Luca - Meet the pricing co-pilot for e-commerce businesses.

We help retailers set prices and discounts that create 10% more profits and revenue, with 10% of the effort.


Luca is a machine learning-powered co-pilot for retail, which constantly identifies headroom in your store, makes recommendations for price adjustments, and helps you manage decisions across all sales channels.

We are an ex-Uber Pricing team that is already helping retailers manage prices for over $50mill of revenue. Get in touch with us!

Our Story

We are Yonah Mann and Tanvi Surti. We met while working at Uber, where we both worked on pricing technology. Our work cumulatively created over $1 billion in margin gains for Uber – and this experience made us realize that configurable revenue tools in the hands of operators could be incredibly powerful!

So, we are now on a mission to bring revenue optimization tools to retail, and build a fun company as we go along!

The Problem

E-commerce teams have to react to large swathes of data from multiple channels to build a pricing and discount strategy, such as  –

  1. ⛅ Seasonal and Market trends, with changing customer price elasticities
  2. 👯 Competitor price changes or promotional campaigns
  3. 🚛 Inventory availability
  4. 🚢 Changing manufacturing and shipping costs

And, they have to do this across 1000s of SKUs and across multiple stakeholder teams such as Merchandising, Marketing, Revenue, and Inventory. This level of complexity makes changing prices time-consuming and inefficient, while still leaving money on the table.

Our Solution

We replace fragmented decision making in e-commerce teams with our pricing system that organizes, recommends and measures outcomes, ensuring that every product is priced in a way that optimizes revenue and profits. Here’s how –

  1. 👀 Observe: We connect with the customer’s sales and inventory data sources (Amazon and Shopify to start, more to come soon), and create a real-time view of customer elasticities and conversion rates.
  2. 👉 Recommend: We feed historical sales, competitor and market data into our machine learning model, combine it with inventory availability and make recommendations for price and discount adjustments.
  3. 🖐 Act: We bubble up the recommendations over email and Slack, allowing the business to quickly act upon the data and push the changes to production across all their channels.
  4. ⚙ Configure: Lastly, we allow the business to configure custom rules, such as competitor-based pricing guardrails or wholesale-price-based constraints.


  • If you work in retail and would like to try our product, please sign up here and we will get in touch with you.
  • If you know someone in your network who would be interested in this, please drop us a note at founders@askluca.com