Case study: Enterprise operations
An LLM layer turned natural-language requests into validated, permission-aware SAP actions.
System
The existing SAP platform already contained the required business functions, but non-specialist users needed substantial SAP knowledge to find them, supply the correct parameters, follow the required sequence and interpret failures. An LLM layer could make SAP easier to use through natural-language requests, but unrestricted SAP access could bypass business rules and permission boundaries.
GAIAA built an LLM layer over SAP that translated intent into structured SAP parameters and selected only predefined, authorized SAP tools. It validated each SAP response and, when an operation failed, could inspect approved SAP dependencies and explain the recovery path rather than claiming success or exposing a raw error.
How does a natural-language request become a controlled SAP action?
Use the controls below to inspect the key stages, constraints and validation decisions in that process.
Close one sales order after checking its dependencies.
SO-1842 cannot be closed while dependency D-14 is open.
Evidence retained: The execution trace recorded interpreted intent, SAP authorization, SAP tool input, SAP response and recovery decisions.
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