RAG vs Enterprise Search: Which Should You Use?

Staff want answers from the firm’s own policies, contracts and manuals, and there is more than one way to give them those answers. Seen plainly, RAG vs enterprise search is a choice between routes to an answer, rather than between two products. One route is a search tool that returns the documents. A second is a ready-made assistant that comes with a software suite, and a third is an assistant built on the firm’s own documents, which is where RAG comes in. Six questions about your documents, access and upkeep point to one of them. This guide sits under the Signisys knowledge search use case.

RAG vs Enterprise Search: Search, Retrieval and a Written Answer

Each term names a different step between a question and an answer.

Enterprise search is software that finds and ranks documents across a firm’s systems for a person to open. Traditional search matches the words someone types against the words in each document. Semantic search matches by meaning instead, and a question about “time off” can find a file on “leave”.

RAG, short for retrieval-augmented generation, works in two moves. First, the system finds passages in the firm’s documents that match the question. Then a language model writes an answer from those passages. The research behind the term is a 2020 paper from Lewis and colleagues, Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. In it, a pre-trained text-generation model works with a neural retriever that draws on a searchable index, which the paper builds from Wikipedia.

A ready-made assistant from a software suite comes with software the firm already uses, and it answers from the documents kept in that software.

In short, a search tool returns documents, while the other two routes return a written answer. Under all three routes, the firm decides who may see which document. For what goes wrong before any route is chosen, see why a staff search returns no answer or a wrong one.

Three Routes to Answers From Business Documents

The table sets the three routes side by side by what a person gets back and who keeps each one running.

None of the rows ranks above the others. A firm that keeps its documents in one suite starts from a different place than a firm whose files sit in five systems. For that reason, the row that fits depends on the questions further down.

Weighing an Assistant Built on Your Firm’s Files

This section weighs one route on its own: the assistant built on the firm’s own documents.

The passage matters for a reason. In 2020 the Lewis paper described provenance, meaning where an answer came from, as an open research problem for the pre-trained language models of the time.

Each of the other two routes could fill a block like this one. What settles the choice is how your firm answers the six questions that follow.

RAG vs Enterprise Search: What to Ask Before You Choose

In Signisys’ working method, six questions about your documents, access and upkeep narrow the choice. Treat them as prompts for discussion. They are our own, and none of them sets a threshold.

1. Where do the documents sit, and can one route reach all those places? If the files sit in a single suite, that suite’s assistant is within reach. If they sit in several systems, a route that reaches only one of them leaves gaps.
2. Which people may open which files, and can the route apply that rule? An answer written from a passage the person may not open exposes that document, even when the answer is right.
3. Must an answer show the passage it came from? Where staff act on policy wording, such as an approval or a contract term, an answer without its source is hard to check.
4. How current must an answer be when a policy changes? If last month’s version can still turn up, someone has to remove or mark it.
5. Who will look after the route after launch? Under each route, a person has to keep the documents and the access rules in order.
6. How will the firm spot and trace a wrong answer? Somebody has to hear about it, find the passage behind it and then fix the source.

Write the answers down before you look at any product; the next table reads from them. To check the documents themselves before answering, see a self-scored sheet for the state of the document set.

RAG vs Enterprise Search: Matching Your Answers to a Route

Signisys’ working method then reads the answers as patterns. Use the table as a way to think. It is not a rule.

Answers can fall between two rows. A firm can also use one route for one document group and a different route for another. For example, engineering drawings may stay on a search tool, while HR policies move to an assistant. Access rules apply in each row, and the wider policy on AI use sits under governing enterprise AI use.

RAG vs Enterprise Search for a Purchase Approval Question

The firm here is made up to illustrate the questions, and it is not a Signisys project. A site manager at an engineering-services firm asks which approval a purchase above a set limit needs.

Through the search tool, the manager gets the purchase policy and the approvals matrix as two documents to open and read. From the suite assistant, the manager gets a written answer drawn from the documents in the suite, which may or may not include the latest matrix. With the built assistant, the manager gets a written answer, along with the policy passage and its date.

In each case, two checks stay with people. The manager and the policy owner still have to confirm that the version is current. They also have to confirm that the manager may see that matrix at all. Neither check passes to the route the firm picks.

The case is here to show how the questions are used. Your own firm’s answers to the six questions will differ, and so may the route.

Decisions Still Open After the Choice

Three matters stay open once a route is picked: whether the documents are fit to be searched, which supplier to trust for a suite or a build, and how the team will test the route before staff use it. Your own files and the people who use them are where each of those gets answered. The steps for a build, with its test, are set out in an ordered method for building the assistant on your own documents.

An outside view is worth having if the access rules are unclear or nobody can be named to look after the route.

Signisys provides data and AI services through its enterprise AI solution and its data and AI service page. The box below describes a Signisys service, not neutral advice, and it makes no promise. If you want the first conversation to start from your answers, bring the answers to the six questions and a list of where your documents sit.

RAG vs Enterprise Search FAQ: Routes, Access and Sources