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OPTINX
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Enterprise Knowledge

Transform technical documentation, manuals, SOPs, and enterprise records into evidence-backed understanding and action — powered by Insora.

The Problem

Critical knowledge scattered across documents, wikis, and databases — unsearchable when needed most.

Current Workflow

1

Manual search across systems

Confluence, SharePoint, Google Drive, email — no unified search

2

Outdated documentation

Docs not updated when systems change

3

Knowledge in people's heads

Expert knowledge not captured, lost with attrition

4

No version control

Can't tell which doc is current or authoritative

OPTINX Approach

1

Document ingestion & parsing

Insora ingests PDFs, wikis, code, databases with version awareness

2

Knowledge graph construction

Entities, relationships, and procedures extracted into queryable graph

3

Evidence-backed retrieval

Hybrid search: vector + keyword + graph with citations

4

Actionable guidance generation

Step-by-step procedures, troubleshooting trees, decision matrices

5

Continuous learning

Resolution feedback improves knowledge over time

Architecture

1

Document Sources

ConfluenceSharePointGitBookNotionS3/Blob StoragePDF Archives
2

Insora Knowledge Layer

Document parsingKnowledge graph constructionHybrid retrievalEvidence synthesisProcedural generation
3

QUACK Runtime

Query orchestrationAccess control enforcementAudit logging
4

Nextmos Memory

Query historyExpert validationsKnowledge gapsUsage patterns

Governance & Security

Human Approval Points

Publishing new procedures requires subject matter expert review
Accessing classified documents requires special authorization
Modifying knowledge graphs requires data steward approval

Security Considerations

Document-level access control preserved in knowledge graph
PII and classified information redacted from search results
No document content used for model training without consent
Full audit trail of all queries and responses

Potential Outcomes

Potential outcomes based on architecture and approach. Actual results depend on integration depth and data quality.

Time to Answer

Knowledge queries resolved in seconds, not hours

Potential

Accuracy

Evidence-backed answers with verifiable citations

Potential

Knowledge Retention

Institutional memory persists despite turnover

Potential

Onboarding Speed

New employees ramp faster with searchable knowledge

Potential
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