64ARC Talk to 64ARC
Work

The ecosystem is the work.

A screenshot of one application says very little. What matters is the architecture it belongs to — what it connects, what it replaced, and what the business can do afterwards.

BeforeArchitecturePlatformsIntelligenceOutcome

How to read these

Five questions,
asked of every engagement.

Before — what the business was actually doing, including the manual parts.

Architecture — the structural decision that everything else follows from.

Platforms — the specific experiences built on that structure.

Intelligence — where context-aware AI changed a decision.

Outcome — what the business can now do that it could not before.

Ecosystem models

Four architectures, described end to end.

These are ecosystem models, not client work — four common business shapes and how 64ARC would approach each. Client stories will be published with permission.

Model 01 — Industrial distribution

A dealer network running on phone calls, spreadsheets and an ERP nobody outside the office could reach.

  • ERP
  • Dealer app
  • Warehouse
  • Credit
  • Forecasting

Before

Dealers ordered by phone and message. The sales desk re-keyed each order, called the warehouse for stock and accounts for credit. Stock lived in a spreadsheet updated each evening. Nobody could answer "where is my order" without three calls.

Architecture

One definition of product, price, stock and credit at the centre. The ERP keeps operations; everything else reads from a shared business layer over it rather than keeping its own copy.

Platforms

  • Dealer ordering app with contract pricing and live credit position
  • Warehouse picking and dispatch interface
  • Sales desk console for exceptions and approvals
  • Management view of channel performance

Intelligence

Replenishment suggestions per dealer from their own buying rhythm. Credit-risk flags before an order is accepted rather than after it ships.

Outcome

The status phone call disappears. Orders arrive structured and priced. Stock is one number everyone shares. The sales desk moves from re-keying to handling the exceptions that actually need judgement.

Model 02 — Manufacturing

Production planned from experience, because no system could see demand and capacity at the same time.

  • Planning
  • Shop floor
  • Procurement
  • Quality
  • Demand forecasting

Before

Orders in one system, production tracked on paper and whiteboards, purchasing driven by memory. Shortages were discovered on the line. Planning depended on two people who had done it for fifteen years.

Architecture

Demand, capacity, materials and stock modelled once, so a change in any of them is visible in all of them. Procurement triggered by the plan instead of by recollection.

Platforms

  • Planning board showing demand against capacity
  • Shop-floor application for job status and consumption
  • Procurement workflow driven by material shortfall
  • Quality capture attached to batch and job

Intelligence

Demand forecasting from real order history. Early warning on the items that will run short, with the lead time needed to act on it.

Outcome

Planning stops depending on two memories. Shortages surface weeks earlier instead of at the machine, and what those two people know is written down where the whole team can use it.

Model 03 — Multi-channel retail

An online store that could not be trusted to know whether an item was actually in stock.

  • Ecommerce
  • Stores
  • Inventory
  • Fulfilment
  • Recommendations

Before

The website held its own catalogue and its own stock figure, synced overnight. Stores had a third view. Orders were cancelled after being accepted, and the same product was described three different ways.

Architecture

One product record and one live stock position across every channel. Fulfilment decided by rules rather than by whoever noticed the order first.

Platforms

  • Storefront reading live availability
  • Store application for stock, transfers and click-and-collect
  • Fulfilment console with routing rules
  • Customer account with orders, returns and history

Intelligence

Recommendations from actual purchase history across channels. Stock rebalancing proposals between locations before something sells out.

Outcome

Every channel tells the customer the same thing. Cancellations caused by phantom stock stop. One catalogue change updates everywhere.

Model 04 — Field service

Engineers dispatched by phone, with the customer's history sitting in a filing cabinet.

  • Service
  • Field app
  • Spares
  • Contracts
  • Knowledge

Before

Complaints arrived by phone and were written down. Engineers were assigned by whoever was free. Spares availability was unknown until the engineer arrived. Contract entitlements were checked manually, sometimes after the work was done.

Architecture

The installed base, contract terms, service history and spares stock modelled as one thing — so a ticket knows what it is entitled to before anyone travels.

Platforms

  • Customer service-request portal
  • Engineer field application, usable offline
  • Dispatch and scheduling console
  • Spares stock across vans and depots

Intelligence

Tickets flagged before they breach commitment. Likely part identified from symptom and service history so the van is loaded correctly the first time.

Outcome

Fewer second visits. Entitlement is known before dispatch, history travels with the engineer, and the customer can see where their request stands.

The common thread

Four different businesses. The same structural move.

01

The manual layer is the system

In each shape, people are the integration layer — carrying information between systems that should have been talking to each other.

02

One definition, not one product

The fix is never a single piece of software. It is agreeing what a customer, a product and a stock position mean.

03

Different interfaces, one reality

Dealers, engineers, planners and customers each get their own experience of the same underlying business.

04

AI comes last

Intelligence is worth adding once there is something coherent for it to reason over. That order is what makes it give answers instead of paragraphs.

The pattern

The business does not become more digital.
It becomes connected — and then the digital part starts paying.

Begin

Which of these looks most like your business? Let's map it.

Architect your ecosystem See how 64ARC works

A conversation about your business — not a product demo.