pillar

AI That Respects Document Permissions By Design

The most common reason enterprise AI projects stall isn't model quality. It's that no one can prove the AI is respecting document permissions. TeamSync addresses this by making permissions a property of the platform the AI runs on, not a rule the AI is expected to remember.

Talk to a security solutions engineer · See how TeamSync handles AI for the CISO

What "Permission-Aware AI" Means

Most enterprise AI tools index your content into a separate vector store, then answer questions from that store. The original permissions never travel with the indexed content, so the AI can end up returning material a user isn't actually cleared to see in the source system. That's a gap most vendors don't talk about, and exactly what a regulator will flag.

TeamSync closes it by treating permissions as part of the platform the AI runs on, not a setting layered on top:

  • The AI uses the same permission engine that governs the document itself. Whether someone opens a file directly, searches the corpus, asks DocuTalk a question, or triggers an agentic workflow, the same access check runs every time.

  • Permissions are checked per request, not per session. A group membership change at 9:31 am takes effect at 9:31 am. A document reclassified at 11:42 am takes effect at 11:42 am. There's no AI cache to clear and no overnight sync job.

What Changes When Permissions Travel With The Answer

Without native permission checks

With TeamSync

Content is indexed once into a separate store; permissions can drift out of sync

Every retrieval checks live permissions at request time

Answers are hard to trace back to a source or a policy decision

Every answer carries a citation and an evidence record: model version, prompt, retrieved content, reasoning steps, and any human review outcome

Audit trail lives in a separate system, if it exists at all

Every AI action is logged to the same cryptographic audit ledger as the rest of the platform, cross-verified across regions

Customer content may be used to improve vendor models

Your corpus stays in your own environment; models query it at the moment of use only, with no secondary use or training

What This Means For Your Organization

Role

What they need

What TeamSync provides

CISO

Proof the AI can't return content a user shouldn't see

Per-request permission checks; cryptographic audit trail; an evidence record for every AI interaction

Chief AI Officer

Evidence the policy was actually followed, per request

Evidence record with prompt, retrieval scope, reasoning steps, and human review outcome

Compliance Officer

Coverage mapped to the relevant regulatory framework

Documentation generated continuously against applicable frameworks, including GDPR, India's DPDP Act 2023, CCPA, PDPA, UAE data law, and US data residency requirements

General Counsel

Confidence that AI decisions can be defended years later

Every request is replayable from the audit ledger

What You Keep

Rolling this out doesn't mean adding new exposure or new vendor dependencies.

  • No retrieval index kept outside your own environment

  • No vendor staff with standing access to your content

  • No model fine-tuning on your documents

  • No need to simply trust the vendor's word — every claim is checkable in the audit ledger

How TeamSync Compares

Common comparisons, and where they tend to fall short:

  • Microsoft 365 Copilot — strong for M365-native content; permission checks can lag behind live changes to group membership or document classification outside that ecosystem

  • Glean — broad enterprise search; the per-request evidence record and cryptographic audit trail are less built out

  • General-purpose RAG chatbots — flexible to build, but permissions typically have to be re-implemented and maintained separately from the source system

The Capabilities Behind This

  • DocuTalk — Natural-language Q&A grounded in your corpus, scoped to the user's permissions, with click-through citations.

  • Semantic Search — Platform-wide hybrid + entity-graph search that respects the same permissions.

  • Agentic AI Workflow — Bounded-autonomy agents whose tool surface is defined by business rules and whose every action is audited.

  • Tamper-evident audit ledger — The Merkle chain that anchors every AI event.

Compliance Frameworks Served

EU AI Act (Articles 11, 13, 14 for high-risk systems). NIST AI Risk Management Framework. ISO/IEC 42001 AI management system. FINRA Reg Notice 24-09 on AI in surveillance. FDA AI/ML SaMD framework. MAS Veritas. FCA AI Discussion Paper DP5/22. SOC 2 Type II. ISO/IEC 27001:2022. HIPAA + HITECH. GDPR Article 17.

See all 12 compliance overlays →

Read Further