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Industries

Every industry runs differently.
We start there.

Where does the data come from. Where does the process get stuck. What jobs keep repeating. What does management actually want to see. Same four questions, different answers in every industry. We start there — then decide whether the first move is IT, data, DR, overseas landing, or a small AI pilot.

How we read an industry

We start with four questions.

Industry buzzwords rarely shape a real project. These four do — where the data comes from, where the process gets stuck, what jobs keep repeating, what management wants to see on Monday morning.

They're not parallel. They stack. Answer all four in your own terms, and the first move — AI, integration, cloud, security or DR — makes itself obvious.

Browse by industry →
TWO TWO · BUSINESS DIAGNOSTIC DIMENSIONS · 4 01 Where data comes from ERP · CRM · OA · POS 02 Where processes stick Approvals · handoffs · reconciliation 03 What jobs repeat Look up · record · verify · chase 04 What management asks Risk · cost · recovery CURRENT FOCUS Data sources ERP orders CRM customers POS in-store OA approvals Support tickets READY RUN Scanning 4 dimensions — dimension 01 focused v2.6
By industry

Look by industry. See where the business gets stuck.

Under each industry isn't a capability keyword — it's our judgment about that industry, and the specific scenarios where you can start.

Financial services

Boundaries first. Efficiency second.

Before AI does anything in finance, three questions come first: who can read what, whose signature is on which approval, and whether the audit trail holds up. Customer data, transactions, compliance reports, internal approvals, service conversations and DR records all live inside carefully drawn permission lines.

Where to start
  • Compliance knowledge base
  • CS & RM assist
  • Approval summaries
  • Audit prep
  • DR drill records
Enter financial services →

Manufacturing & construction

Orders, materials, drawings, equipment and site work must connect.

Data circulates between ERP, procurement, inventory, drawings, QC, site logs, equipment maintenance and after-sales. The first step for AI is often not prediction, but making it faster to find orders, materials, drawings, exceptions and repair history.

Where to start
  • Drawing & doc search
  • Procurement/inventory Q&A
  • QC exception logs
  • Equipment knowledge
  • Project reporting
Enter manufacturing & construction →

Retail & F&B

Stores produce data every day. HQ often can't see it clearly.

Retail and F&B data scatters across POS, membership, e-commerce, delivery platforms, inventory, service and store reports. The real problem isn't whether data exists — it's that HQ, stores, finance and operations see different versions.

Where to start
  • Member segmentation
  • Product Q&A
  • Replenishment suggestions
  • Store daily reports
  • Service knowledge
  • Promo review
Enter retail & f&b →

Logistics & supply chain

More nodes means more need to see status and accountability.

Difficulty in logistics comes from many nodes, systems and owners. Orders, warehousing, transport, customs, deliveries, exceptions and billing sit in different systems. AI should first help teams check status, find exceptions, sort documents and respond to customers — not just build a pretty dashboard.

Where to start
  • Order status Q&A
  • Exception attribution
  • Document organisation
  • ETA lookup
  • Vendor communication
  • Warehouse reporting
Enter logistics & supply chain →

Government & public sector

Fast is good. Explainable is required.

A public-sector project can't just chase automation. Permissions, audit trails, data boundaries, service continuity and long-term maintenance all get defined up front. AI can step into documents, Q&A, internal workflow and knowledge organisation — as long as every step leaves a record a human can go back and check.

Where to start
  • Policy & document search
  • Public Q&A
  • Internal workflow aid
  • Materials organisation
  • Compliance reporting
  • Service desk knowledge
Enter government & public sector →

Energy & utilities

Continuous operation, on-site safety and recovery matter more than a demo.

Energy & utilities depend on continuous operation, field safety and incident response. AI's value here isn't in showcasing capabilities — it's in helping teams find equipment records, inspection history, maintenance procedures, incident case studies and recovery playbooks faster.

Where to start
  • Equipment knowledge base
  • Inspection log search
  • Incident response workflow
  • Compute platform hosting
  • DR drills
  • Operations reporting
Enter energy & utilities →

Real estate & PropTech

Leasing, property, contracts, billing and work orders need to see each other.

Real estate data comes from leasing, sales, property management, customer service, contracts, billing, energy and site work orders. AI can first help teams look up contracts, categorise work orders, respond to tenants and organise reports — not rebuild an entire platform from scratch.

Where to start
  • Tenant Q&A
  • Contract search
  • Work order routing
  • Property service knowledge
  • Energy reporting
  • Operations organisation
Enter real estate & proptech →
How discovery calls go

We don't start blank.
We come with the industry checklist.

We don't open a call with "what AI do you want to do?" We look first at industry, systems, data, process and accountability. Once those are clear, we can decide whether phase one is a data platform, a lightweight AI scenario, system integration, cloud & security, or DR and overseas IT.

These five aren't all covered every time — they set the direction of the conversation. And they help you avoid packaging every problem into one big project.

Book a 30-min call →
TWO TWO · CLIENT INTAKE MEMO 5 / 5 DIAGNOSTIC STACK STEP 05 / ACTIVE 01 · SYSTEMS ERP · CRM · OA 02 · DATA Trust · boundaries · permissions 03 · PROCESS Blocks · error points 04 · ACCOUNTABILITY Use · approve · maintain · on-call STEP 05 · ACTIVE 02 : 47 Pick a first move Move one thing — the one blocking business most Make it work first, then scale Don't wrap every problem into one big project DECISION Move one not all at once Intake completed — awaiting first-move decision READY
Talk to us

Start with the problem. The solution comes after.

A 30-minute call with a solution architect. No spec needed — just tell us where the business is stuck. Systems that don't talk. Data that won't behave. An overseas office with no one running IT. A DR plan on paper that no one has tested. A first AI use case you want to try for real. If we fit, we'll show you the next step. If not, we'll tell you straight.