Can I train custom intent recognition models?

Yes. POST /v1/models/train accepts training data in JSON format with intents, entities, and example utterances. The API trains a model specific to your domain and deploys it to a model ID for inference. You can version models, run A/B tests, and retrain based on production feedback.

What languages does Pinn AI support?

Pinn AI supports 30+ languages for NLU including English, Spanish, French, German, Portuguese, Italian, Dutch, Chinese, Japanese, and Korean. Speech synthesis is available in 20+ languages with multiple voice options per language. Language is specified per conversation or inference request.

What are the rate limits?

Standard plans have 1000 NLU requests per minute and 500 TTS requests per minute. Enterprise plans offer higher limits and dedicated infrastructure. Rate limit headers (X-RateLimit-Limit, X-RateLimit-Remaining) are returned in all responses.

How does Pinn AI handle conversation context?

Each conversation session (POST /v1/conversations) maintains context across multiple messages. The API tracks dialogue state, previous intents, extracted entities, and user preferences. Context is retained for the session duration (default 30 minutes of inactivity) or until explicitly cleared.

Is there a free tier?

Yes. Pinn AI offers a free Developer plan with 10,000 NLU requests and 5,000 TTS requests per month. Paid plans start at $99/month for production use with higher limits, custom model training, and premium voices.