Enterprise AI on AWS
Put generative AI to work on governed enterprise context
Altivate connects Amazon Bedrock and SageMaker AI to the data, workflows, controls, and evaluation needed for production. The goal is not another isolated assistant. It is a measurable capability that people can trust and operate.
AWS service focus
Design, build, govern, and scale generative AI and machine learning products on AWS.
Capabilities
What Altivate delivers
Delivery path
A controlled path from decision to value
Select
Choose one valuable workflow with an owner, baseline, users, and safe scope.
Ground
Connect the right enterprise context, permissions, retrieval, and source evidence.
Evaluate
Test quality, safety, latency, cost, failure handling, and task completion before launch.
Scale
Operate prompts, models, data, controls, telemetry, adoption, and improvement as one product.
Business outcomes
What changes when the platform works
Architecture earns its place by improving measurable business and operating outcomes.
Faster knowledge work
Help teams find evidence, draft, compare, investigate, and act with less manual assembly.
More consistent service
Ground answers and next actions in approved enterprise knowledge and business rules.
Controlled automation
Use bounded agents and human approval to automate work without hiding authority.
Reusable AI foundation
Establish shared model access, security, evaluation, observability, and cost controls for future use cases.
Altivate point of view
The production gap is context, control, and adoption
Model access is only the starting point. Altivate engineers the data path, permission boundary, evaluation suite, operating telemetry, and human workflow that turn a prototype into dependable work.
Frequently asked
Generative AI & ML questions
Amazon Bedrock or SageMaker AI?
Use Amazon Bedrock for managed access to foundation models and generative AI capabilities. Use SageMaker AI when teams need deeper model building, training, deployment, and MLOps control. Many enterprise platforms use both.
Can generative AI use SAP data?
Yes. We connect approved SAP APIs, events, analytics, documents, and process context while preserving source authorization, auditability, and transaction controls.
How do we reduce hallucinations?
Ground responses in current sources, require citations, constrain tools and output formats, evaluate representative tasks, test refusal paths, and route high-risk decisions to people.
