AWS AI, Machine Learning & Generative AI

Build My AI Strategy

Assess your business, data and technology environment and identify practical AI opportunities aligned with AWS.

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The challenge

Where organisations get stuck

Your organisation knows AI is important but isn't sure where to start or which opportunities are worth pursuing.

Money spent on disconnected experiments
Initiatives that never reach production
No shared view of AI priorities

Abstract neural network over compute hardware representing AWS AI and machine learning

How Analytics Hive helps

AWS AI Strategy & Readiness

Analytics Hive assesses your business, data and technology environment and identifies practical AI opportunities aligned with AWS.

What the engagement includes

AI opportunity assessment
AI readiness assessment
Data readiness
Use-case prioritisation
AI architecture strategy
AWS service mapping
AI roadmap
Governance considerations
Business case development

Expected outcome

From AI uncertainty to a prioritised AWS AI transformation roadmap.

What we deliver

Tangible outputs, not slideware

Typical artefacts from a ai & machine learning engagement, tailored to the scope we agree with you.

AI opportunity assessment and prioritised use-case roadmap
AI and data readiness review
Generative AI solution architecture with guardrails
Retrieval-augmented knowledge assistants
Predictive model development and evaluation
MLOps pipelines, monitoring and retraining strategy
Responsible AI governance framework

Our approach

How the work runs

01
Assess
Understand your business objectives, current environment, risks and opportunities.
02
Architect
Design the right AWS target architecture and transformation roadmap.
03
Build
Implement the cloud, data, AI and security capabilities required.
04
Secure
Embed security, governance, resilience and compliance into the environment.

Business outcomes

What the business gains

Technical work only matters when it changes how the organisation performs.

01
Clear AI priorities
02
Realistic business cases
03
A roadmap the organisation can execute

AWS context

Built on AWS-native capability

AI & Machine Learning work at Analytics Hive is delivered on AWS and aligned to the AWS Well-Architected Framework.

Amazon Bedrock and foundation model selection
Amazon SageMaker AI for training and deployment
Amazon Kendra and Amazon OpenSearch for retrieval
AWS Step Functions and Lambda for AI workflows
Amazon Textract, Comprehend and Transcribe
SageMaker Pipelines, Model Registry and Model Monitor
Amazon S3 data lakes as the AI data foundation

Built around enterprise priorities

Security-first
Protect workloads, identities and data with controls designed in from the start.
Scalable
Architect AWS environments that grow with demand instead of constraining it.
Resilient
Design for availability, continuity and tested recovery, not best-effort uptime.
Cost-conscious
Optimise infrastructure spend without compromising performance or resilience.

Next step