back to epiuse.com
 
Contact
AWS AI Services Competency

AWS AI Solutions From generative to agentic AI on AWS

Move from isolated AI pilots to secure production systems that act across ERP, finance, and operations.

Talk to an AI Expert
AWS AI Services Competency badge
  • 42+ yearsOf enterprise technology experience
  • 170+ clientsGlobally
  • Part of Group Elephant4,000+ professionals in 42 countries
The problem

AI pilots are easy to start and hard to scale.

  1. Stuck in pilot

    Proof of concept show promise but never reach production.

  2. Data not ready

    Use cases stall when data is not prepared or accessible.

  3. Privacy and control

    Leaders need models to run in private, governed environments.

  4. Disconnected systems

    AI that cannot reach enterprise software cannot act on the business.

  5. Unproven value

    Without KPIs, AI spend is hard to defend.

How it works

An enterprise-ready path from first use case to production.

EPI‑USE guides you through a six-step generative AI adoption path on AWS.

  1. 01Assess

    Identify high-value use cases and check data readiness.

  2. 02Mobilize

    Establish secure foundations with AWS landing zones.

  3. 03Experiment

    Launch pilots across select, high-value use cases.

  4. 04Upskill

    Enable your people with AI tools and governance playbooks.

  5. 05Scale

    Move proven use cases to production.

  6. 06Measure

    Track performance, efficiency, cost optimization, and ROAII (Return On Artificial Intelligence Investment).

Agentic AI

Agents that act on your business data.

Built on Amazon Bedrock, these agentic architectures integrate with enterprise platforms to improve productivity and resilience.

ERP exception resolution

Agents reconcile anomalies in real time.

  1. DetectAn invoice does not match its purchase order.
  2. DecideFinds the cause: a price change on the order.Within guardrails
  3. ApproveFinance approves the correction.
  4. Act in SAPPosts the corrected invoice.

Finance and operations automation

Agents manage transactions, workflows, and approvals.

  1. DetectA supplier payment request arrives.
  2. DecideChecks it against policy, budget, and history.Within guardrails
  3. ApproveThe budget owner approves it.
  4. Act in ERPSchedules the payment and updates the workflow.

Predictive maintenance and supply chain optimization

Multi-agent systems anticipate issues and act before they occur.

  1. DetectSensor readings drift on a production line.
  2. DecidePredicts a failure and checks parts on hand.Within guardrails
  3. ApproveThe planner approves the work order.
  4. Act in SAPRaises the order and reserves the part.

Illustrative examples

Security and responsible AI

Governed from day one.

  • Data privacy

    Models run in secure AWS environments with private access. Your data stays owned by you and encrypted.

  • Responsible AI

    Guardrails, explainability, and governance frameworks from day one.

  • Compliance

    Controls aligned to industry standards. Examples include SOC 2, HIPAA, FedRAMP, and others.

Built on AWS

The AWS AI services we build with.

  1. Amazon BedrockOne place to build generative AI applications and agents, with a broad choice of leading foundation models.
  2. Amazon Bedrock AgentCoreManaged hosting, observability, and policy controls that take agents from prototype to production without a rebuild.
  3. Amazon Bedrock GuardrailsPolicies you set once and enforce across every application, to keep responses accurate and on topic.
  4. Amazon SageMaker AITrain, customize, and serve models on your own data when an off-the-shelf model is not enough.
  5. KiroAgentic engineering for developers, from writing specifications to remediating legacy code.
By industry

AI for your industry.

  • Financial services
    • Intelligent document processing
    • Fraud detection
    • Risk modeling
  • Manufacturing and supply chain
    • Predictive operations
    • Autonomous planning
  • Public sector
    • Secure data summarization
    • Citizen engagement assistants
  • Healthcare and life sciences
    • Privacy-safe insights
    • Faster R&D cycles
    • Patient support
  • Professional services
    • Automated proposal generation
    • Knowledge retrieval
    • Case resolution
Client outcomes

What clients achieved on AWS.

Agentic FinOps · Amazon Bedrock

WebOps

Human-governed AI agents on Amazon Bedrock analyze billing and usage data, so leadership can see which AWS spend is necessary.

Read the WebOps story
CEO confidence that AWS spend is necessary spend
Before~10%
After~80%
EPI-USE has given me the confidence that our AWS cost is what it has to be and that I’m not spending money unnecessarily.
Eric AndersonCEO, WebOps
FAQ

AI questions.

What is the difference between generative and agentic AI?

Generative AI creates content such as text, summaries, and answers. Agentic AI goes further: agents detect events, decide on next steps within set guardrails, and act inside your business systems.

Which AWS services do you build on?

Amazon Bedrock and Amazon SageMaker, on secure foundations built with AWS landing zones.

Does our data leave our AWS environment?

Models run in secure AWS environments with private access, and your data stays owned by you and encrypted.

Can AI agents work with SAP and Microsoft systems?

Yes. EPI‑USE’s agentic architectures integrate with SAP, Microsoft, and other enterprise platforms.

How do we move a prototype into production?

We build on Amazon Bedrock AgentCore, which provides managed hosting, observability, and policy controls, so a proven pilot can go live without being rebuilt.

How do we start?

With an Enterprise AI Assessment. Step one identifies high-value use cases and checks data readiness.

Which industries do you work with?

Use cases cover financial services, manufacturing, supply chain, public sector, healthcare and life sciences, and professional services. 

Next step

Ready to move from
exploration to execution?

  • Talk it through with an AI solutions expert.
  • Identify the use cases worth building first.
  • Get a roadmap from pilot to production.

We typically respond within one business day, or email aws@epiuse.com.