Build with AWS AI
Engagements
AI Readiness Assessment
We review your AWS environment, data sources, and candidate use cases. The output is a ranked build plan: what can go to production now, what needs data or infrastructure work first.
Data Foundation Engineering
Pipelines, vector storage, embedding strategy, access controls, and a governed data layer for the AI workloads that follow. For organisations whose data sits across disconnected systems or in formats foundation models cannot consume.
Use Case Build
One defined use case, from architecture through production. Model selection on Bedrock, fine-tuning where the use case requires it, evaluation metrics, human review checkpoints, and handover documentation.
Agentic AI Deployment
Multi-step agents that reason across tools, hold context, and execute workflows with guardrails. Policy enforcement, monitoring, evaluation loops, and escalation paths built into the deployment.
AWS AI services we work with
QED42 works across the AWS AI stack — selecting the right services for the use case, not defaulting to the same stack for every client.
01
Amazon Bedrock
Foundation model access with enterprise security. We use Bedrock for RAG implementations, knowledge bases, content workflows, and agent orchestration. We select from the full range of foundation models available on Bedrock, matching model capabilities to the use case rather than defaulting to one provider.
02
Amazon Bedrock Agents
Production infrastructure for autonomous agents. Tool access, memory, session isolation, and governance for agents that operate across enterprise systems.
03
Amazon Q
Enterprise knowledge assistant. We connect Q to your existing data sources, fromcontent systems and business applications to databases and internal tools, soteams get answers from organisational data. Similar to what our product Aeldris does.
04
Document and language processing
Textract for document extraction and Comprehend for entity recognition, sentimentanalysis, and classification. These services feed into larger pipelines for intakeautomation, content routing, and compliance workflows.
05
Amazon SageMaker AI
Infrastructure for fine-tuning and deploying models where Bedrock's managedoptions do not meet the use case requirements. We use SageMaker AI for customtraining jobs, model evaluation, and hosting endpoints that need dedicatedcompute.
Why QED42 for AWS AI
We build the systems AI runs on
Content platforms, customer-facing applications, enterprise websites. QED42 has delivered platform engineering for 18 years. When we add AI to a system, it shows up where editors and end users already work.
Fine-tuning, not model training
We select from the foundation models on Bedrock and fine-tune smaller LMs where a specific task demands higher accuracy. We do not train models from scratch. The value is in getting the right model to perform well on your data.
Leading the Drupal AI initiative
Drupal powers content infrastructure for governments, universities, publishers, and large enterprises. QED42 leads the innovation workstream that defines how AI integrates with that ecosystem at the architecture level.
Human review at every decision point
Every system we deploy has defined points where a person reviews, approves, or overrides AI output before it reaches an end user. That is the design principle, not a feature toggle.
In practice
Why most AI pilots never reach production
The gaps that stall AI projects between a working demo and a deployed system. Data quality, integration, monitoring, governance, and team adoption. Applies whether you are on Azure, AWS, or both.
Common questions
What does it take to make enterprise data ready for Amazon Bedrock?
How do Amazon Bedrock costs scale from pilot to production?
When should we use RAG on Bedrock versus fine-tuning a model?
How does Amazon Bedrock handle data privacy and security?
How do you select the right foundation model on Bedrock?
What does it take to deploy AI agents on AWS in production?
How long does it take to go from use case to production on AWS AI?
Bring your use case, we will build it
Not sure where AI fits? We will help you figure that out