kvsoftware

DeQRypt

Scan a QR, pay with DeFi, and let an AI agent put idle crypto to work

A Base app that pays QR invoices straight from a DeFi position: a router contract swaps and settles in one atomic transaction. An AI agent built on LangChain and Gemini reads plain-language requests like "invest my idle ETH" and suggests lending moves, in a consultant mode that never signs anything unsafe on its own.

Crypto that sits in a lending pool earns yield, but the moment you want to pay for something with it, you have to pull it out, swap it, and send it, by hand. DeQRypt makes it two moves: scan a QR invoice and pay straight from your DeFi position. Alongside it, an AI agent helps put idle crypto to work, without ever moving it on its own. We built it for the Base Hackathon.

Hackathon
Base Hackathon
Team
5 people
Network
Base Sepolia

Scan to pay

  1. Scan

    The merchant's QR invoice.

  2. Pay with IDRX

    From the funds in your DeFi position.

  3. Router contract

    Swaps and settles in one atomic transaction.

  4. Settled

    The merchant is paid; nothing half-done.

A payment either completes in full or not at all.

The agent

Ask in plain language, like "invest my idle ETH", and the agent works out what you mean with LangChain and Gemini. It then looks up live APYs for trusted lending pools on Base, such as Moonwell and Aave V3, from DefiLlama, and recommends one for your token, with what you'd earn over two months, six months, and a year.

  1. Your request

    In plain language.

  2. LangChain + Gemini

    Reads the intent.

  3. Live APYs

    Trusted Base lending pools, from DefiLlama.

  4. Recommendation

    A pool and the projected profit. You decide.

The agent recommends; only you can act on it.

Consultant mode

An agent that can move money is only as safe as what stops it. In consultant mode, the agent never lends on its own: it can only recommend. That rule lives in two places, the prompt and the code, so even if the model is talked into trying, the backend won't let the move through.

My part

I was one of the two AI agent architects and backend engineers on a team of five. I orchestrated the agent's flow, from reading the request to returning a recommendation, and built the API the app needed around it.

Where it ended

We didn't make the finals. DeQRypt runs on Base Sepolia, Base's test network, with test tokens; moving to mainnet and real protocol integrations was the next step on the roadmap.

Back to the work