AGENTIC TRANSFORMATION
Enterprise AI orchestration across 10 value streams, powering autonomous decision-making with human-in-the-loop governance
01.A
AGENTIC COMPRESSION: FROM TASKS TO VALUE
The Compression Effect
Traditional process automation asks "how do we speed up each task?" Agentic transformation asks "what is the best possible output for this value stream element?" Agents work backwards from the output template, pulling only the minimum necessary data and human judgment—compressing ~1,700 tasks into coherent, outcome-driven clusters.
~45 min
avg per task
Structured into
~2 hrs
avg per activity
Mapped to
~1 day
avg cycle time
Compressed into
~15 min
avg to output
96%
Time Reduction
From ~45 min/task to ~15 min/output
70%
Touch Reduction
Human-in-loop only for exceptions
189:1
Task Compression
~1,700 tasks → 9 agent clusters
6
CoG Outputs
Canonical state objects per client
01.B
PE VALUE CREATION: FROM COMPRESSION TO RETURNS
Process Compression
↓ Manual Touch Points
↓ Cycle Time
↓ Error Rates
↑ Throughput
→
Operational Leverage
↓ OpEx / Revenue
↑ Revenue / FTE
↑ Capacity Headroom
↓ Incremental Cost
→
PE Value Dials
↑ EBITDA Margin
↑ Organic Growth
↑ Retention / LTV
↑ Exit Multiple
Value Stream → PE Metric Impact
Service, Retain & Grow
SRV-A1, A2, A3
42 L4s
→
3 Agents
Retention
+3.2%
Cross-sell
+18%
GWP Impact
+$85M
Implement & Administer
IMP-A1, A2, A3
40 L4s
→
3 Agents
Admin Cost
-35%
Error Rate
-60%
EBITDA Impact
+280 bps
Market & Acquire
MKT Cluster
38 L4s
→
2 Agents
Quote-to-Bind
+22%
Producer Yield
+15%
Organic Growth
+4.5%
Claims & Risk
RISK Cluster
38 L4s
→
2 Agents
TCoR
-12%
Claims Cycle
-40%
Client Value
+NPS 15
Projected Annual Value Creation
$2.4B → $2.85B
GWP Growth
Retention uplift + organic growth + cross-sell
24% → 28.2%
EBITDA Margin
OpEx reduction + revenue leverage + scale efficiency
$45M+
Annual EBITDA Uplift
From process compression + automation
12-14x
Target Multiple
Tech-enabled broker premium valuation
01.C
VALUE STREAMS
01
Market & Acquire Clients
Client-Facing
6
L3s
38
L4s
02
Assess Client Risk & Needs
Client-Facing
5
L3s
32
L4s
03
Design & Structure Solutions
Client-Facing
5
L3s
34
L4s
04
Place & Negotiate Coverage
Client-Facing
5
L3s
36
L4s
05
Implement & Administer
Client-Facing
5
L3s
40
L4s
06
Service, Retain & Grow
Client-Facing
5
L3s
42
L4s
07
Claims & Risk Management
Client-Facing
5
L3s
38
L4s
08
Specialized Programs
Platform / Growth
4
L3s
28
L4s
09
Acquire & Integrate Partners
Platform / Growth
6
L3s
44
L4s
10
Enable the Enterprise
Platform / Growth
6
L3s
36
L4s
02.A
HIGH-LEVEL SYSTEM ARCHITECTURE
Navacord AgentOS Process Engine
EVENT SOURCES
AMS / Policy Systems
Policy Changes
Renewal Triggers
Endorsements
CRM / Client Portal
Service Requests
Client Updates
Opportunity Signals
Benefits Admin / HR
Enrollment Events
Census Changes
Life Events
Claims Systems
New Claims
Status Updates
Loss Runs
Orchestration Engine
Workflow Orchestration & State Management
Service Tasks → AI Agents
User Tasks → Human Review
Message Events → Async Ops
Process State → Long-Running
AI Agents (via MCP)
IMP-A1
Program Activation
IMP-A2
Financials
IMP-A3
Enablement
SRV-A1
Renewals
SRV-A2
Growth Engine
TARGET SYSTEMS
Finance / GL
Commission Posting
Revenue Recognition
AP/AR Updates
Client Portal
Certificate Delivery
Document Access
Status Updates
Carrier Systems
Submissions
Binding Requests
Claims Filing
Analytics / BI
Event Lake
KPI Dashboards
PE Reporting
02.B
THE RIVER SYSTEM: DATA FLOWS & FILTER GATES
Data Cleanliness as a Native Feature
Traditional transformations demand months of data cleansing before delivering value. Our agentic approach inverts this: AI agents continuously validate and enrich data as part of their daily work—flagging mismatches, reconciling discrepancies, and surfacing gaps while they manage renewals, process claims, and generate invoices. Clean data becomes an output of operations, not a prerequisite.
One Lake, Many Rivers
Platforms become tributary rivers into an AI-optimized data lake organized by output and value-stream.
Filter Gates (Agents)
Agents at each river mouth inspect, enrich, and map data into canonical schema—or push back corrections.
Knowledge Graph Layer
Links policies to clients, clients to renewals, renewals to claims—so agents can reason about cause-and-effect.
Agent Cache ↔ Cache
Agents share intermediate state through the lake and graph, enabling cache-to-cache communication.
