Practice 03 of 04
AI Foundation
Data that agents can reach with the right permissions, the platform on Azure or AWS, and the security and governance around it.
An agent is only as useful as the data it can reach and the controls around it. We build that layer once on Azure or AWS, and each new agent reuses it.
AI Foundation
What the work covers
Data foundation
Pipelines and stores on Azure or AWS that agents can query, with permissions carried over from the source systems.
AWS AI and dataSearch and retrieval
Retrieval over your documents and knowledge bases that respects who may see what and cites its sources.
Enterprise RAG systemsAI platform
Azure OpenAI or Amazon Bedrock set up in your own tenant, with model access and logging under your control.
Identity and security
Each agent gets its own identity and least-privilege access, reviewed with your security team before launch.
Security and complianceGovernance and evaluation
Evaluation sets and audit trails, mapped to what the EU AI Act asks of companies that deploy AI.
AI governanceDigital workplace
Intranets and Microsoft 365 workplaces that make company knowledge easy to find for people and for agents.
Intelligent workplace hubProof
Work we can show you
Global healthcare organization · AWS
90+ processes
Sales workflows on AWS data. The business data sits in a shared foundation on AWS, so other applications and analytics reuse it.
Read the case studyRockwell Automation
12 min → under 4
Time to find information after we rebuilt the intranet and its search for 28,000 employees.
Read the case studyHow an engagement starts
From the first call to a workflow in daily use.
Every engagement starts with one scoped workflow and a written definition of done. Commercial terms are set in the statement of work.
- First call
A conversation with our team
You tell us about the program or the workflow you have in mind, the systems involved and who checks the work today.
- Scoping
One scoped workflow
We agree which workflow comes first and what done looks like for it: the inputs, the outputs, the accuracy it must reach and where a person approves the result.
- Before the build
A written definition of done
The acceptance criteria go into the statement of work with the deliverables and the commercial terms. Nothing is built before both sides sign.
- Delivery
Build, then run or hand over
We build in your environment and test against the criteria you signed. Then we run the workflow for you, or your own team takes it over with the documentation.
Go deeper
Related pages
- AWS AI and dataBedrock workflows and governed data on AWS.
- Enterprise RAG systemsCited answers from your own knowledge.
- What is enterprise AI searchA guide to permission-aware search.
- Security and complianceHow we build to SOC 2, HIPAA and GDPR standards.
- Microsoft partnershipMicrosoft Solutions Partner, Microsoft partner since 2015.
Planning an AI program?
Talk to the team that builds it and runs it after launch.
- Built to SOC 2, HIPAA and GDPR standards
- EU AI Act-aligned delivery
- Microsoft Solutions Partner