01
Support that starts with context
Draft replies, summarise tickets and help your team find answers. Keep a human review step where it matters.
For teams building AI into their products
Ship AI features.
Keep access and costs under control.
Connect your application to multiple AI models through one API. Manage access, set spending limits and track usage—with consolidated billing in rupees.
OpenAI-compatible API · Scoped keys · INR billing
Start with one useful feature
What are you building?
02
Documents your software can use
Extract fields, classify documents and turn unstructured text into a workflow. Validate model output before saving it.
03
An AI feature inside your product
Add a writing assistant, search experience or in-app copilot. Evaluate models against the task your customers actually need.
Your application. One integration.
From a model call
to a feature you can ship.
Use the OpenAI SDK with the unoblox endpoint and your API key. Choose a model from the catalogue, then test it on representative inputs from your application.
This Python example drafts a support reply. Install the openai package and set UNOBLOX_API_KEY in your server environment. Keep your key out of browser code.
Example · draft a support reply
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.unoblox.ai/v1",
api_key=os.environ["UNOBLOX_API_KEY"],
)
response = client.chat.completions.create(
model="qwen/qwen3.8-27b",
messages=[{
"role": "user",
"content": "Draft a reply asking which invoice needs correcting.",
}],
max_tokens=256,
)
print(response.choices[0].message.content)As your feature grows
Keep the controls in one place.
Control access
Create scoped API keys for your applications and manage which models they can use.
Set spending limits
Apply key-level budgets and monitor usage as you move from a prototype to real traffic.
Simplify model billing
Access supported models through one gateway with consolidated INR billing. Check current model pricing before you run.
A practical first step
Bring one workload. Test it properly.
Start with a real task, a small evaluation set and a spending limit. Compare answer quality, latency and cost before expanding. Tell us what you are building if you would like help choosing where to start.