AI LAB
Zepto Order-Support Agent: Route to the Right Tool
Build a project on LLM order-support routing that sends every Zepto chat to the right tool automatically
Verified Certificate on Successful Completion
What is in it for you?
LLM tokens included
A metered token budget is bundled in, call real models from your code with no API key or extra cost.
AI mentor on tap
Stuck? An in-IDE AI mentor gives hints and debugging help, without handing you the answer.
Instant grading
Submit and get an objective, rubric-based verdict in seconds, pass, or actionable feedback.
Verified certificate
Pass and earn a shareable, verifiable certificate you can add to your LinkedIn profile.
Zero-setup cloud IDE
A ready sandbox with the libraries pre-installed, start building in the browser instantly.
Retry until you pass
Iterate as many times as your budget allows; a fail keeps the lab open to try again.
Grab your slot before the offer expires
Start solving today!
Basic Info
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Project Statement
Business Problem
A quick-commerce support desk fields 40,000+ customer chats a day, and every one has to be sorted into the right queue — delivery status, missing items, cancellations, or repeat orders. Manual triage by 60+ agents adds 30–45 seconds per message and misroutes roughly 12% of tickets, delaying refunds and frustrating customers.
AI Solution
You'll build an LLM agent that classifies each incoming message into exactly one of four support actions and outputs a single clean tool name that automation can act on instantly. The focus is on prompt design and output discipline so the model stops chatting and starts deciding — reliably, one decision per message.
Potential Impact
Automated first-touch routing can cut triage time from ~40 seconds to near-zero per message and lift routing accuracy above 95%, freeing agents to resolve issues instead of sorting them. For a 40,000-chat-a-day operation that's hundreds of agent-hours saved weekly and faster refunds and CSAT gains.
Skills that you will build
Solve a real AI-engineering problem that builds in-demand skills and a portfolio-ready, verified certificate.
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Prompt engineering for structured, deterministic outputsIntent classification with LLMsDesigning tool-calling / routing agentsConstraining model output to strict formatsTesting agent behaviour across varied inputsDebugging weak prompts into reliable onesManaging an LLM token budget efficientlyAI Lab Pre-requisites
- Comfortable reading and running basic Python
- Understand what an LLM prompt is at a high level
Target Roles
- AI Engineer
- LLM Application Developer
- Agent Engineer
- AI Solutions Architect
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Frequently asked questions
Are LLM tokens included?
Yes. The lab runs on a metered LLM budget that's included — no separate API key or billing needed.
What do I earn on completion?
A verified, shareable credential you can add to LinkedIn or your resume to prove your agent-building skills.
Do I need prior AI experience?
No. If you can read basic Python and understand what a prompt is, you're ready. An AI mentor is available for hints.
Is this a course with classes?
No. It's a single focused, hands-on lab you solve in a locked-down cloud IDE — no batches, no schedules.
How is my work graded?
An auto-grader instantly checks that your agent routes each message to the correct support action in the required format.
What if I get stuck?
An AI mentor is built into the lab to give you hints without handing you the answer.