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InfoSun
Core GCC Capabilities

Warehouse Automation Integration and Emulation That De-Risk Go-Live

Warehouse automation integration is the engineering work that connects robotics, conveyors, and control systems to a WMS and validates that they perform as one system before and after go-live. It uses emulation and simulation to test throughput, find bottlenecks, and prove readiness while the physical site is still being built.

Human-orchestrated AI Runs on your existing systems Outcomes, not headcount
Core GCC CapabilitiesLiveCapability you ownPeople governAI assists and executes
Overview

InfoSun designs, integrates, and validates warehouse automation and robotics before and after go-live. We build automation frameworks with simulation and emulation, integrate WMS and robotics through structured SIT and performance validation, and govern every change with controlled release management. The result is lower go-live risk: throughput is proven in a digital twin before automation ever touches a live order, with engineers supervising each step.

What we run in Automation Systems Engineering & Integration

Warehouse automation emulation and simulation
Digital twin modelling for automation validation
WMS and robotics integration for AMR, conveyor, and sortation
System integration testing (SIT) and hardware acceptance testing (HAT)
Throughput, bottleneck, and capacity what-if analysis
Performance validation, traceability, and operational dashboarding
Controlled release governance and continuous regression testing
Services

Services in Automation Systems Engineering & Integration

Each service runs on the same human-governed, AI-native operating model. Explore any one for what it covers, the outcomes it drives, and how it is delivered.

Outcomes, not headcount

What the work delivers

Prove it before you build

Emulation validates throughput in a digital twin before automation goes live.

Lower go-live risk

SIT and performance validation catch integration faults early.

Robotics that fit the WMS

Integrate AMRs, conveyor, and sortation so systems act as one.

Safe change

Controlled release and regression testing keep live automation stable.

Typical ranges across supply chain, logistics, and enterprise engagements, baselined against your current numbers at the start.

How it works

One operating model, from first workflow to full scale

1
Agree the scope

Choose the processes together, and analyze them first

2
Establish

Stand up the team, governance, and KPIs

3
Find the AI fit

Where supervised AI suits the work, and where it does not

4
Augment

Agents draft and perform; your people approve

5
Improve together

Tune against live KPIs with your team

Runs on Manhattan, SAP EWM, and Blue Yonder, plus your TMS and ERP. No rip-and-replace.

Ways to run it

Build alone, contract it out, or run it with InfoSun

Build in-house aloneContract it outRun it with InfoSun
Speed to valueSlow ramp: hire, tool, and train firstFast startFast start, on the systems you already run
Who owns the capabilityYou, eventuallyThe vendorYou: playbooks, models, and process transfer to you
Process knowledge and dataStays in-houseAccumulates with the vendorStays in your systems and your data
AI in the operationYou build it yourselfOn the vendor's roadmapAI-native from day one, human-supervised
Measured onEffort and milestonesActivity and SLAsOutcomes against your baseline

India hosts 1,700+ global capability centers, and 83% of GCCs are already engaging generative AI.

NASSCOM and Zinnov India GCC Landscape; EY GCC Pulse, 2025. Market context, not InfoSun results.

How we prove it

You see the number on your own systems

No logos to borrow, no invented results. We prove value the only way that counts: on your baseline, on your dashboards.

  1. 1
    Baseline your numbers

    We measure your current cost, accuracy, and service together at the start, so every target is grounded in your reality.

  2. 2
    Agree the target first

    We set the outcome numbers with you before work starts. No moving goalposts.

  3. 3
    Run it on one site

    We prove the model on a single workflow or site before scaling, so risk stays small.

  4. 4
    Report on your dashboards

    You see the movement on your own metrics, monthly, not on ours.

No rip-and-replace

We run on the WMS, TMS, and ERP you already own.

Human in the loop

AI agents propose, your experts approve. Never a black box.

Start with an assessment

Get the baseline and business case before you commit.

Outcomes, not headcount

Measured on cost, accuracy, and decision speed, on your P&L.

Frequently asked questions

What is emulation in warehouse automation?+

Emulation in warehouse automation is a technique that mimics the real control systems and equipment so the actual WMS and WCS software can be tested against a virtual warehouse. Because it connects to live software, emulation validates real control logic and throughput before any hardware is installed, which reduces go-live risk and rework.

What is the difference between simulation and emulation in a warehouse?+

Simulation models how a warehouse would behave to answer design questions like throughput and capacity, using approximate logic. Emulation connects the real WMS and control software to a virtual copy of the equipment to test the actual software as if hardware were present. In short, simulation validates the design; emulation validates the software and controls.

How do you integrate robotics with a WMS?+

You integrate robotics with a WMS by connecting the robots' control system, often through a WES or WCS, so the WMS can direct work and receive status in real time. InfoSun maps the process flows, builds and tests the interfaces, and runs system integration testing so AMRs, conveyor, and sortation execute WMS instructions reliably and report progress back.

How does a digital twin reduce warehouse automation risk?+

A digital twin is a virtual model of the warehouse and its automation that you run scenarios against before and after go-live. It reveals bottlenecks, validates throughput under peak, and tests changes safely without touching live operations. By proving performance in the twin first, teams avoid costly surprises when the physical system starts.

What is system integration testing (SIT) for warehouse automation?+

System integration testing (SIT) for warehouse automation verifies that the WMS, WES, WCS, and physical equipment work together correctly as one system. It checks that instructions flow, exceptions are handled, and data is traceable end to end across every integrated component. SIT is a key gate for go-live readiness.

How do you validate warehouse throughput before go-live?+

You validate warehouse throughput before go-live using emulation and a digital twin: the real control software runs against a virtual site under realistic order profiles and peak volumes. Engineers measure throughput, find bottlenecks, and run capacity what-if analysis to confirm the design meets targets. Only validated performance moves to live operation.

Written and reviewed by the InfoSun operations team. Last updated July 14, 2026.

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