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Technical perspective

Enterprise search or workflow automation: which architecture fits?

When enterprise search is enough and when a process must coordinate multiple data sources, rules, and system actions.

Technical note · 1 min read
01

RAG answers questions

Retrieval augmented generation connects a request to approved company content. It is useful for research, summaries, and answers with traceable sources.

It depends on reliable documents and metadata. Missing permissions, duplicates, and stale content cannot be repaired by a language model.

02

Workflows change state

Once a system writes data, routes a case, or coordinates applications, it becomes a workflow. Rules, transactions, error handling, and approvals then matter more than how an answer is phrased.

  • Use RAG for read access to bounded knowledge
  • Use workflow automation for actions in business systems
  • Use a hybrid when research and action belong together
03

Prefer the simplest robust solution

Not every process needs an agent. A conventional integration or rules engine is often cheaper and easier to audit. AI earns its place when unstructured content or variable language is genuinely part of the problem.

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What does this perspective mean for your data and process?

We apply the architecture question to your system landscape and responsibilities.