Launch · Commerce & Consumer Brands

Flash AI pivots to AI shopping assistant

By Startup Enthusiast · 3 February 2026

What they do

Flash AI is an AI-powered shopping assistant that helps users discover and research products

The Bengaluru startup raised $12.5 Mn and launched its new assistant in September 2025

It targets the pre-purchase stage, aiming to tap into a $3-5 Tn agentic commerce market

Flash AI launched as an AI-powered shopping assistant in September 2025.
The company raised $12.5 Mn across two rounds from Blume Ventures, PeerCapital, and angels.
The startup pivoted from a centralised email service for power shoppers to an AI assistant.
The new service works by appending 'flash.co/' before a product page URL for AI analysis.
The AI presents a summary of features, pros, and cons within a minute.
Flash AI ended support for its email service and cut back rewards to focus on the pivot.
The assistant handles 750,000 users and researches nearly 2 Mn products monthly.
Most traction comes from beauty, personal care, and electronics categories.

Agentic commerce (AI agents that shop on behalf of users) could add $3-5 Tn in revenue to global B2C retail.
64% of Indian consumers use AI tools in their purchase journey.
There are 50 Mn ChatGPT queries a day related to shopping.
The pivot from email to AI assistant reflects a shift to hyper-personalisation in pre-purchase research.

Flash AI is an AI shopping assistant for personalised product discovery and research.
It targets the pre-purchase stage, not the transaction itself.
The service uses 6-7 LLM calls per product research, with pre/post-processing, real-time and cache.
It sources information from YouTube, Reddit, expert blogs, transcription, and classification.
The AI provides unbiased, consumer-first reviews, not optimised for conversion.
The earlier email service tracked orders, provided spending insights, and earned rewards.
In its inbox era, it handled 3-4 Mn orders a month.
The company is based in Bengaluru.

Building a skin analyser with dermatologists using selfies for personalised product recommendations.
Will beat competitors in depth, not breadth, with category-level personalisation.