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How we work

From one pain pointto a complete system.

Every system we build starts small: one real problem, one tool your team can use straight away. Then it grows module by module on the same data, steered by what your team actually uses.

Discuss your needsWatch a system grow
Start with one pain pointAbout a week per module, plus testingAI drafts, people approve

Custom ERP development walkthrough

How a custom ERP grows, step by step.

This walkthrough combines what we learned building five real systems. Scroll and watch the system map take shape.

  1. 01

    Find the pain point

    Find the one step that costs the most time or causes the most errors, before writing any feature list.

    e.g.hours of manual quoting every day; outlets ordering by chat while the kitchen retypes it all.

  2. 02

    Ship a first working version

    Build one tool that removes that pain and put it in your team’s hands.

    e.g.paste a customer request and get matched products and a quote; turn a recipe manual into live costing and a kitchen screen.

  3. 03

    Connect real data

    Replace sample data with your POS exports, accounting records, email history and supplier catalogues. Real data shows the next problem.

    e.g.reconciling food cost against real purchases led to a purchasing guide.

  4. 04

    Grow along the business chain

    Each new module reuses the same records: quote → order → purchase → stock → production → dispatch → invoice → payment.

    e.g.one project number links every email, attachment, quote, purchase order and invoice.

  5. 05

    Meet people where they work

    Staff apps, customer and distributor portals, websites, voice and chat, all on one database.

    e.g.staff forward an assessment report from their phone, confirm prices, and the quote and accounting draft are ready.

  6. 06

    Put AI into daily work

    Reading photos and PDFs, matching products, drafting orders and replies, daily briefings, quality checks. AI drafts, people approve.

    e.g.photograph a handwritten stock count and AI reads it; photograph a plate and AI checks it against the recipe.

  7. 07

    Keep improving, and prune

    Review every month: strengthen what gets used, remove what doesn’t, and change course when the real bottleneck turns out to be elsewhere.

    e.g.one project dropped online ordering once the real bottleneck turned out to be outlets ordering from the central kitchen.

System map

A complete system

20modules live

Starting point
Spreadsheets, chat and retypingreplacedFirst tool: quotes & orders
Real data
POS salesAccountingEmail historySupplier catalogues
Business chain
PurchasingStock & warehouseProductionDispatchInvoicing & paymentsQuality records
Channels
Staff appCustomer & distributor portalsWebsiteOnline orderingremoved
AI
AI assistant with voicePhoto & PDF readingProduct matchingDaily briefingQuality checks
Owner’s view
Today’s decisions board & monthly review

Illustration: the modules are chosen for each business.

From real projects

Five systems, one way of growing.

Different industries and starting points, yet each began with one pain point and grew step by step. Client names stay confidential.

Manufacturing · Export

An LED lighting manufacturer and exporter

Started withOnly a company deck and a PDF catalogue, and a need for a website that could take enquiries and orders.

  1. Catalogue & AI chat
  2. Distributor portal
  3. iOS & Android apps
  4. Quote workflow instead of a cart
  5. 3D lighting simulator
  6. Factory ERP: BOM, MRP, work orders, QC, export tax refunds
  7. Staff AI assistant

What we learnedOne product dataset feeds the website, portal, apps, AI chat and ERP, and the website is now published from the ERP.

Food service · Central kitchen

A restaurant group with a central kitchen

Started withAn owner who wanted today’s decisions, not reports. The first version was a “Today” decision screen, stocktakes that become purchase orders, and a link to the existing POS.

  1. Multilingual website
  2. Staff iPhone app
  3. AI dish checks
  4. FIFO batches with QR labels
  5. Outlet ordering from the kitchen

What we learnedThe real bottleneck surfaced later: outlets ordering from the central kitchen. Online ordering went to delivery platforms so we could focus there.

Food service · Franchising

A café brand preparing to franchise

Started withA recipe and costing manual in a PDF, and a kitchen team speaking many languages. The first version turned it into costing, a multilingual kitchen mode and inventory.

  1. Website & franchise enquiries
  2. Roles & purchasing
  3. Staff apps & voice
  4. Real POS data
  5. Owner briefing
  6. Purchasing guide
  7. AI dish checks

What we learnedEach real dataset revealed the next module to build.

Distribution · Care

An aged-care and mobility equipment supplier

Started withEvery quote was manual: read the email, find products, chase suppliers, work out freight and margin. The first version was an AI quote assistant.

  1. Reading assessment reports
  2. Email history & project tracking
  3. Accounting integration
  4. Purchasing, stock & warehouse
  5. Payment reminders
  6. Customer portal & mobile quoting

What we learnedQuote first, then follow the document chain. Nothing goes out without staff approval.

Founders · Small business

An AI platform for founders and small businesses

Started withOne AI digital employee with a knowledge base.

  1. Specialist AI employees
  2. A guided step-by-step journey
  3. Billing & an operator console
  4. iOS app
  5. Website builder & media studio
  6. Worker machines for heavy jobs

What we learnedExpand, then prune: after a usability review, whole features were removed and the product got easier to use.

Descriptions are anonymised. Some systems are still in pilot or demonstration, and none of this is a claim of verified business results.

Our principles

Six rules these projects taught us.

Fix the costliest problem first

Not a feature list, but the step that wastes the most time or causes the most errors.

Use it first, then refine

Get a working version into your team’s hands, then refine it with real feedback.

One database, many doors

Website, apps, portals, chat and ERP share one set of data, so nothing is typed twice.

Every module serves a decision

Late orders, skipped batches and failed checks all become today’s decisions for the owner.

AI drafts, people approve

AI drafts quotes, purchase orders, emails and replies. Staff approve before anything is sent.

Be willing to remove

Remove what nobody uses, and change course when the real bottleneck is elsewhere.

Working together

From diagnosis to ongoing support.

  1. Diagnose

    Map pain points, current tools, team responsibilities and data, then define success.

  2. Design

    Agree priorities, scope, budget, integrations and a phased roadmap.

  3. Deliver

    Build and integrate, validate with a pilot, train the team and roll out in stages.

  4. Improve

    Maintain the system, measure outcomes, update knowledge and evaluate the next useful improvement.

  • About a week per module, plus testing
  • A monthly review and report
  • Monthly terms; stop with notice before month-end

Tell us the problem that hurts most.

Together we’ll sketch the first working version and how it could grow into a complete system.

Discuss your needsinfo@optiviseai.com.au