Systems that run real operations.

Plant ERPs, warehouse vision and booking engines that run every shift. Each case shows what the system does, the features that matter on the floor, and the engineering that makes it hold up.

On the floor today

Across client plants
  1. Machine stop timed, with the reason tapped in by the operatorDowntime trackingJust now
  2. Supplier batch put on hold before the next jobAuto-hold on bad batches4 min ago
  3. Hindi voice note read into an order for 300 unitsWhatsApp order intake11 min ago
  4. Dock 2 loaded 23 of 24 cartons, so the truck was held at the gateDock camera check26 min ago
  5. Raw-material batch flagged: waste climbing to 7.8% on every jobWaste drift detection48 min ago

Representative events from client systems, with identifying details removed.

Plant dashboard
Factory TV board
Live view
On site
Engineers work on the client’s floor, not from a slide deck
Built around you
Shaped to how each operation already runs, not an off-the-shelf ERP
Under NDA
Client names, customers and figures stay private
Yours to keep
Code, infrastructure and data transfer to the client
Client confidentiality

What we can show, and what we can’t.

Almost everything we build runs inside our clients’ operations under non-disclosure agreements. Customer lists, pricing, supplier terms, production volumes and staff details belong to them, and publishing those would break both their trust and our contracts.

So client names are withheld, every screen on this page has been sanitised, and brand marks are removed. Names, phone numbers, figures and identifiers are masked or replaced with representative values. What you see is the real software as it looks on the floor, with the private parts taken out.

  • Real product screens, captured from the running systems
  • Client names withheld, brand marks removed
  • Customer, supplier and staff details masked
  • Full walkthroughs for serious prospects, on a call, under NDA

Plants & warehouses

The factory floor, as one live system.

Each system replaces registers, phone calls and month-end surprises with a single source of truth: orders read straight from WhatsApp, material traced to the batch, waste explained as it happens, and vision AI on the cameras the plant already owns.

Waste controlOrder-to-dispatch operating systemMaterial balance on every job

Every order, every kilo of raw material, every rupee of waste, accounted for in real time.

Web console · WhatsApp Business API · English & Hindi

Orders arrived as WhatsApp messages, production lived in registers, and material loss surfaced only at month-end stock-taking.

We engineered an order-to-dispatch operating system that models the plant as a single event stream: from the raw-material batch a job was drawn from, through every machine and furnace cycle, to the truck and LR number it left on.

Workspaces
Role-scoped consoles for owner, order desk, production, operator, store and dispatch
Assets modelled
Production machines and batch furnaces, each with its own queue and cycle time
Channels
WhatsApp Business API, server-rendered PDF digests, Excel OS sheets
Languages
English and Hindi, switchable per user
Live view

Recorded in use: the waste alert on the owner’s live view opens straight into the root cause, batch by batch.

Sanitised screen, with customer names, contacts and figures masked

How an order moves through the system

  1. 1

    Order intake

    WhatsApp orders parsed into size, grade, quantity and due date, then accepted at the order desk.

  2. 2

    Material reservation

    Stock is matched against raw-material batches, oldest first; shortfalls raise purchase requests.

  3. 3

    Machine scheduling

    Jobs sequenced across machines by size changeover and due date.

  4. 4

    Process cycles

    Furnace cycles tracked per batch, with dwell-time alerts.

  5. 5

    Dispatch

    Trucks loaded against orders; LR number and invoice pushed to the customer on WhatsApp.

  6. 6

    Close the loop

    Payments chased, waste costed, and an 8 pm digest delivered to the owner.

What makes it hold up

Material balance per job

Waste is never estimated. Every job closes material issued against material returned and good output, so loss is attributable to a batch, a machine, a shift and an operator.

Drift detection on batches

A statistical watch on per-batch waste caught one batch climbing 3.4% → 7.8% across five jobs, priced the overrun and projected the cost of continuing.

Leakage ledger

Idle leftover stock, machine stops and unaccounted material are each valued in rupees, so the owner sees where margin is leaking, ranked, every week.

Plant ERPProcess-plant ERPBatch genealogy, quality and automations

From raw-material yard to dispatch bay: a process plant run batch by batch on one system.

Web console · offline Android app · iOS from one codebase

The plant runs a multi-stage process line from raw material to finished product. Sales, production, quality, maintenance and environmental compliance each lived in separate sheets.

