Independent research-project review. Microsoft’s reviewed repository says GraphRAG is largely in maintenance mode and is not an officially supported Microsoft offering. The business pilot below is a proposed example, with no claimed client or benchmark result.
1. Start with questions that cross document boundaries
Keyword search can work well when an employee knows the document or phrase they need. A broader question such as “Which supplier issues repeatedly delayed projects?” may require connecting evidence across meeting notes, project reports, and incident records. The first task is to decide whether that broader question is useful and answerable from the available material.
Microsoft’s public GraphRAG project describes a pipeline that extracts structured information from unstructured text using language models. Its documentation discusses knowledge graphs, communities, summaries, and several query approaches.
The reviewed repository explicitly describes it as a research demonstration, largely in maintenance mode, rather than an officially supported Microsoft product. Its design is a reference for an evaluated pilot; adopting it as a managed enterprise service would be a different claim.
2. How the published approach organizes information
The documented indexing process divides source text into units, extracts entities and relationships, groups related entities into communities, and produces summaries. At query time, these structures and source text can supply context for an answer.
- Local search: combines graph-related information and source text for questions about particular entities.
- Global search: uses community reports to explore broader questions across the collection.
- Basic search: provides a simpler vector-search comparison, useful when the question is best answered by retrieving relevant passages.
This adds processing and maintenance work. The repository warns that indexing can be expensive and that out-of-the-box prompts may not perform well for every dataset. A graph extracted by a model also needs evaluation: a plausible relationship is not automatically a verified business fact.
3. Define a bounded company knowledge pilot
Choose a document collection with a clear owner and a small set of useful questions. For example, a service business might start with approved project retrospectives accessible to one internal team. Exclude unrelated private material and define the permission boundary before indexing.
On small screens, scroll the table sideways to see every column.
| Deliverable | Business purpose |
|---|---|
| Document register | Record ownership, revision, scope, and the intended audience for every source. |
| Question set | Define representative factual, cross-document, missing-answer, and restricted-content questions. |
| Baseline search | Compare the proposed approach with a simpler retrieval or existing search process. |
| Evidence and review interface | Let a reviewer inspect supporting source material and flag unsupported conclusions. |
Summaries, graph records, caches, and logs can carry information derived from restricted documents. Enforce the access design across those outputs as well as the original files. A search-time filter alone should not be assumed to repair an index built with the wrong audience.
4. Test a question with evidence and an honest gap
For an illustrative evaluation, prepare 20 reviewed questions: ten factual lookups, five questions spanning several documents, three unanswerable questions, and two access-boundary checks. These counts define a sample test set; they are not a reported Microsoft evaluation.
One question might ask which recurring supplier issues appear in the approved retrospectives. A useful answer identifies the issue, names the supporting projects and source passages, and separates an explicit statement from an inferred theme. A missing source should result in an acknowledged gap.
Compare the answer with a subject-matter expert’s reference notes. Check whether cited evidence actually supports the claim, whether conflicting versions were handled, and whether any restricted information appears. A polished summary without those checks is insufficient for a business decision.
5. Build evaluation and ongoing updates into delivery
- Discovery: agree users, questions, document scope, retention, and access responsibilities.
- Baseline: test ordinary search or simpler retrieval on the same question set.
- Prototype: index the bounded collection, tune instructions where appropriate, and capture operating costs.
- Review: assess evidence quality, missing answers, permissions, response time, and the effort to correct sources.
- Handover: document refreshes, deletion propagation, evaluation reruns, and ownership before expanding access.
Treat deletion and revision as real workflows. An obsolete policy should not survive only in a summary after its source has changed. Keep a reproducible relationship between the source collection, generated index, configuration, and evaluation results.
6. Choose the simplest approach that answers the questions
Track supported-answer quality, correct handling of unknowns, access-boundary failures, query time, indexing cost, and the effort needed to keep the collection current. Compare the same questions and source versions across approaches.
A graph-based method is useful only if it improves the intended questions enough to justify added cost and complexity. For a small policy library, good document ownership and simpler retrieval may solve the problem. For cross-document investigation, the structured approach may be worth a controlled evaluation.
This article reports no production deployment, accuracy percentage, or savings. Its practical outcome is a project brief that makes evidence, permissions, and operational cost part of the proposed solution.
7. Frequently asked questions
Is GraphRAG an officially supported Microsoft enterprise product?
The reviewed repository says its code is a research demonstration, largely in maintenance mode, and not an officially supported Microsoft offering. Check the current project status and support model before any adoption decision.
Will GraphRAG always outperform simpler document search?
No universal result is established here. Evaluate representative questions against a simpler baseline, including source support, permissions, latency, indexing cost, and ongoing maintenance.
Can we index all company documents into one unrestricted assistant?
Define the intended audience and access boundary first. Derived graph records, summaries, caches, and logs must follow that design as well as the original documents.