Selected work

Real businesses.
Real outcomes.

Every case study below represents a business that replaced chaos with clarity. The numbers are real. The transformations are ongoing.

Garment ManufacturingLeading Garment Export House

From registers to real-time — a 400-operator garment factory, digitized.

Problem

A 400-operator garment export house was running production, cutting, stitching, and payroll on paper. Month-end closing took 12 days. Fabric consumption was estimated, not measured.

Analysis

We spent 6 days on the factory floor. Mapped 47 distinct workflows. Identified that 38% of operator time was spent on non-value-adding documentation.

Solution

Built a unified Garment ERP covering Style → BOM → Cutting → Stitching → Finishing → Packing → Shipping with integrated piece-rate payroll.

Modules delivered

Style & BOMCutting PlanBundle TrackingStitching LinePiece-Rate PayrollShipping

Technology

Next.jsPostgreSQLRedisDockerAWS

Lessons learned

The biggest win wasn't the software — it was redesigning the bundle-tracking workflow. Software amplified a better process.

Business impact

Month-close time
12 days2 days
Fabric wastage
6.2%3.8%
Payroll processing
8 days6 hours
On-time dispatch
71%94%
Product screenshot
Warehouse & LogisticsRegional 3PL Operator

A 60,000 sq.ft warehouse, running on WhatsApp — until it wasn't.

Problem

A 60,000 sq.ft warehouse serving 40+ e-commerce clients was coordinated via WhatsApp groups. Inventory accuracy was ~82%. Picking errors were 4.1%.

Analysis

Pickers walked an average of 11 km per shift. 60% of that was wasted movement. Slotting was random.

Solution

Implemented a WMS with directed putaway, wave picking, mobile RF scanning, and packing verification.

Modules delivered

InboundPutawayWave PickingPackingDispatchClient Portal

Technology

Next.jsReact NativePostgreSQLRedisGCP

Lessons learned

Slotting by velocity alone wasn't enough. Affinity-based slotting (items often ordered together) delivered the second-order win.

Business impact

Inventory accuracy
82%99.6%
Picker walk distance
11 km4.2 km
Picking errors
4.1%0.3%
Orders per picker/day
85220
Product screenshot
Wholesale DistributionWholesale Distributor

A 30-year-old wholesale business, off Excel, in 14 weeks.

Problem

A family-run wholesale distributor with 28 years of history ran on Tally + 14 Excel sheets + 3 WhatsApp groups. Credit limits were advisory, not enforced.

Analysis

Overdue receivables were ₹2.4 Cr. 34% of customers had crossed credit limits — nobody knew.

Solution

Built a unified Inventory + CRM with hard credit control, scheme engine, route sales, and two-way Tally sync.

Modules delivered

InventoryCRMCredit ControlScheme EngineRoute SalesTally Sync

Technology

Next.jsPostgreSQLBullMQTally API

Lessons learned

Hard credit control was resisted for 3 weeks. By week 6, the owners wouldn't go back. The system changed the culture.

Business impact

Overdue receivables
₹2.4 Cr₹0.7 Cr
Order-to-dispatch
36 hrs9 hrs
Month-close
9 days2 days
Scheme calculation errors
~8%0%
Product screenshot

Your case study could be next.

If you're running a business on registers, Excel, and WhatsApp — let's talk.