The ERP we built connects them. Every batch carries its input mix, power, chemistry and lab results from the first stage to the test certificate, while CRM, credit, procurement and finance run on the same data. One codebase ships as a web console and an offline-capable Android app.

Process
Multi-stage line from charging to weighbridge dispatch, tracked per batch
Modules
CRM and sales through waste & environment, workforce safety and automations
Surfaces
Web console, offline Android app, iOS from the same codebase
Compliance
Test certificates per batch, hazardous-waste register, stack emission limits
Plant dashboard
The plant dashboard with the line live: unit states, temperatures and grades per batch, output against the daily target and a prioritised attention queue.

The plant dashboard with the line live: unit states, temperatures and grades per batch, output against the daily target and a prioritised attention queue.

Sanitised screen, with customer names, contacts and figures masked

What makes it hold up

Batch genealogy

Each batch links input mix, power, chemistry and lab results to the products it became, so a certificate or an NCR traces back to its source in one step.

Trigger → condition → action

Automation rules with on/off control and run-now. Every run is logged, auditable and raises the right notification.

Credit-aware selling

New orders preview the customer’s credit exposure live. Over-limit orders are held and routed to finance before they ever reach production.

Order intake AIManufacturing execution systemMultimodal orders and batch root cause

A multi-line plant, scheduled, metered and explained as it runs.

Factory TV board · 8 pm owner PDF · English & Hindi

The plant runs several production lines making short-run custom orders for many buyers. Orders arrive as WhatsApp text, purchase-order PDFs and Hindi voice notes.

The system converts each order into a costed job on the right line, meters material consumption by supplier batch, runs root-cause analysis when waste drifts, and keeps the owner, the customer and the floor working from the same live state.

Lines
Several production lines, each with its own job queue and changeover rules
Order intake
WhatsApp text, PDF purchase orders and Hindi voice notes, read by AI
Outputs
Factory TV board, 8 pm owner PDF, Excel OS sheet, supplier claims
Languages
English and Hindi
Live view
Plant live view: order stages, waste against the 4% target, extra material cost, savings to date and an exceptions queue. The batch alert was raised and the batch put on hold automatically.

Plant live view: order stages, waste against the 4% target, extra material cost, savings to date and an exceptions queue. The batch alert was raised and the batch put on hold automatically.

Sanitised screen, with customer names, contacts and figures masked

How an order moves through the system

  1. 1

    Multimodal intake

    Text, PDF POs and Hindi voice notes extracted into SKU, quantity and due date.

  2. 2

    Stock check

    Finished goods go straight to dispatch; otherwise raw material is reserved by batch.

  3. 3

    Line allocation

    Jobs assigned to the best-fit machine, or a purchase request raised for what is short.

  4. 4

    Operator actuals

    Material issued, good pieces, leftover, scrap and downtime logged per job.

  5. 5

    Dispatch & billing

    LR on WhatsApp, invoice generated, payment reminders until settled.

  6. 6

    Owner intelligence

    Instant alerts, the 8 pm PDF and the TV board, always in sync.

What makes it hold up

Voice and PDF understanding

Hinglish voice notes and scanned purchase orders become structured line items. Low-confidence extractions route to a person instead of guessing.

Auto-hold on bad batches

When waste on a supplier batch drifts beyond control limits, the batch is held for new jobs, the likely cause is named and the rupee exposure is quantified.

Supplier claims, pre-built

Out-of-spec consumption is packaged into a claim against the supplier with job-level evidence, instead of being written off.

BOM engineFactory operating systemBOM-driven allocation and lot traceability

Materials, sizes and lead times: a factory run from WhatsApp order to challan.

Desktop · mobile · factory TV · English & Hindi

The factory makes a multi-size product range across several lines. Orders arrive from distributors and retailers as WhatsApp text, PDF purchase orders and Hindi voice notes like “teen sau piece, bees tarikh tak”.

The system reads each order, allocates finished goods size by size, checks the remainder against every article’s bill of materials, raises work orders across the production stations and tracks raw material by supplier lot, through to the truck, the LR and the payment.

Intake
WhatsApp text, PDF POs and Hindi voice notes, with quantity and date understanding
Floor
Cutting presses, assembly and finishing stations
Material
Supplier-lot traceability, leftover matching, supplier claim letters
Surfaces
Desktop, mobile and factory TV, in English and Hindi
WhatsApp orders

Recorded in use: an order read from WhatsApp is accepted, routed to production, and the next voice-note order is already read.

