0.3.5 APPLIED_AI_AND_AGENTIC_SYSTEMS
Applied AI & Agentic Systems
AI earns its keep when it has governed access to real data, a way to measure whether its answers are right, and a human in the loop on anything that matters. That groundwork is the work.
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MCP platforms and governed tool access
Expose ERP, operational data, and documents to applications and agents through governed, audited tools with scoped access, instead of raw credentials or copy-paste into public chat.
Agentic workflows with human-in-the-loop
Workflows that draft real work, structured extraction, order entry, classification, and route it to a person for review before anything commits. Auditable by design.
Retrieval, search, and evaluation
Hybrid and semantic retrieval over your own knowledge base, with reranking and metadata filtering, plus LLM-as-a-judge evaluation so quality is measured and regressions surface before users hit them.
AI readiness and controlled deployment
When the data or access model is not ready yet, the near-term output can still be a readiness plan: which sources are usable, who can query them, and whether local, cloud, or hybrid deployment fits.
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Want AI that ships and that you can actually trust?
Start with governed access to real data, evaluation, and a human in the loop, not a demo that falls over in production.
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