Hatz AI API

Name: Hatz AI API
Brand: Hatz AI API
Availability: InStock

✓ Official Vendor SpecAI/MLLanguage ModelsapiKey, bearer3 EndpointsREST

For Agents

Generate chat completions and responses through Hatz AI's OpenAI-compatible gateway, and list available models for routing.

Install Jentic One Beta

Connect the Hatz AI API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Hatz 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://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhatz.ai%2Fhatz-ai" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhatz.ai%2Fhatz-ai" | 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 Hatz AI API.

Generate chat completions through /chat/completions using an OpenAI-compatible request body

Run multi-turn responses through /openai/responses with the newer Responses API shape

List available language models on the account via /chat/models for routing decisions

GET STARTED

Start building with Hatz AI API

Explore with Jentic One

View OpenAPI Document

Hatz AI provides an AI inference gateway aimed at managed service providers and small businesses, exposing chat completion endpoints that follow the OpenAI request shape. The API offers a /chat/completions endpoint for standard chat workloads, an /openai/responses endpoint for the newer Responses API pattern, and a /chat/models endpoint for listing the language models available on the account. Teams use it to embed conversational AI in helpdesks, ticket triage, and customer-facing assistants without running their own model infrastructure.

Use Cases

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

★ MSP Helpdesk Assistant

Managed service providers wire Hatz AI into ticketing tools to draft first-response messages and summarize ticket history. The /chat/completions endpoint accepts the same JSON shape as OpenAI, so existing helpdesk plugins work after only changing the base URL and key. This shortens response time on common L1 tickets without retraining staff on a new SDK.

Send a chat completion request to /chat/completions with a system prompt summarizing a ticket and return a draft reply

Model Routing for Cost Control

Call /chat/models at startup to discover which models the account is entitled to, then route requests by cost or capability. A small business can keep cheap models for autoresponders and switch to a stronger model for escalations without hardcoding model IDs. Refreshing the list periodically also picks up newly enabled models without a redeploy.

Call GET /chat/models, parse the response, and select the model with the lowest pricing tag for a draft email task

Responses API Pattern for Multi-Turn Workflows

Use /openai/responses for stateful conversations where you want to pass tool results back into the model on the next turn. The Responses shape simplifies tool-call handling compared with manually threading messages on /chat/completions. Teams adopt it for agent-style workflows that mix retrieval and generation steps.

POST a responses request to /openai/responses with a tool definition and verify the response contains a tool_calls block

AI Agent Inference via Jentic

Agents search Jentic for 'generate a chat completion' and Jentic surfaces Hatz AI's /chat/completions operation alongside other inference providers. The agent picks Hatz AI when an MSP customer needs vendor-specific routing, executes the call with credentials drawn from the vault, and never sees the raw API key. This makes Hatz AI a swappable inference backend in a multi-provider toolkit.

Use Jentic search 'generate a chat completion' to load /chat/completions for hatz.ai and execute with a 3-message conversation

Key Endpoints

3 endpoints — hatz ai provides an ai inference gateway aimed at managed service providers and small businesses, exposing chat completion endpoints that follow the openai request shape.

METHOD

PATH

DESCRIPTION

POST

/chat/completions

Create a chat completion

GET

/chat/models

List available models

POST

/openai/responses

Create a response in the OpenAI Responses shape

POST

/chat/completions

Create a chat completion

GET

/chat/models

List available models

POST

/openai/responses

Create a response in the OpenAI Responses shape

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring Hatz AI by hand means picking between an X-API-Key header and a bearer token and attaching the right one on every inference call. Through Jentic you install once, import the Hatz AI API from the API Directory, store the credential once, and your agent calls it.

Permission scoping

Hatz AI sends its target in the request body across a few inference endpoints (/chat/completions, /openai/responses, /chat/models), so limit the agent to the operations it needs, such as generating a chat completion or listing models. You choose the operations it may call, so anything beyond that set is not included unless you add it.

Credential isolation

Your Hatz AI key or bearer token is stored once, encrypted, by your own Jentic One instance and injected as the right header at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'generate a chat completion' or 'list available models', and Jentic returns the matching Hatz AI operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using Hatz AI API through Jentic.

What authentication does the Hatz AI API use?

The API accepts either an X-API-Key header (apiKey scheme) or a standard Authorization: Bearer token. Jentic stores the credential in the vault and attaches the header automatically at execution time.

Can I list the models available on my Hatz AI account?

Yes. Call GET /chat/models with your credentials and the response lists each model id you can pass into /chat/completions or /openai/responses requests.

Is the Hatz AI API OpenAI-compatible?

The /chat/completions and /openai/responses endpoints follow the OpenAI request and response shapes, so existing OpenAI client libraries work by changing the base URL to https://ai.hatz.ai/v1 and swapping the key.

What are the rate limits for the Hatz AI API?

Hatz AI does not publish public per-endpoint rate limits in the spec; limits are tied to your plan and model tier. Check the Hatz AI dashboard at api-docs.hatz.ai for the limits attached to your account.

How do I send a chat completion through Jentic?

Search Jentic for 'generate a chat completion', load the /chat/completions operation for hatz.ai, and execute with your messages array. Jentic injects the X-API-Key header from the vault so the request runs without your code touching the secret.

Does Hatz AI support tool calling?

The /openai/responses endpoint accepts tool definitions and returns tool_calls in the response, mirroring the OpenAI Responses pattern. Use this endpoint for agent-style workflows that need structured tool invocations rather than free-form text.

Can I limit what my agent is allowed to do with the Hatz AI API?

Yes. Because Jentic One is self-hosted on your own instance, you decide which Hatz AI operations your agent may call, so you can grant only what a task needs, such as generating a chat completion via /chat/completions or listing models via /chat/models. If you do not add an operation like /openai/responses, the agent cannot call it. The credential you store is attached at execution time only for the operations you have allowed, so the agent never gains access beyond that set.

Hatz AI API

Connect the Hatz AI API to your agent

Capabilities

Start building with Hatz AI API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs