Technology
Automation. AI. IoT.
Running underneath every shipment.
Indicold designs its own warehouse automation, writes its own WMS, and instruments its own reefers. The tech stack isn’t bolted on — it’s how the company works.
The Indicold stack
Four layers.
One cold chain.
Every Indicold facility, every IndiLink partner, every IndiMove reefer runs on the same four-layer stack — built in-house, owned end-to-end, deployed everywhere.
Our in-house warehouse management system. Multi-tenant, multi-temperature, multi-site. Available as iOS and Android apps for operators and as a customer portal for visibility.
Energy-management AI for chamber load and compressor scheduling. Routing AI for last-mile and line-haul. Demand-forecasting models for peak-season prep.
Per-pallet, per-chamber, per-reefer sensors for temperature, humidity, door state and GPS. 60-second cadence, redundant power, edge buffering for connectivity gaps.
Rack-clad ASRS, stacker cranes, conveyor lines, automated dock doors, low-GWP refrigeration plants. Designed in-house, integrated by Indicold engineering.
Moolcode WMS
A warehouse management system built for cold chain reality.
Moolcode is the in-house operating system of every Indicold and IndiLink site. We built it because no off-the-shelf WMS treated temperature as a first-class citizen, and because Indian cold-chain operators need software that works on cheap Android handhelds inside −25 °C chambers.
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Built for handhelds
Native iOS and Android apps for operators. Glove-friendly UI. Offline-tolerant.
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Temperature as a first-class dimension
Every SKU, every pallet, every location is bound to a target temperature class. Mis-routes are caught at scan time.
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Multi-tenant, multi-site
One Moolcode instance manages all Indicold sites and partner sites — with row-level isolation per customer.
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Customer portal + alerting
Customers see their own inventory, telemetry and audit trail. Excursion alerts via email, SMS and Slack.
Moolcode mobile apps available on iOS App Store and Google Play.
AI where it pays back
No buzzwords.
Just measured outcomes.
We don’t deploy AI for show. We deploy it where it cuts cost, cuts emissions, or cuts excursions — and we measure the result.
Energy savings, network-wide
AI-driven compressor scheduling and chamber load balancing. Measured against pre-AI baseline at Dholasan over a 12-month window.
Fewer kilometers per drop
Routing AI for last-mile reefer milk runs. Measured against driver-selected routes on the same QSR operator network.
Reduction in chamber excursions
Anomaly-detection model flagging compressor faults 4–12 hours before failure. Pre-emptive maintenance saves the cargo.
Plays well with others
Built for your stack, too.
Moolcode WMS speaks REST. We integrate with SAP, Oracle, Microsoft Dynamics, Blue Yonder, Manhattan, and the major TMS systems out there — out of the box.
Talk to engineering.
We’re happy to walk you through the architecture, the WMS, or what we’ve built on the floor.