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RMZ Case Study

RMZ

RMZ's teams hold years of institutional knowledge across SharePoint and OneDrive. Reckonsys built a Claude-powered assistant that lets them ask for it in plain language and get an answer grounded in the documents they are permitted to open, with every claim traced back to its source page.

Cited answer - hover a marker
What is our notice period for vendor contract termination?
Standard vendor agreements require 60 days' written notice for termination without cause . Where the contract value exceeds the delegated approval threshold, termination additionally requires sign-off from the commercial lead . Notice must be served to the address on record, not by email alone .
Retrieved sources
Vendor Master Agreement Template v4.pdf
SharePoint › Legal › Templates - p. 14
Permitted
Delegation of Authority Matrix.xlsx
SharePoint › Finance › Governance - Sheet 2
Permitted
Confidential Settlement Schedule 2025.docx
SharePoint › Legal › Restricted
Not permitted
Filtered before retrieval. Never entered the model's context.
Client
RMZ
Built with
Claude APIClaude for Teams
Services offered
AI DevelopmentRAG Model DevelopmentCustom Software DevelopmentAI Data Systems
01

Background

  • Institutional knowledge spread across SharePoint Online sites and OneDrive for Business, in PDFs, Word files, Excel workbooks and CSVs.
  • Native SharePoint search matches keywords rather than meaning, so finding a document required knowing the right terms and the right location.
  • Teams fell back on manual lookup and asking colleagues, turning routine questions into repeated, slow work.
  • Existing document permissions had to be respected exactly. Convenience was not a reason to show anyone a file they were not entitled to see.
02

Challenges

  • Make unstructured and structured content across two Microsoft repositories answerable through one conversational interface.
  • Enforce per-user permissions at query time rather than at ingestion, so access changes take effect immediately.
  • Keep a large, constantly changing document estate in sync without reprocessing everything on every run.
  • Give users grounds to trust generated answers instead of asking them to take them on faith.
  • Maintain a defensible record of who accessed which document and when.
Model selection

Why Claude

Enterprise knowledge retrieval makes unusual demands of a language model. An answer has to stay inside the retrieved source material, attribute precisely, and say nothing when the evidence is absent. A confident but unsourced answer about an internal policy or a contract term is worse than no answer at all, because it will be believed.

Claude was selected as the reasoning engine on three counts. It follows grounding instructions reliably, staying within supplied context rather than filling gaps from general knowledge. It handles the long retrieved document sets that enterprise questions tend to require. And it produces consistent structured output, which is what makes machine-rendered citations and source cards possible at all.

03

Solutions

Reckonsys built a permission-aware retrieval-augmented generation platform with Claude at its core.

  • Ingest continuously
    Incremental document discovery through the Microsoft Graph API, with change detection and deduplication, so only what has changed gets reprocessed.
  • Retrieve semantically
    A semantic index over unstructured content, alongside a Pandas-based parsing path for structured Excel and CSV sources.
  • Route intelligently
    Claude classifies each query's intent and decides whether it needs grounded retrieval or direct generation.
  • Answer with evidence
    Claude generates Markdown responses constrained to retrieved context, carrying page-level citations and source preview cards.
  • Enforce entitlements live
    Azure AD OAuth 2.0 with JWT sessions and real-time Graph API validation on every query, so Claude only ever reasons over documents the requesting user can open.
01

Ingestion & indexing pipeline

  • Automated file discovery across target SharePoint sites and OneDrive for Business accounts.
  • Format validation and semantic chunking tuned for long-form enterprise documents.
  • Deduplication and version tracking, so superseded drafts do not compete with current ones.
  • Timestamp-based incremental sync keeps the index current without full reprocessing.

The pipeline exists to serve Claude clean, current, correctly scoped context at the moment a question is asked. Retrieval quality sets the ceiling on answer quality, and no amount of prompt engineering recovers from feeding the model the wrong three documents.

02

Claude-powered retrieval & conversational assistant

  • Intent classification with Claude routes each query down the retrieval-grounded or direct-generation path.
  • Grounded answer generation has Claude synthesise from retrieved chunks under instructions to remain within source material and attribute every claim.
  • Structured-source reasoning parses Excel and CSV rather than treating them as prose, passing Claude data it can reason over numerically.
  • Citations and source previews render Claude's attributions as page-level cards, so a user verifies an answer against the original in one click.
  • Multi-turn context lets users ask follow-up questions naturally, with Claude carrying the thread.
03

Security, access control & audit

  • Azure AD OAuth 2.0 authentication with JWT-backed sessions.
  • Real-time Graph API permission validation on every query, with a 5-minute TTL cache balancing responsiveness against load.
  • Permission filtering runs before retrieval, so out-of-scope documents never enter Claude's context window.
  • PostgreSQL holds audit logs and ID-to-URL metadata mappings.
  • Traefik fronts the deployment as a secure reverse proxy.
04

Engineering & delivery

Phase 1Foundation & access
Azure AD app registration, OAuth 2.0 scope approval, Graph API connectivity, environment provisioning, PostgreSQL and Traefik setup, security review sign-off.
Phase 2Ingestion pipeline
File discovery, format validation, semantic chunking and indexing, deduplication, incremental sync.
Phase 3Assistant & retrieval layer
Claude-based intent routing and answer generation, structured and unstructured retrieval paths, citation rendering, multi-turn context, query-time permission enforcement.
Phase 4Pilot & hardening
Limited business-unit pilot, retrieval-accuracy and permission-leakage testing, prompt and latency tuning, audit-log validation.
Phase 5Go-live & enablement
Production cutover, champion training, support-handover runbook, adoption tracking and feedback loop.
Anthropic partnership

Built with Claude

Claude does the reasoning work across the entire assistant. Every incoming question passes through Claude for intent classification, which determines whether it should be answered from retrieved documents or handled directly. Where retrieval applies, Claude synthesises the response from the returned chunks under prompt constraints that keep it inside the source material and require attribution for each claim. Where the source is a spreadsheet rather than a document, Claude reasons over parsed tabular data instead of prose. The Markdown it returns carries the page-level citations that the interface renders as source preview cards.

That last detail is the one that matters most in an enterprise setting. An assistant that answers well but cannot show its working is difficult to trust and impossible to audit. Constraining Claude to retrieved context and requiring attribution turns a fluent answer into a checkable one, which is what allowed the platform to be considered for material that carries real consequences when it is wrong.

Claude for Teams supports the human side of the rollout, giving champions and pilot users a working environment during enablement.

Fluent is not the bar. Checkable is.
Claude API Claude for Teams Python Microsoft Graph API Azure AD / OAuth 2.0 PostgreSQL Pandas Traefik
04

The outcome

Users ask questions the way they would ask a colleague. Claude answers from documents they are entitled to open, and every claim leads back to its source page.

Keyword-only SharePoint search and manual document lookup give way to unified semantic search across the estate. Behind the interface sits a complete audit trail of document access.

Key takeaways
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