AI-first retail analytics

See what happens in the aisle, not just at the till.

Niflr fuses computer vision from your in-store cameras with your POS and transactional data — so you know why sales moved, not just that they did. Real-time, store by store, shelf by shelf.

Works with the CCTV you already have. Built in Bangalore.

Backed by Upsparks Capital

CAM-04 · Aisle 7 · Beverages LIVE
SKU-1182 ×3 OUT OF STOCK SKU-0457 ×3 SHOPPER · 42s
On-shelf availability94.2%
Gaps flagged1
Dwell · aisle 742s
Uses existing CCTV Plugs into your POS & ERP Privacy-first — no facial recognition Edge + cloud deployment
The blind spot

Your POS tells you what sold. It can't tell you what didn't.

Transaction data only captures the final moment of a shopping trip. Empty shelves, abandoned baskets, long queues and ignored promotions never show up in a receipt — so the biggest revenue leaks stay invisible. Niflr closes that gap.

Transactions alone

  • Why did SKU sales drop on Tuesday?
  • How many shoppers walked out empty-handed?
  • Was the promo display actually set up?
  • When do queues start costing us sales?

Vision + transactions with Niflr

  • Shelf was empty 11am–3pm — restock alert missed
  • Footfall-to-purchase conversion by zone and hour
  • Planogram and display compliance, verified visually
  • Queue length linked to basket abandonment
How it works

From camera pixels and till receipts to decisions — automatically.

No new hardware roll-outs, no months-long integration. Niflr sits on top of the infrastructure you already run.

Connect

Link existing CCTV streams and your POS, inventory and loyalty data through secure connectors.

Perceive

Vision models detect products, gaps, shoppers and queues — processed at the edge, anonymised by design.

Fuse

Visual events are aligned with transactions by time, location and SKU to build one view of the store.

Act

AI surfaces root causes and pushes alerts to store staff, category managers and brands in real time.

Solutions

One platform. Every question your store couldn't answer.

Start with a single use case in a handful of stores, then scale across your network with the same deployment.

On-shelf availability

Detect out-of-stocks and low facings the moment they happen, and trigger replenishment before sales are lost.

Store ops · Supply chain

Footfall & conversion

Measure visitors, zone heatmaps and dwell time, then tie them to transactions for true conversion by aisle and hour.

Retail leadership · Marketing

Planogram compliance

Automatically audit shelf layouts against planograms across every store — no clipboards, no manual photo checks.

Category management

Promotion & display ROI

Verify that end-caps and brand displays are executed, see how shoppers engage, and measure the real sales uplift.

Brands · Trade marketing

Queue & staffing

Forecast checkout demand from live footfall, alert when queues build up, and align staff rosters to real traffic.

Store managers · Workforce

Shrink & loss insights

Reconcile what left the shelf with what was scanned at checkout to spot anomalies and high-risk zones.

Loss prevention
The platform

An analyst for every store, working every minute.

Niflr doesn't just chart data — it explains it. Ask a question in plain language and get an answer grounded in what the cameras saw and what the tills recorded.

Conversational insights“Why did snacks underperform in Koramangala last week?” — answered with evidence.

Real-time alertsPush notifications to staff apps, WhatsApp or your existing tools.

Network benchmarkingCompare stores, regions and formats on the same visual and sales KPIs.

Open APIsStream events and metrics into your data warehouse or BI stack.

Store 112 · IndiranagarToday · updated 2 min ago
Footfall3,418▲ 8.1% vs LW
Conversion41.6%▼ 2.3 pts
Shelf availability92.7%▲ 1.4 pts
FootfallTransactions
2 pm – 5 pm 9am9pm
Niflr insight: conversion dipped 2–5 pm while footfall peaked. Aisle 7 beverages were out of stock for 3h 10m and checkout queues averaged 6+ shoppers. Estimated lost sales: ₹38,400.

Illustrative sample data

Why Niflr

Built for the realities of modern retail — especially in India.

AI-first, not AI-added

Vision and language models are the core of the product, not a feature bolted onto a BI dashboard.

Hardware-agnostic

Runs on the cameras you already own — from modern IP cameras to older CCTV setups.

Privacy by design

Shoppers are counted and tracked anonymously. No facial recognition, no personal identifiers stored.

Made for scale

From a single kirana-style outlet to hundreds of hypermarkets, with edge processing that handles patchy connectivity.

Backed by
Upsparks Capital

Niflr is funded by Upsparks Capital, who share our belief that the next generation of retail intelligence will be AI-first and built in India.

Get started

See your stores the way Niflr sees them.

Write to us with a little about your business and we'll set up a pilot on a few of your existing cameras — so you see results on your own data, not a demo reel.

Email us [email protected] Request a demo
Niflr Technologies Private Limited
1st Floor, 17th Cross Rd, Sector 4,
HSR Layout, Bengaluru – 560102