Experience Analytics in Action
Explore live dashboards, automation, and AI-powered business insights.
Every industry, its own dashboard story
Ten dashboards. Different KPIs, different chart types, one interaction model. Filters cross-update every KPI, chart, table, and AI insight instantly. Fictional demonstration data.
Insurance dashboard
Watch loss ratio against target and understand where claims stack up.
Premium revenue
$148.4M
+8.6%
Loss ratio
62.4%
-1.6pp
Avg. processing (d)
5
-0.6d
Retention
91.0%
+1.4pp
Loss ratio vs target 65%
62.4%
Target 65.0%-4.0%
Claim lifecycle
Premium by policy type (stacked)
Loss ratio % (policy × region)
| West | Central | East | Southeast | |
|---|---|---|---|---|
| Auto | 62.0% | 66.0% | ||
| Home | 64.0% | 68.0% | 66.0% | 72.0% |
| Commercial | 63.0% | 65.0% | 70.0% | |
| Life | 62.0% |
Top claim causes
Claims by region
Click to filter| Region | Submitted | Approved | Loss ratio |
|---|---|---|---|
| West | 4,120 | 3,460 | 61.2% |
| Central | 3,240 | 2,720 | 63.4% |
| East | 3,180 | 2,620 | 62.8% |
| Southeast | 2,280 | 1,880 | 64.1% |
AI insights
- Collision leads at 3,400 — 31% of the mix.
- Other trails the leader by 5.5× — highest-leverage growth target.
- Loss ratio vs target 65% is under target of 65.
Need a dashboard designed for your business?
We build these to your KPIs, data sources, and team.
A live view of the metrics that move the business
KPI cards, revenue trends, customer segmentation, sales by region, and operational health — all interactive.
Revenue
$5.6M
Customers
21,130
Churn rate
3.1%
Uptime
99.94%
Revenue trend
Last 12 months · AllCustomer segmentation
Sales by region
Operational metrics
Avg. response
1.4h
-22% wk/wk
Orders / day
3,214
+8.6%
Fulfilment SLA
97.2%
+1.1pp
Error rate
0.18%
-0.04pp
Sales & Financial dashboard
Interactive filters, drill-down, and a semantic model powering executive KPIs — the way a real Power BI report feels.
Fictional sample data · for demonstration only
FY26 · All regions · USD
Revenue
$24.1M
+18.4%
Gross margin
62.8%
+2.1pp
New logos
184
+12
Pipeline
$38.6M
+22%
Revenue vs. forecast
Revenue by product
Click a row (Power BI drill-through)
Need something similar for your business?
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Automated reporting workbook
Power Query pulls, cleans, and refreshes the model. Pivot-driven KPI cards and charts sit on top — one click to update.
Fictional sample data · for demonstration only
| Region | Units | Revenue | Margin |
|---|---|---|---|
| North | 4,820 | $128,400 | 42.0% |
| South | 3,650 | $98,700 | 38.0% |
| East | 5,940 | $156,800 | 45.0% |
| West | 6,720 | $182,300 | 48.0% |
| TOTAL | 21,130 | $566,200 | — |
Revenue by region
PivotChartSum
$566,200
Avg margin
43.3%
Best region
West
Need something similar for your business?
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Executive & operational storyboard
Combined executive KPIs, operational drill-down, and geographic mix — the Tableau storytelling pattern our clients ship to the board.
Fictional sample data · for demonstration only
Quarterly performance
Filters
Insight
Q4 revenue up 76% vs. Q1; enterprise segment drives 58% of growth.
Need something similar for your business?
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Visual ETL workflow
Two source systems, cleansed and joined, validated, then delivered to a warehouse and a governed Excel deliverable.
Fictional sample data · for demonstration only
Rows in
1.2M
Rows out
1.18M
Rejected
0.9%
Runtime
42s
Need something similar for your business?
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Automated data-processing workflow
A scheduled Python job that ingests raw files, cleans and analyzes, then generates the executive report — no human in the loop.
Fictional sample data · for demonstration only
import pandas as pd
from pathlib import Path
from report import build_workbook, email_report
df = (pd.read_csv("s3://raw/sales.csv")
.dropna(subset=["order_id"])
.assign(revenue=lambda d: d.qty * d.unit_price))
summary = (df.groupby(["region", "product"])
.agg(revenue=("revenue", "sum"),
orders=("order_id", "nunique"))
.reset_index())
wb = build_workbook(summary, title="Weekly Sales")
email_report(wb, to="exec@client.com")
Pipeline run · #4,218
Scheduled Monday 06:00 CST
Records
248,912
Runtime
1m 12s
Status
Sent ✓
Need something similar for your business?
30 minutes. No pitch. We'll map the fastest path to a dashboard like this one.
Model your savings in real time
Slide the inputs. Watch payback, cumulative savings, and hours recovered update instantly.
Your inputs
Assumes ~75% automation of manual reporting. Real engagements typically hit 70–90%.
Annual savings
$101.4K
Hours recovered
1,560
Year-1 ROI
576%
Cumulative savings vs. investment
Break-even in month 2
Want a detailed report tailored to your team?
From spreadsheet chaos to AI-ready insights
Watch the pipeline flow — every stage automated, governed, and observable.
Live pipeline preview
Now processing
Excel
Messy sheets & CSVs
Rows processed
2.4M
Latency
1.2s
Quality score
99.6%
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