Sanitised screen, with customer names, contacts and figures masked

What makes it hold up

BOM-driven allocation

Accepting an order allocates finished goods by size, explodes the remainder through each article’s bill of materials with scrap allowance, then issues material or places a material hold with a draft requisition.

Self-releasing holds

Receiving a requisition re-checks every held order and releases whatever can now be built, automatically.

Lot forensics

Cutting waste is tracked per material lot, press and shift. A lot measuring under spec drove waste from 5.6% to 10.4%; the system held it and drafted the supplier claim.

Compliance ERPGMP-grade plant ERPLot-wise stores, batches in process and downtime

Regulated-grade control: lot-wise stock, every batch in process and every minute of downtime.

Store keeper’s phone · operator tablet · owner’s WhatsApp

A regulated manufacturer ran stores, production and accounts on disconnected Excel sheets, and physical stock rarely matched the books.

The ERP gives each person one simple screen (three big buttons on the store keeper’s phone, two taps on the operator’s tablet, a four-line WhatsApp to the owner at 8 pm) while the office sees lot-wise inventory with GMP status, every batch on the process line, downtime by cause and cash flow weeks ahead.

Process
Dispensing → processing → separation → drying → QC → packing, tracked per batch
Compliance
GMP lot states (quarantine, under test, released, rejected); FIFO issue of released lots only
Integrations
Existing accounting and HR systems, with two-way sync
Team surfaces
Store keeper’s phone, operator’s tablet, owner’s WhatsApp
Home
The plant home: stock accuracy, batches in process, machine time lost and late receivables, each with a red, amber or green state and a direct route to the fix.

The plant home: stock accuracy, batches in process, machine time lost and late receivables, each with a red, amber or green state and a direct route to the fix.

Sanitised screen, with customer names, contacts and figures masked

What makes it hold up

Blind cycle counts

Store keepers count one lot at a time without seeing the system figure. Variances post with a reason and feed a stock-accuracy trend.

Quality-gated issue

Only QC-released lots can be issued, oldest first. A batch waiting on an unreleased lot shows as stuck, with the lot that unblocks it.

Cash visibility

Actual inflow and outflow, a forward forecast, receivables by age and one-tap reminders.

Order trackingMulti-department plant ERPOne order thread across every department

Raw material to container: a multi-department plant on one live order thread.

Live machine map · quality · water & energy

The plant takes every export order through several departments, each with its own machines and backlog, before it ships in a container.

The ERP follows each order on one production thread, checks delivery feasibility against materials and machine backlog before a date is promised, maps every machine live from the monitoring system, and tracks quality, maintenance, water, energy and effluent against regulatory limits.

Departments
Every stage from raw material to packed goods on one order thread
Shop floor
Live machine map from PLC data loggers, breakdown reporting
Quality
Inspection scoring, defect Pareto, sample approvals
Sustainability
Water per kg of output, effluent against pollution-board limits, power mix
Plant overview
The plant overview: output this shift, machine efficiency against plan, the open order book, on-time delivery and water per kilogram of output, with daily output by department.

The plant overview: output this shift, machine efficiency against plan, the open order book, on-time delivery and water per kilogram of output, with daily output by department.

Sanitised screen, with customer names, contacts and figures masked

What makes it hold up

Can-we-deliver engine

Before a date is promised, the availability check tests raw material, consumables and machine backlog, and returns the earliest realistic ex-factory date.

One order thread

Each order carries one thread from raw material to container, so order health (on track, at risk, delayed) is computed rather than reported.

Compliance built in

Water, energy and effluent are tracked per department against statutory limits, ready for the audits export buyers run.

Vision quotingQuote-to-install systemPhoto to priced quote to build plan

From a WhatsApp photo to a priced, scheduled, fabricated install, before the event date.

Worker PWA · client tracking page · WhatsApp updates

The studio designs and fabricates custom installations in metal, wood, fibre and finishes. Clients send a reference photo on WhatsApp and expect a price the same day, and every event date is an immovable deadline.

The system reads the photo into priced elements, builds the quote from a live rate card with labour hours and margin, and on advance payment generates the bill of materials, stock reservations and a build plan scheduled backwards from the event date. When a job is at risk, it proposes the fix.

Quoting
Vision reads the reference image into elements, priced from the rate card
Planning
Build plan scheduled back from the event date across every trade stage
Floor
Worker phone screens in the local language: timers, material logs, progress photos
Client
Live tracking page and WhatsApp updates; installable PWA
Quote

Recorded in use: a client’s reference photo is read into elements, and each one is sized and priced from the rate card.

