TBZ Jewellers (Tribhovandas Bhimji Zaveri) Case Study Hero Background

How TBZ Jewellers Transformed Retail Decision-Making with Autonomous BI Agents on Microsoft Fabric

LocationIndia

SolutionAutonomous BI Decision Agents with Microsoft Fabric & Power BI

Real-Time

Store Sales & Inventory Forecasting

15+ hrs/wk

Saved in Manual Dashboard Analysis

Proactive

Stock Balancing & Reorder Triggers

At-a-Glance

TBZ Jewellers (Tribhovandas Bhimji Zaveri Ltd.) — one of India’s most historic and renowned luxury jewelry retail brands with showrooms across the nation.

Case Study

CHALLENGE:

Managing high-value precious jewelry inventory across dozens of retail stores required tracking volatile gold commodity prices, fluctuating bridal demand, and localized store sales. Static daily Power BI dashboards left leaders reactive to stockouts and slow-moving collections.

SOLUTION:

Intelegain implemented Autonomous Business Intelligence Agents connecting Microsoft Fabric and Power BI with Microsoft Foundry and Python. The agents autonomously analyze multi-store data, forecast localized trends, and trigger proactive inventory rebalancing decisions.

RESULTS:

Shifted corporate BI from passive reporting to proactive decision support, saving 15+ hours per week per regional manager and reducing stockouts on high-velocity bridal collections by 40%.

The Challenge: High-Value Inventory Friction in Luxury Retail

Tribhovandas Bhimji Zaveri (TBZ) is synonymous with Indian bridal luxury and fine craftsmanship. Operating across a nationwide network of flagship showrooms, TBZ manages thousands of high-value stock-keeping units (SKUs) in gold, diamond, and platinum jewelry.

In luxury jewelry, inventory management is exceptionally intricate. Retail margins and consumer purchasing decisions fluctuate with daily global bullion rates, regional wedding calendar dates, and localized festival demand. For years, executive leadership and regional store heads relied on static Power BI reports and spreadsheet exports compiled overnight.

This retrospective approach created operational blind spots. Regional managers spent hours slicing and dicing dashboards trying to spot stock shortages or slow-moving collections. By the time inventory imbalances were noticed, sales opportunities were already lost to competing retail brands.

Store leadership dependent on manual dashboard analysis, leading to delayed operational decisions.

Frequent stockouts of fast-moving bridal and festival designs during seasonal shopping peaks.

Excess capital tied up in slow-moving collections in stores with mismatched consumer demographics.

Volatile precious metals pricing requiring immediate, store-level pricing and margin adjustments.

Why Intelegain Was Chosen

TBZ Jewellers partnered with Intelegain due to our advanced mastery of the Microsoft Modern Data & AI stack (Microsoft Fabric, Power BI, Azure Synapse) and our agentic BI philosophy.

Microsoft Fabric & OneLake Architecture:

Creating a unified, single-source-of-truth enterprise data lakehouse that ingests showroom POS data, warehouse logistics, and bullion feeds in real time.

Autonomous Agentic Intelligence:

Moving beyond passive dashboards to proactive AI agents that continuously interrogate data models and detect anomalies without human prompting.

Actionable Decision Triggers:

Empowering agents to calculate stock reorder points, forecast localized run-rates, and trigger automated alerts directly to store managers.

Enterprise Governance & Data Security:

Enforcing strict role-based data partitioning across store networks, safeguarding proprietary retail margins.

Implementation: The Intelegain Approach

The autonomous BI transformation was executed over a 16-week enterprise deployment:

Phase 1: Fabric OneLake Unified Data Architecture

Intelegain integrated TBZ’s multi-store POS databases, supply chain ERP, and real-time bullion rate feeds into Microsoft Fabric OneLake, establishing an automated Delta Parquet lakehouse with sub-minute data freshness.

Phase 2: Predictive & Diagnostic Agent Development

Using Python and Microsoft Foundry, we built specialized analytical agents. The agents continuously evaluate inventory turn-rates, regional bridal buying cycles, and price elasticity, identifying inventory optimization opportunities autonomously.

Phase 3: Proactive Notification Triggers & Teams Delivery

We integrated the agents with Microsoft Teams and Power Automate. Instead of opening dashboards, regional heads receive proactive daily briefing cards: ‘Showroom A will run out of Bridal Choker Set X within 48 hours; Showroom B has 3 unsold units—rebalance recommended.

PythonMicrosoft FoundryMicrosoft FabricPower BIMicrosoft DataverseAzure Synapse AnalyticsMicrosoft Teams

Measurable Results & Business Impact

Real-Time

Continuous inventory forecasting and stockout anomaly detection

15+ hrs

Saved per regional manager each week in manual data slicing

40%

Reduction in stockout incidents during peak festive and bridal seasons

18%

Improvement in nationwide inventory turn-rate across gold and diamond jewelry

The deployment of Autonomous BI Agents propelled TBZ from reactive reporting into proactive decision intelligence. Store managers and retail directors no longer comb through hundreds of dashboard rows to find operational answers. Instead, the AI agents continuously watch the business, surfacing high-value anomalies and recommending exact inventory movements that maximize retail sell-through.

Ready to evolve your enterprise reporting from passive dashboards to autonomous decision agents?

Discover how Intelegain can leverage Microsoft Fabric and Power BI to build predictive agents for your enterprise.

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