River 1: Policy & Program Activation Flow
IMP-A1
AMS / Policy Admin
Raw policy data
Binders, endorsements
Activation Filter Gate
Validates, normalizes, enriches
Clean policy records
Data Lake
Canonical policy entities linked by knowledge graph
Program Activation State
IMP-A1 Agent
→ Live Program Status
CoG outputs
Rejection Flow: If coverage gaps, missing carriers, or term conflicts are detected, the filter gate sends structured "fix packs" back to AMS with specific correction requests instead of silently accepting bad data.
River 2: Renewal & Retention Flow
SRV-A1
CRM / Service
Client interactions
Service tickets, NPS
Renewal Filter Gate
Enriches with loss & exposure data
Renewal data packs
Data Lake
Renewal pipeline, risk scores, relationship signals
Renewal & Retention State
SRV-A1 Agent
→ Renewal Strategies
Auto-renewals, proposals
Rejection Flow: When exposure data is stale or satisfaction scores conflict with service history, the filter gate flags these back to CRM/AMS teams with "please confirm" tasks, improving data quality at the source.
River 3: Financial & Commission Flow
IMP-A2
Billing / AR
Invoices & payments
Financial records
Billing Filter Gate
Matches to policies, reconciles
Canonical invoices
Data Lake
Invoice, commission, leakage tied to programs
Financial Flow State
IMP-A2 Agent
→ Clean Invoice Sets
Reconciled financials
Rejection Flow: When charges can't be matched to policies, rates don't align with contracts, or systematic leakage patterns are detected, the filter gate generates prioritized worklists for AR and finance teams.
River 4: Claims & Risk Management Flow
CLAIMS
Claims Systems
Loss notices, reserves
Raw claims data
Claims Filter Gate
Links to policies, validates coverage
Structured loss events
Data Lake
Claims history, loss patterns, risk signals
Claims & Risk State
Risk Agent
→ Loss Summaries
Risk programs, alerts
Rejection Flow: When claims can't be linked to active policies or coverage terms are unclear, the filter gate routes back to claims teams with specific "coverage verification" requests before proceeding.
📊 Data Enrichment Sources (Click to explore)
Historical Performance
Past loss experience, cost curves, exception patterns by client and segment
Contract & SLA Data
Rate cards, service commitments, penalty structures, carrier agreements
External Data Feeds
Market rates, industry benchmarks, regulatory changes, weather events
Knowledge Graph
Entity relationships: policy → client → carrier → renewal → claim
02.C
AGENT CLUSTERS
Implementation Cluster
IMP
Orchestrates program activation, financials, and client enablement for seamless implementations.
IMP-A1
Program Activation Orchestrator
IMP-A2
Program Financials Orchestrator
IMP-A3
Client Enablement Orchestrator
Service & Growth Cluster
SRV
Drives renewals, retention, cross-sell opportunities, and strategic relationship management.
SRV-A1
Renewal Cockpit Copilot
SRV-A2
Growth from Within Engine
SRV-A3
Relationship Brain
SRV-A4
Service Experience Copilot
SRV-A5
Satisfaction Insights Synthesizer
Shared Infrastructure
SHR
Cross-cutting capabilities that power and govern the entire AgentOS ecosystem.
SHR-DQ
Data Quality Sentinel
SHR-KB
Knowledge Base Manager
SHR-GOV
Governance & Compliance
03
AUTOMATION MODEL (A/B/C)
A
FULLY AUTOMATED
No per-instance human review. Uses locked templates, rules, and thresholds. Monitored via metrics and periodic sampling.
~70%
of all tasks
B
AUTO + EXCEPTION
Agent performs action by default. Human reviews only low-confidence cases, large deltas, or rule conflicts.
~25%
of all tasks
C
HUMAN-GATED
Always requires human approval. Reserved for legal commitments, high-value decisions, and strategic shifts.
~5%
of all tasks
04
CENTER OF GRAVITY STATES
Program Activation State
owner
IMP-A1
coverages[]
PolicyObject[]
effectiveDate
Date
carriers[]
CarrierRef[]
status
"LIVE" | "PENDING"
Financial Flow State
owner
IMP-A2
billing[]
BillingEvent[]
receivables
Currency
commissions
Currency
reconciled
Boolean
Enablement State
owner
IMP-A3
audiences[]
AudienceRef[]
adoptionScore
0-100
riskFlags[]
RiskFlag[]
healthStatus
"GREEN" | "AMBER"
Renewal State
owner
SRV-A1
strategy
StrategyType
riskScore
0-100
options[]
RenewalOption[]
outcome
OutcomeType
Expansion Portfolio
owner
SRV-A2
opportunities[]
Opportunity[]
priorityScore
0-100
potentialRevenue
Currency
plays[]
PlayRef[]
Relationship State
owner
SRV-A3
healthScore
0-100
stakeholders[]
Contact[]
accountPlan
PlanRef
sentiment
SentimentType
05
END-TO-END PROCESS FLOW
🎯
Market & Acquire
🔍
Assess Risk
⚙️
Design Solutions
🤝
Place Coverage
🚀
Implement
💎
Service & Grow
🛡️
Claims
52
L3 Processes
~350
L4 Activities
~1,700
L5 Tasks
15
Agent Clusters