Turn policies, SOPs, and enterprise documents into citation-backed answers. A sovereign RAG architecture operating 100% inside your security perimeter.
Contextual, role-specific intelligence delivering accurate answers across enterprise workflows.
Product specs, pricing matrices, competitive intel, CRM history — synthesized and delivered in real-time.
What's new with the Enterprise Shield product? I have a client call in 30 minutes.
Here's what's changed with Enterprise Shield since your last briefing:
New Feature: Zero-trust data isolation now available for APAC deployments (launched Jan 28)
Pricing Update: Volume tier 3 discount increased from 15% → 22% for annual contracts
Competitive Intel: CompetitorX dropped sovereign deployment — position us as the only sovereign option
Lead with APAC zero-trust — Meridian has 3 APAC offices. Mention CompetitorX gap. Avoid Q3 outage topic unless raised.
At its core, Enterprise Knowledge Intelligence is a governed RAG system — retrieving relevant content from your document corpus and using it to generate accurate, grounded responses with full traceability.
"What is our data retention policy for EU customers?"
[0.023, -0.847, 0.156, 0.923, -0.412, ...]Per [GDPR-Policy.pdf § 4.2.1], EU customer data must be retained for a maximum of 3 years after last interaction, unless statutory preservation notices apply.
Chunks split on natural document transitions, not arbitrary token limits. Each chunk retains hierarchical metadata for zero contextual degradation.
Every generated assertion is deterministically bound to source chunks. If an insight does not exist in your audited knowledge base, it is not generated.
Cryptographic role-based controls ensure users only retrieve information authorized for their clearance, enforced before prompt synthesis occurs.
Enterprises depend on policies, SOPs, manuals, and governance documents to operate safely. Yet over time, this knowledge becomes fragmented — creating risk, inconsistency, and audit exposure.
Policies and SOPs live across document systems, shared drives, emails, and legacy tools — often duplicated and inconsistent across departments.
Traditional search and AI chat tools return answers without provenance, making them unusable in audits and investigations.
Missing, outdated, or contradictory policies are rarely identified until a failure or audit reveals them — often too late.
Many AI-based knowledge tools require data to leave the enterprise or rely on opaque models that cannot be explained or audited.
See how your query flows through the RAG pipeline — from semantic search to grounded response with full source attribution.
Per GDPR-Policy-v4.2 §4.2.1, EU customer personal data must be retained for a maximum of 3 years after last interaction. Consent records require 7 years per Article 17.
No documented SOP for Third-Party Data Breach Response. Critical gap for GDPR Article 33 compliance.
GDPR Policy §4.2.1 says 3 years. HR Data Policy §2.1.4 says 5 years for employee records.
Standard RAG systems chunk by fixed token counts — breaking mid-sentence, mid-thought, mid-context. The LLM fills gaps with hallucinated content.
Our algorithm detects subject and object transitions — chunking only when semantic focus changes. Each chunk is metatagged with full context.
Personal data of EU residents must be retained for a maximum period of three (3) years following the date of last interaction. Consent records and audit logs, however, must be maintained for seven (7) years to comply with regulatory requirements. The Data Protection Officer is responsible for enforcing these retention periods across all business units.
"Personal data of EU residents must be retained for a maximum period of three (3) years following the date of last interaction."
"Consent records and audit logs must be maintained for seven (7) years to comply with regulatory requirements."
"...three (3) years following the date of last | interaction. Consent records and audit..."
→ Broken context leads to hallucination
Our RAG system doesn't just retrieve and generate — it analyzes your entire knowledge corpus to find gaps, conflicts, and inconsistencies.
Vector similarity search finds the most relevant chunks from your knowledge base, then the LLM generates precise answers grounded in those retrieved sources — with citations.
What are the approval thresholds for vendor contracts?
Per Procurement Policy v3.1:
All your documents — across repositories, formats, and departments — chunked, embedded, and indexed in a single searchable vector database.
Automatically identify missing SOPs, outdated documents, and conflicting rules — turning reactive maintenance into proactive governance.
No documented procedure for "Third-Party Data Breach Response"
IT-Security-Policy.pdf last updated 847 days ago
Expense Policy vs. Travel Policy: Different approval limits
Section 4.2.1
"Personal data retention: 3 years max"
Section 2.1.4
"Employee records: 5 years retention"
HR Policy should be updated to align with GDPR requirements. Employee PII falls under GDPR scope.
Detect contradictions like conflicting approval thresholds, regional vs. global policy conflicts, and rule violations — surfaced clearly.
Designed for regulated environments first, not retrofitted later. Every feature serves security, explainability, and governance.
This is not "AI on top of documents." It is governed intelligence over enterprise knowledge.
...the data retention requirements under GDPR Article 17 specify that personal data...
...policy framework for data management including retention schedules...
⚠ User must manually open and read multiple documents to piece together an answer
Under GDPR, personal data must be retained for 3 years maximum after last interaction. Consent records require 7 years retention per Article 17.
⚡ Direct grounded answer with verified source citations — zero document hunting
Measurable operational clarity and audit readiness delivered across every enterprise team.
Proactive detection before auditors arrive
Eliminate operational and regulatory exposure
Confident, evidence-based decision-making
Safe adoption in governance-critical domains
Enterprise Knowledge Intelligence runs on Mentis OS, Genovation's enterprise agentic operating system. Customers interact with a product. Mentis OS ensures that product remains trustworthy at scale.
If your organization requires a defensible, explainable, and sovereign knowledge intelligence system, we should talk.
Your enterprise corpus never leaves your sovereign infrastructure
100% of generated responses metatagged with verified source citations
Automatic SOP gap discovery, conflict alerts, and complete audit trail
"Enterprise knowledge should not just be searchable. It should be trustworthy."