Why Legal Research, KM,
and AI Usually Fail

Three Initiatives. Three Systems. Zero Alignment.

Legacy architecture forces lawyers to bridge gaps manually.

✕ Keyword & Folder Bound

✕ Static Retrieval

✕ Manual File Hunting

✕ Separate Silos

✕ Manual Tagging

✕ High Admin Burden

✕ External Indexing

✕ Governance Gaps

✕ High Latency

CAPABILITYTRADITIONAL SYSTEMSARIVU.LEGAL (NATIVE)
ResearchKeyword & folder basedConcept & matter based
KMSeparate systemsEmerges from workflow
AIExternal platformsIn-tenant, permission-aware
GovernanceAdded laterInherited from M365

How we eliminate the “Bridge”

Unlike tools that use a Universal File Picker to pull data out for external processing,

Paari.Legal lives inside your security perimeter.

1

Native Indexing

We leverage your existing M365 search schemas. No external indexing, no duplicated data, and zero lag.

2

Identity-Based Access

AI results are trimmed by the user’s SharePoint permissions in real-time. If they can’t see the file, the AI can’t use the file.

3

Direct M365 Integration

Zero “middleware.” The solution is deployed as a native app within your M365 tenant, respecting your global Purview policies.

In-Tenant Data Flow

Data StoreYour Sharepoint
Security LayerYour Purview / SSO
AI EngineARIVU.LEGAL Native App

Architectural Conclusion: Data sovereignty is maintained. No “bridge” required.

“AI should sit on top of knowledge.

Workflow should live where lawyers already work.”

— Arivu.Legal Architecture Principle

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