Enterprise Knowledge Agent
Unified enterprise knowledge retrieval with governed access, memory continuity, and source-backed answers.
Why enterprise knowledge is fragmented
- ●Knowledge is spread across documents, internal systems, and operational tools with no unified retrieval layer.
- ●Teams lose context between sessions, forcing repeated searches and duplicate analysis.
- ●Uncontrolled AI access to internal knowledge creates governance and security risk.
- ●Answers often lack source traceability, reducing trust in operational decisions.
What Enterprise Knowledge Agent provides
AI Answer
Enterprise claims above $50,000 require dual approval and fraud screening per v4.2 policy. Exceptions are limited to approved platinum accounts under the Jan 2026 addendum (Clause 2).
Retrieved Sources
| Document | Type | Match | Section |
|---|---|---|---|
| claims-policy-v4.2.pdf | 0.96 | §8.1–8.4 | |
| finance-access-matrix.csv | CSV | 0.91 | Row 42–58 |
| ops/approval-playbook.md | MD | 0.87 | Full doc |
| enterprise-addendum-jan-2026 | 0.84 | Clause 2 |
Query Details
Access Scope
Session
ses-8f2a1b4c-e937Unified knowledge retrieval
Search across enterprise documents, tools, and systems from one governed interface.
AI Answer
Enterprise claims above $50,000 require dual approval and fraud screening per v4.2 policy. Exceptions are limited to approved platinum accounts under the Jan 2026 addendum (Clause 2).
Retrieved Sources
| Document | Type | Match | Section |
|---|---|---|---|
| claims-policy-v4.2.pdf | 0.96 | §8.1–8.4 | |
| finance-access-matrix.csv | CSV | 0.91 | Row 42–58 |
| ops/approval-playbook.md | MD | 0.87 | Full doc |
| enterprise-addendum-jan-2026 | 0.84 | Clause 2 |
Query Details
Access Scope
Session
ses-8f2a1b4c-e937Memory-aware conversations
Persist context across sessions so teams do not re-explain operational details.
Conversation Memory
Persistent context across 37 sessions
Session History
Context Reuse — Current Query
Recognized prior conversation about threshold overrides (Feb 03). Injected org-specific context without re-prompting.Saved ~4 exchanges.
Memory Objects
Active Account
Role-based governed access
Apply policy-bounded access controls for every retrieval and answer path.
Access Governance
Role-Based Access Control · Policy v3.1
RBAC Policy Matrix
| Role | Resource | Scope | Access |
|---|---|---|---|
| Claims Analyst | Policy summary | read | allowed |
| Finance Lead | Payout thresholds | read+export | allowed |
| Vendor User | PII claim details | read | denied |
| External Auditor | Aggregated reports | read | allowed |
Policy Evaluation Log
Policy Stack
Enforcement
Source-backed responses
Attach references and confidence signals for trustworthy operational answers.
Source-Backed Answer
Enterprise claims above $50,000 require dual-review. Exceptions are limited to approved platinum accounts under the Jan 2026 addendum. The dual-review rule traces to claims-policy-v4.2 §8.1.
Citation Evidence
| ID | Source | Section | Relevance |
|---|---|---|---|
| C-1 | claims-policy-v4.2.pdf | §8.1 — Approval thresholds | high |
| C-2 | enterprise-addendum-jan-2026 | Clause 2 — Exceptions | high |
| C-3 | risk-runbook.md | Dual-review procedure | medium |
| C-4 | audit-note-4421 | Threshold override history | medium |
Answer Metadata
Lineage
Policy-bound agents
Capability enforcement ensures autonomous systems operate within explicit boundaries.
Governance Flow
Policy-bound agent execution ensures autonomous systems operate within boundaries.
Autonomous systems require explicit boundaries.
Where it sits in the stack
PlantoOS Architecture
The stack relationship between apps, agents, runtime, and systems.
Applications
Products and workflows
Agents
LLM-powered autonomous units
PlantoOS Runtime
Execution · orchestration · control
Capability Layer
Policy enforcement and tool access
Medhara Core
Memory · governance · lineage
Enterprise + Public Systems
Databases, APIs, infrastructure
A new compute layer for systems operated by agents.
Key workflows
How data flows through the system in typical usage patterns.
Workflow 1
Input
Knowledge query from a team member
Core Process
Retrieves context across enterprise systems with policy filtering
Output
Unified response with source-linked evidence
Workflow 2
Input
Follow-up multi-turn conversation
Core Process
Persists conversation memory and role-aware context
Output
Faster answers without repeated re-contextualization
Workflow 3
Input
Governance review request
Core Process
Logs access scope, policy decisions, and cited references
Output
Audit-ready trace of answer generation
Measured outcomes
↓ 30–45%
Internal search time
↑ 20–35%
Knowledge answer confidence
100%
Source traceability coverage
Indicative ranges from internal benchmarks and early deployments; results vary by workload, model, and infrastructure.
How it integrates
SDK-first integration — governed from the first line of code.
Connect sources
Link internal tools, docs, and data stores
Apply policies
Configure role-based access and usage constraints
Launch interface
Deploy governed retrieval assistant to teams