Skip to main content
This page walks you through the golden path — every step takes ≤ 60 seconds. All Agntix APIs are served from a single base URL behind the API gateway: 
https://api.agntix.ai
The gateway routes traffic to the appropriate upstream service based on the path prefix. As a customer you only ever talk to api.agntix.ai — internal service URLs are not exposed.
1

Create an account

Sign up at app.agntix.ai/signup. The default org plan includes enough free quota to finish this quickstart.
2

Get your API key

Open Settings → API Keys, click Create key, pick Read & write, and copy the value. It looks like:
pk_live_xxxxxxxxxxxxxxxxxxxxxxxx
Set it in your shell:
export AGNTIX_API_KEY=pk_live_xxxxxxxxxxxxxxxxxxxxxxxx
Keys grant full access to your organization. Store them in a secret manager — never commit one to git.
3

Make your first authenticated call

GET /v1/chat/models lists every model your org can use. It needs auth but no body — perfect for a smoke test.
curl https://api.agntix.ai/v1/chat/models \
  -H "x-api-key: $AGNTIX_API_KEY"
A 200 OK here means your key works.
4

Create an agent

The minimum agent needs a name, a model, and a system prompt.
curl https://api.agntix.ai/v1/chat/agents \
  -H "x-api-key: $AGNTIX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Quickstart bot",
    "modelId": "gpt-4o-mini",
    "systemPrompt": "You are a friendly assistant. Be concise."
  }'
Save the id from the response — you’ll need it next.
5

Send a message

Open a session against the agent, then post a user message. The response includes the assistant’s reply.
SESSION=$(curl -s https://api.agntix.ai/v1/chat/chat/sessions \
  -H "x-api-key: $AGNTIX_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{\"agentId\": \"$AGENT_ID\"}" | jq -r .id)

curl https://api.agntix.ai/v1/chat/chat/sessions/$SESSION/messages \
  -H "x-api-key: $AGNTIX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"content": "Say hello in three words."}'

​
You’re done

You now have:
  • An agent your team can iterate on from the dashboard or the API.
  • A session with a real LLM-generated reply.
  • A working API key suitable for your local dev environment.

​
What’s next

Add a knowledge store (RAG)

Make the agent answer from your own documents instead of generic web knowledge.

Wire up voice

Same agent, now speaking — over the browser or PSTN phone calls.

Subscribe to webhooks

Push session lifecycle events to your back-office.

Production checklist

Rate limits, retries, error handling, and SLOs.