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Live Pricing Engine — v3.4.1

Competitor Pricing Heatmap

AI ingesting 24 live feeds — 8 signals active

AI IngestingRate UpRate Down
CompetitorTerm 10yrTerm 20yrWhole LifeUL FlexVUL Core
Axis Re
-2.4%
-2.7%
-1.2%
-2.6%
-2.9%
Meridian Life
+3.4%
-0.4%
-3.1%
+1.0%
-3.1%
Vantage Cap
+2.3%
+1.6%
+3.9%
-0.3%
+0.8%
CoreShield
-2.0%
+0.5%
+1.6%
+3.0%
+0.3%
NovaPrime
-1.2%
+1.7%
+3.9%
+3.8%
+2.3%
Time to Reprice
6 min
6 weeks manual
Margin Found
$2.4M
avg. per portfolio
Competitor Lag
Real-time
blind quarterly
Signals Processed2.1B+Rate Adjustments Deployed847KAvg. Margin Recovery$2.4MReprice Latency< 6 minPortfolios Monitored340+Competitor Feeds Live1,200+Basis Points Recovered18–42 bpsUptime SLA99.97%
01 / The Gap

Every week you wait, the market doesn't.

Manual pricing cycles were designed for a world where competitor data arrived monthly. That world ended. Here's what the gap looks like in practice.

Manual Pricing
Calibrate AI
Time to Reprice
6 weeks
committee review + spreadsheet build
6 minutes
ML engine detects + recommends + queues
Margin Leakage Detected
$0
invisible until quarterly close
$2.4M found
avg. per mid-market portfolio
Competitor Response Lag
Blind
rate moves discovered weeks later
Real-time
1,200+ feeds monitored continuously
Pricing Granularity
12 segments
age band × product line only
340+ micro-segments
behavioral + actuarial + market signals
Analyst Hours per Cycle
120 hrs
data pull, model, validate, present
2 hrs review
approve or override AI recommendations
02 / Client Outcomes

Numbers that don't need qualifying language.

Mid-Market Insurer
Midwest, $2.1B AUM
Verified Result
18%
Rate Erosion Reduction

Reduced rate erosion 18% in Q1

Deployed 340 micro-price adjustments across 12 product lines in 90 days. Zero manual analyst hours after initial config.

340
Adjustments Deployed
4 days
Time to First Push
Fintech Lending Platform
San Francisco, $800M book
Verified Result
$7.2M
Margin Recovered

Captured $7.2M in previously invisible margin

Basis-point optimization across 18 loan cohorts. Calibrate identified competitor underpricing windows that manual review had missed for 11 months.

18
Cohorts Optimized
23 days
Payback Period
Wealth Management Platform
New York, $4.8B AUM
Verified Result
3.4×
Revenue per Client Uplift

Fee schedules repriced from gut feel to data

Fee schedules last updated by intuition in 2021. Calibrate surfaced 47 pricing anomalies in week one — $1.8M annualized uplift identified before a single deployment.

47
Anomalies Found
$1.8M
Annualized Uplift
03 / ROI Calculator

What's sitting in your pricing blind spot?

Input your book size and current cycle. Calibrate models your recoverable margin.

$500M
$50M$5.0B
18%
5%40%
4× / year
1× / year12× / year
Estimated Annual Recovery
$0M
recoverable margin with Calibrate
Competitor gap capture$0.9M
Cycle compression gains$0.7M
Micro-segment unlock$0.4M

Pre-filled with your inputs. 2-step, 90 seconds.

04 / Get Started

Your pricing data is
already talking.

The question isn't whether you have a pricing gap. Every mid-market book does. The question is whether you find it in the next 6 minutes — or the next 6 weeks.

No commitment. 90-second form. Results in 24 hours.

🔒SOC 2 Type II
NAIC Compliant
📋FINRA Registered Data Vendor
99.97% Uptime SLA