HomeBig DataSmarter Selections at Scale: How Lotus’s Makes use of AI and NLQ...

Smarter Selections at Scale: How Lotus’s Makes use of AI and NLQ to Empower 3,000+ Shops with Actual-Time Intelligence


Making On a regular basis Retailer Selections Smarter, Sooner

Within the fast-paced world of retail, retailer managers are underneath fixed stress to make fast choices based mostly on real-time efficiency. Lotus’s, one in every of Thailand’s largest retailers, acknowledged that regardless of getting access to considerable knowledge, actionable insights remained out of attain for a lot of frontline groups. The corporate sought a approach to empower its 3,000+ retailer managers to make smarter choices from the palm of their hand.

Amity Options partnered with Lotus’s to introduce a Pure Language Question (NLQ) platform built-in with a chatbot interface, making it simple for non-technical customers to retrieve insights simply by asking questions in Thai or English in plain language like “ยอดขายวันนี้เทียบกับเมื่อวานเป็นอย่างไร?” or “Which SKUs are underperforming this week?”—no dashboards, no delay, simply on the spot solutions.

A Basis for Scale, Pace, and Retailer-centric Selections

With Amity’s NLQ-powered resolution, Lotus’s has redefined how insights are accessed and acted upon on the retailer stage. Quite than navigating a number of methods or stories, retailer groups now have interaction instantly with their knowledge utilizing pure questions, decreasing dependency on head workplace and rushing up response time to on-ground occasions.

The chatbot interface, built-in with each desktop and cellular platforms, ensures that knowledge is at all times obtainable on the go. Whether or not figuring out underperforming SKUs or validating promotional effectiveness, retailer leaders at the moment are outfitted to make choices immediately and independently.

Actual-Time Retail Intelligence in Below a Minute

This near-instantaneous response is powered by Databricks Mosaic AI Mannequin Serving, which ensures low-latency, real-time inference. This permits retailer managers to obtain solutions in seconds with out mannequin deployment and upkeep complexities. The platform additionally makes use of Mosaic AI Vector Search to seek out essentially the most related knowledge for every question effectively.

With a backend powered by scalable infrastructure, Amity’s resolution gives solutions inside 5 seconds to 1 minute. This has reduce perception supply time from a mean of 2-3 hours to underneath a minute, decreasing guide report dependency and enabling leaner ops groups throughout areas. Insights that when took a good portion of the day to compile at the moment are only a query away.

Whether or not checking on gross sales anomalies, inventory provisions, or weekly identified loss stories, managers can act sooner, growing store-level effectivity, agility, and efficiency.

Example UI Page of Real-Time Retail Intelligence: Follow-up Question
Determine 1. Instance UI Web page of Actual-Time Retail Intelligence: Comply with-up Query
Example UI Page of Real-Time Retail Intelligence: Sales Report
Determine 2. Instance UI Web page of Actual-Time Retail Intelligence: Gross sales Report

The Rising Utilization of Actual-Time Retail Intelligence

Daily User Performance Breakdown
Determine 3. Every day Consumer Efficiency Breakdown

This chart illustrates the growing utilization of an AI-powered system by monitoring two key metrics over time (from September 2024 to April 2025).

The information demonstrates an upward development in system engagement (message quantity) and consumer base (distinctive customers), showcasing elevated adoption and utilization of the AI capabilities throughout the group.

Reworking Information Entry with Morning To-Do Lists

To transcend conventional query-based insights, Amity launched a To-Do Checklist (TDL) characteristic, a day by day AI-generated briefing tailor-made for every retailer. It highlights anomalies, efficiency gaps, and high-priority actions throughout:

  • Gross sales spikes and underperformance
  • Inventory gaps and overstock alerts
  • Margin points and adjustment solutions
  • Identified loss monitoring with detailed merchandise breakdowns
  • Promotion feasibility based mostly on present inventory

Retailer managers begin their day at 8:00 AM with the TDL, which now replaces the necessity to open a number of BI instruments or await IT stories.

TDL offers me insights I’ve by no means seen earlier than. It helps me focus straight away. I can spot irregular gross sales, perceive inventory points, and even see margin gaps earlier than morning rounds are over. — Retailer Supervisor, Lotus’s

Example UI Page of To-Do List
Determine 4. Instance UI Web page of To-Do Checklist

Safe and Scalable Information Infrastructure with Databricks

Behind the scenes, your complete knowledge and analytics engine is constructed on Databricks, making certain pace, scalability, and robustness throughout 1000’s of areas. Amity applied a Row-Degree Safety (RLS) mannequin inside the Databricks Platform, making certain that every retailer supervisor solely accesses the information related to their retailer, preserving privateness and operational integrity.

To streamline deployment and observability throughout its rising variety of LLM-based instruments, Amity leverages Mosaic AI Gateway. This permits for unified logging, efficiency monitoring, and fallback routing throughout basis fashions, making certain reliability and governance at enterprise scale.

This structure helps real-time knowledge pipelines, day by day AI job era, and safe user-specific querying, all managed on a unified lakehouse structure. The result’s a seamless stability between enterprise-scale governance and on-the-ground usability.

Scaling Perception Throughout Hundreds of Shops

Amity Options at present powers over 3,000 shops throughout Thailand. The AI chatbot receives 1,000+ messages day by day on common, serving as the first interface for retail intelligence that matches into retailer managers’ routines and gadgets.

By making knowledge obtainable immediately and in plain language. Amity has democratized knowledge throughout each stage of the Lotus’s group. From frontline decision-making to regional technique, the insights delivered have shortened response occasions, elevated focus, and empowered each retailer to carry out at its greatest.

A New Commonplace for Information-Pushed Retail

The collaboration between Lotus’s and Amity Options marks a brand new chapter in trendy retail operations. Each retailer supervisor has entry to AI-powered insights, and each choice is backed by knowledge delivered in actual time.

With confirmed success throughout 1000’s of areas, this resolution has redefined how Lotus’s groups work, making knowledge not simply accessible however actionable, personalised, and embedded into their day by day workflow.

As Lotus’s continues to guide in digital transformation, the NLQ, TDL, and Databricks-powered infrastructure stand as a testomony to what’s attainable when know-how is constructed for the individuals who use it most, delivering readability, pace, safety, and confidence on the frontlines of retail.

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