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Data & AI

Generative AI Engineered for Real Business Workflows

Apply LLM integrations, RAG, semantic search, document intelligence, and natural-language interfaces to governed business workflows.

Identify a Generative AI Use Case View Related Context

Governance Path

Data, models, and approval boundaries

Move generative AI from experimentation into workflow-specific systems with access control, evaluation, and human review where needed.

Use-case boundary
Knowledge layer
Model layer

Intelligence Surface

Where AI and analytics require control

Move generative AI from experimentation into workflow-specific systems with access control, evaluation, and human review where needed.

Intelligence Surface Where AI and analytics require control
  1. 01 LLM integrations What the AI should and should not do
  2. 02 RAG Documents, metadata, retrieval, citations
  3. 03 Semantic search Provider, routing, prompts, evaluations
  4. 04 Document intelligence Human review, tools, logging
  5. 05 Natural-language interfaces What the AI should and should not do

Governance Matrix

How data decisions affect reliable intelligence

How data decisions affect reliable intelligence
Architecture ElementWhat HRHK EvaluatesPublication Value
Use-case boundaryWhat the AI should and should not doLimits risk
Knowledge layerDocuments, metadata, retrieval, citationsGrounds responses
Model layerProvider, routing, prompts, evaluationsFits workload requirements
Workflow layerHuman review, tools, loggingMakes output operational

Identify a Generative AI Use Case

Start with the data source, workflow, model use case, or governance risk. HRHK can design the access, retrieval, evaluation, and approval path before AI enters operations.

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