I Built India's First AI Agent Observability Platform — Here's How to Use It (Free, Open Source)

Step 2: Add 2 Lines to Your Agent
from drishti import Drishti

drishti = Drishti(api_key="Your_API_KEY")

with drishti.trace("my_agent") as trace:
result = agent.run(user_query)
trace.set_output(result)

That's it. Every LLM call is now tracked.

What You See on the Dashboard
Live Demo: https://youtu.be/k8U_DwPs1Uk

Once integrated, your dashboard shows:

1. Today's Spend in ₹
2. Total Traces with latency
3. Error Rate with Hinglish explanations
4. Step-by-step timeline of every agent execution

Hinglish Error Example
Error: Failed to connect to shipping-api.example.com — timeout after 5s

Hinglish Explanation:
🔮 Timeout!
Request ka time limit khatam ho gaya — server ne response nahi diya.

Fix karo: Timeout value badhaao (default 30s se 60s karo).
Ya retry logic add karo apne code mein.

Pricing Built for India

Free: 10,000 traces/month, 7-day history
Pro: ₹799/month, 500K traces, WhatsApp alerts
Team: ₹2,499/month, unlimited traces

No dollar conversion. No hidden fees. INR always.

Open Source Core

The SDK is MIT licensed on GitHub. Self-host for free or use our managed cloud.
🔗 Website: drishtiai.dev
📦 GitHub: github.com/Harsh-0602/drishti-sdk

Built for Indian Developers

I'm Harsh, a solo developer from India. I built Drishti because I faced this problem every day. If you're building with LLMs in India, I'd genuinely love your feedback.

Try it free — no credit card required.

What features would you like to see next? Let me know in the comments 👇