RazorScout
An AI-powered agentic commerce platform that takes buyers from natural-language intent to a verified Razorpay transaction.
The idea
What if AI could actually participate in commerce?
Traditional e-commerce puts the entire shopping workflow on the buyer — searching, comparing, finding accessories, managing the cart and finally completing payment.
RazorScout changes that interaction by introducing an AI agent directly into the commerce workflow.
Buyers can describe what they want naturally. The agent discovers relevant products, manages the cart and, when appropriate, recommends complementary products before checkout.
The final transaction remains controlled by the backend and Razorpay, keeping AI reasoning separate from transaction-critical operations.
The experience
From intent to transaction.
Two buying paths, designed around how people actually shop.
Intent → Product → Payment
When a buyer already knows what they want, the agent provides a frictionless path directly to Razorpay Checkout.
Cart → Context → Cross-Sell
When the buyer is already building a cart, RazorScout uses that context to surface complementary products before payment.
Product
Built around the buyer.
A commerce interface where natural language, product discovery and transactions come together.
CROSS-SELL
Contextual recommendations
CART
Agent-assisted checkout
PAYMENTS
From AI interaction to a verified transaction
RazorScout creates Razorpay orders on the backend and verifies the payment before confirming the order.
Recommendation engine
Related is not enough.
A simple similarity search can find products that are related to what a customer is buying. But related does not necessarily mean complementary.
RazorScout combines semantic retrieval, structured product metadata, business rules and AI classification to determine whether a product is complementary, an alternative, or unrelated.
Under the hood
AI for reasoning. Backend for control.
The architecture separates probabilistic AI decisions from transaction-critical commerce operations.
AI
LangChain · LangGraph · Groq · Gemini
Search
LanceDB · Embeddings · Semantic Retrieval
Backend
Node.js · Express · MongoDB
Payments
Razorpay · Server-side Verification
Agentic commerce
Built with boundaries.
An AI agent participating in commerce needs more than intelligence. It needs control, visibility and accountability.
Explainable
Recommendations are based on product context and classification.
Bounded
Commerce operations enforce stock, cart and transaction constraints.
Gated
Money movement requires explicit Razorpay Checkout authorization.
Auditable
USER and AGENT actions are recorded throughout the journey.
Merchant side
AI that can be measured.
The merchant does not just get an AI assistant. They can see whether AI recommendations actually lead to additional purchases and revenue.
AI-GENERATED REVENUE
₹XXXX
ADDITIONAL PURCHASES
XX
RazorScout
Commerce that moves at the speed of intent.
From natural-language intent to discovery, recommendation, cart, payment and verification — an AI agent participating in the commerce workflow.