Opportunity identification
Workshops with business and technical teams to surface use cases tied to real processes and outcomes.
Find the AI opportunities worth pursuing first.
We start with your business problems, not a model or a platform. The result is a short list of opportunities, a realistic view of readiness and a roadmap you can act on.
Problems we address
Too many ideas, no way to choose
Without shared criteria, AI work goes to the loudest request instead of the most valuable one.
Data and systems that are not ready
A good use case still fails if the data is scattered, poor in quality or out of reach.
Value that is never defined
Projects that cannot say how success is measured struggle to justify the next stage of investment.
No plan for running it
Governance, ownership and operations are left until after the pilot, when they are hardest to add.
Capabilities
Prioritisation
Rank use cases by business value, feasibility, data readiness and risk, so the first project is a sensible one.
Data and systems readiness
Assess the data, integrations and platforms a use case depends on, and what must change first.
Architecture and approach
Outline how a solution would fit with your environment on AWS, including security and governance.
Business case and measures
Define the outcomes, costs and indicators that will show whether the work is paying off.
Roadmap and ownership
A staged plan from prototype to production, with clear owners for operating and improving each solution.
How we deliver
Listen
Understand your goals, processes, constraints and where people lose time today.
Define
Turn ideas into well-formed use cases with measurable outcomes.
Assess
Test feasibility against your data, systems and risk tolerance.
Prioritise and plan
Choose the first opportunities and agree the roadmap, roles and governance.
Hand over or continue
Take the plan forward yourselves, or let us prototype and build it with you.
Technical foundations on AWS
We use structured frameworks as guidance, such as the AWS Cloud Adoption Framework, which looks at an AI programme from business, people, governance, platform, security and operations perspectives.
- AWS Cloud Adoption Framework
- Amazon Bedrock
- Amazon SageMaker AI
- Platform choices follow the use case, your data and your skills.
Security, governance and operations
Risk and responsible use
Agree early how risks such as errors, bias, privacy and misuse will be managed.
Clear accountability
Each solution has a business owner and a technical owner.
Human oversight
Decide where people review, approve or override AI output.
Measurement
Quality, cost and business impact are tracked from the start.
Where we apply it
- Energy & Critical InfrastructureData, forecasting and AI for energy operators, from live market and meter data to asset performance and storage optimisation.
- Financial & Business OperationsAI-assisted reconciliation, document processing and customer service for finance, banking, insurance and business operations.
Related services
- AI DiscoveryIdentify where AI can create measurable value in your organisation and agree a practical route from the first opportunity to a working solution.
- Agentic AI & AI AgentsEnterprise AI agents on AWS, integrated with your systems, with controlled tool use, evaluation, security, human oversight and operational monitoring.
- Forward Deployed EngineeringCloudStraight joins architecture and execution: our architects stay close to implementation, validate designs in your real environment and help build through to production.
Have an AI or Cloud challenge to solve?
Let's identify the opportunity and determine the right path to a working solution.
Discuss Your Initiative