Sanitised screen, with customer names, contacts and figures masked

What makes it hold up

Image to bill of materials

Approved elements become a bill of materials, stock reservations and a purchase list for whatever is short.

Deadline-aware scheduling

Work is scheduled back from each event date, crew capacity is modelled per person, and risk is recalculated as hours are logged.

Leakage analysis

Quoted against actual by job, stage, worker and material. Painting and finishing running 38% over estimate surfaced as the first fix.

Vision AIWarehouse operating system with CCTV visionShelf counts, dock checks and staff tracking

Every order, carton and camera in a distribution warehouse, on one screen.

Office console · dispatch wall board · tracking page · face kiosk

The client stocks a large SKU range for a dealer network. Orders arrived on WhatsApp, picking ran on paper, and the warehouse cameras recorded everything while nobody had time to watch them.

We built the warehouse operating system and wired the existing camera network into it. Dealer orders flow from WhatsApp through pick, pack and dispatch; rack cameras count stock on every shelf against the books; dock cameras check cartons loaded against the invoice; and staff are placed on a live floor map by camera re-identification and checked in by face.

Cameras
Existing CCTV across gate, receiving, racks, packing and docks, with AI overlays on the live wall
Vision
Shelf counting, carton-vs-invoice checks at docks, ANPR at the gate, staff re-identification, face check-in
Operations
WhatsApp order inbox, pick & pack, stock, purchases, returns, dispatch, receivables, margins
Surfaces
Office console, dispatch wall board, dealer tracking page, face-sign-in kiosk
Live cameras

Recorded in use: the live camera wall, then the receiving dock up close, with AI detections counting people and cartons.

Sanitised screen, with customer names, contacts and figures masked

What makes it hold up

Cameras that do inventory

Rack cameras recount every shelf every 15 minutes, so a missing box is caught the same shift with its bin, value and the footage around it.

Loading checked against the invoice

Dock cameras count cartons onto each truck and raise a short-loading alert before it leaves, not after the dealer complains.

People, placed and verified

Staff are located by camera re-identification, checked in by face, and flagged when a vest is missing in a forklift zone.

Vision AIRuns on existing CCTVInventory

The plant’s existing CCTV cameras, turned into a stock auditor that never sleeps.

CCTV stock counting

On every shop floor, book stock and physical stock drift apart: material parked in the wrong bay, pallets moved without an entry, finished goods counted once a month.

We run object-detection models on the plant’s existing CCTV streams, count pallets, bundles and units per floor zone every few minutes, and reconcile each count against book stock in the plant ERP. A variance raises an alert with the camera frame attached.

  1. 1Ingest. RTSP streams pulled from the existing NVR. No new cameras.
  2. 2Edge inference. Detection runs on an on-premise GPU box, so footage never leaves the plant.
  3. 3Zone counting. Per-camera zone polygons, multi-frame smoothing for occlusion, cross-camera de-duplication.
  4. 4Reconcile. Counts compared with book stock per SKU class and zone.
  5. 5Alert. Variance pushed to the store keeper on WhatsApp with the snapshot as evidence.
ZONE A 4.5 × 1.5ZONE B 4 × 1.2ZONE C 6 × 2CAM-03 STOCK YARD BAY BREC 18:11:54stock-det v4 edge GPU 12 fpsCOUNT 00 / 36
Live reconciliationCounting
ZoneSeenBookStatus
Zone A 4.5 × 1.5012…
Zone B 4 × 1.2012…
Zone C 6 × 2012…
Vision AICCTV plus machine signalsFloor safety & uptime

Every workstation watched for stoppages, absence and safety, escalated in seconds rather than at shift end.

Worker station alerts

A machine idle for twenty minutes, or an operator away from a running press, usually goes unnoticed until the shift report.

We combine CCTV presence and PPE detection with machine run signals to watch every station continuously. Each event climbs an escalation ladder (operator, then supervisor, then plant head), each step on WhatsApp with a live snapshot and an acknowledgement timer.

What it detects

  • Operator absent from a running machine
  • Machine stopped without a reason code
  • Helmet or gloves missing in a marked hot zone
  • Unauthorised entry into a danger zone
  • Station idle beyond its SLA
Floor plan, 12 stationsWatching
ST-01
ST-02
ST-03
ST-04

Operator away

ST-05
ST-06
ST-07
ST-08
ST-09
ST-10
ST-11
ST-12
Live incident
ST-04Operator away

Offset press 1: Press running, operator absent for 6 min. Snapshot attached.

