Industries

Where these systems tend to earn their keep.

The patterns below describe applicable cloud and AI use cases by sector. They are illustrative of what we build, not a claim about existing customers in each industry.

Financial services

High regulatory load, long-lived core systems, and pressure to serve customers digitally without widening the risk surface.

Applicable use cases

  • Document intelligence for onboarding and verification
  • Knowledge assistants over policy and product documentation
  • Cloud security posture and evidence collection for audit
  • Modernisation of batch processes to event-driven services

Design constraint

Data residency, auditability and least-privilege access are design inputs from the first session, not a review at the end.

Education

Seasonal load patterns, constrained budgets, and growing volumes of learner and content data.

Applicable use cases

  • Learner and staff support assistants grounded in institutional content
  • Cost optimisation for workloads with sharp seasonal peaks
  • Content and assessment document processing
  • Migration of on-premise learning platforms to AWS

Design constraint

Learner data protection and predictable cost under variable demand shape most decisions.

Healthcare

Sensitive data, strict access requirements, and clinical and administrative processes that are still largely manual.

Applicable use cases

  • Administrative document processing and summarisation
  • Internal knowledge assistants over protocols and procedures
  • Secure data platforms with strict access separation
  • Reliability and disaster recovery for critical systems

Design constraint

Access control, data minimisation and human review of anything that reaches a clinical context.

Professional services

Expertise held in documents and in people's heads, with billable time lost to retrieval and drafting.

Applicable use cases

  • Knowledge assistants over precedent, policy and prior work
  • Contract and report document intelligence
  • Workflow automation across practice management systems
  • Engineering support for client-facing digital products

Design constraint

Client confidentiality boundaries must hold inside retrieval, not only at the application layer.

Retail and e-commerce

Traffic that spikes hard, thin margins, and customer expectations set by much larger competitors.

Applicable use cases

  • Customer service agents with order and account context
  • Semantic product search and merchandising support
  • Cost optimisation and autoscaling for peak trading
  • Platform migration and modernisation ahead of growth

Design constraint

Peak-load behaviour and per-transaction cost matter more than average-case performance.

Technology companies

Product teams that need to ship AI features without diverting their whole roadmap into infrastructure.

Applicable use cases

  • AI-native features built into an existing product
  • Platform engineering and golden paths for delivery teams
  • Evaluation and observability for AI components
  • Multi-tenant architecture and cost attribution per customer

Design constraint

Unit economics and the ability to change model or provider later are usually the deciding factors.

Public sector

Legacy systems, procurement constraints, and services that must remain accessible to everyone.

Applicable use cases

  • Citizen-facing information assistants grounded in official content
  • Form and application document processing
  • Application modernisation with phased migration
  • Governance, logging and transparency controls

Design constraint

Accessibility, transparency and the ability to explain an automated decision are non-negotiable.

Logistics and operations

Coordination across many systems and parties, where delays compound and visibility is partial.

Applicable use cases

  • Workflow automation across scheduling, tracking and billing systems
  • Operations agents that triage exceptions and gather context
  • Document intelligence for consignment and customs paperwork
  • Event-driven architecture for real-time visibility

Design constraint

Integration breadth and graceful behaviour when an upstream system is unavailable.

Not sure where you fit?

Sector matters less than the constraint you are hitting.

Most engagements start with a conversation about the specific problem — a stalled proof of concept, a cloud bill nobody can attribute, a release process that has become the bottleneck.

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