  1. Operator
    0:00
  2. Supervisor
    +2 min
  3. Plant head
    +10 min

Each rung is a WhatsApp alert with an acknowledge button.

Resolved
  • ST-10 Idle beyond SLA, Anil (QC lead)Acknowledged in 0:48
  • ST-12 Danger-zone entry, Imran (dispatch)Acknowledged in 1:12
  • ST-07 Stopped, no reason, Manoj (shift lead)Acknowledged in 0:31

Ticketing & bookings

Built for the minute tickets open.

High concurrencyMulti-venue booking engineSeat holds, scheduling and payments

A multi-venue box office, rebuilt as one booking engine.

Android · iOS · PWA · box-office POS · gate scanner

The operator runs multiple venues from one HQ. We built its ticketing and programming platform: customer apps for Android, iOS and the web, an HQ command centre for programming, pricing and revenue, a box-office POS and a dedicated gate-scanner app.

Every surface runs from one React Native codebase and one booking engine, engineered for release-day demand when thousands of people want the same seats in the same minute.

Surfaces
Customer app (Android, iOS, PWA), HQ command centre, box-office POS, gate-scanner app
Network
Multi-venue, managed from one HQ
Stack
React Native (Expo), Node.js, PostgreSQL, Redis, Razorpay, AWS
Assurance
Concurrency tests against real PostgreSQL, k6 release-day load test
Discovery
Customer discovery: HQ-curated hero slides, now showing and coming soon, filtered by venue, genre and language.

Customer discovery: HQ-curated hero slides, now showing and coming soon, filtered by venue, genre and language.

Sanitised screen, with customer names, contacts and figures masked

What makes it hold up

A seat cannot be sold twice

Holds are one transaction: rows locked in a fixed order, then a single conditional UPDATE. With 40 concurrent buyers racing for one seat, exactly one wins.

Shows cannot overlap

A PostgreSQL exclusion constraint on screen and time range, buffers included. With several HQ schedulers booking the same slot, exactly one show is created.

Payments are never lost

Callback, webhook and a minute-by-minute reconciler converge on one idempotent confirmation path. Late UPI payments are revived or refunded automatically.

Tickets admit once

Signed QR codes with single-use check-in at the gate. Tickets share on WhatsApp through signed links, and copies are refused after first entry.

Commerce, education & lifestyle

Platforms people use every day.

Storefronts, marketplaces, admissions platforms and booking products, each designed around the business behind it.

D2C storefront screenCommerce

D2C storefront

A direct-to-consumer brand built end to end: catalogue and curated discovery, a build-your-own set configurator with combinatorial pricing, a rules-based promotions engine evaluated at checkout, and WhatsApp-native support.

StorefrontSet configuratorPromotions engine
Delivery platform screenMulti-vendor commerce

Delivery platform

On-demand delivery across customer and operator: catalogue and ordering, an order-tracking state machine from basket to doorstep, and a back-office console for inventory, slotting and fulfilment. Android and web.

OrderingLive trackingFulfilment console
Listings marketplace screenMarketplace

Listings marketplace

A two-sided listings marketplace: rich listings, faceted search, geospatial map discovery, agent lead routing and an inventory administration console.

Faceted searchMap discoveryLead routing
Admissions platform screenEducation

Admissions platform

An admissions platform: syllabus-level course catalogue, student portfolio gallery, faculty credentials and dual-channel enquiry capture (WhatsApp and callback) feeding the admissions pipeline.

Admissions funnelCourse catalogueLead capture
Programmes & results platform screenEducation

Programmes & results platform

An institute platform spanning school boards and competitive exams: programme listings, published results, faculty profiles and enquiry routing to admissions counsellors.

ProgrammesResultsEnquiry routing
Premium booking experience screenBookings

Premium booking experience

A premium booking experience: destination discovery, room inventory and selection, a multi-step booking flow and itinerary management, designed to feel like the brand rather than a form.

Room inventoryBooking flowItineraries
Membership & training app screenMemberships

Membership & training app

A retention-led membership product: structured training programmes, an exercise library, guided session timing, progress tracking and membership management for the operator.

ProgrammesProgress trackingMemberships

Your operation could be the next case study.

Our engineers come on site, map how work actually moves, and build the system around it. You own the code, the infrastructure and the data.

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