NotebookPipeline
Loss ratio reporting on autopilot
Build the loss ratio analysis once in a collaborative notebook, then schedule it as a pipeline so the morning report lands in your claims team's inbox every day.
Talk to your claims and policy data, build pricing and reserving models, deploy internal apps and automate regulatory reports — all from one platform connected to the systems your underwriters and actuaries already trust.
See how it worksAsk your claims, policies and loss data in plain language
From notebook to internal app for underwriting, claims and ops
Schedule regulatory reports, loss runs and data refreshes
From triaging a claim to shipping an internal app, MINEO covers the full journey — connected to the data your insurance team already trusts.
Connect any datasource — claims, policies, premiums, loss data — and start asking questions in natural language. Threads auto-generates SQL, runs code, and delivers answers with interactive charts and tables. Build custom AI assistants with the model of your choice.
Threads · Claims analysis { "tool": "servicenow-mcp", "action": "create_task", "summary": "Flag the top 10 suspicious claims for fraud review" }
via servicenow-mcp · just now
More than Jupyter. MINEO Notebooks combine code, AI assistant cells, interactive widgets and visual tools in one collaborative environment. Perfect for actuaries, pricing analysts and claims teams — write Python, explore your data, and deploy as live apps from the same notebook.
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Compare loss ratios across lines of business and regions.
df = mineo.query("SELECT line_of_business, SUM(incurred_losses) FROM claims GROUP BY line_of_business")
px.bar(df, x="line_of_business", y="incurred_losses", title="Loss Ratio by LoB")
Key insight: North America drives 43% of total revenue. APAC showed the strongest growth at +23% QoQ, driven by expansion in Japan and Australia.
df.sort_values("revenue", ascending=False).head()
| Region | Revenue | Growth |
|---|---|---|
| North America | $1.8M | +12% |
| Europe | $1.1M | +8% |
| APAC | $820K | +23% |
| LATAM | $480K | -3% |
Turn notebooks into always-on dashboards and interactive applications for claims, underwriting, pricing and operations. Deploy with Streamlit, Gradio, Dash and 6+ more frameworks. Custom domains, white-label branding and embeddable visualizations — ready for your stakeholders.
Mineo · Claims dashboard Last updated: 2 minutes ago
Claims filed
4,218
+14% vs Q3
Active policies
82,340
+6% vs Q3
Loss ratio
62%
-2% vs Q3
| Customer | Region | Revenue | Status |
|---|---|---|---|
| Acme Corp | NA | $245K | Active |
| TechFlow GmbH | EU | $182K | Active |
| Sakura Ltd | APAC | $156K | Pending |
| DataBr SA | LATAM | $98K | Active |
A complete Linux development environment accessible from your browser. Install any package, any tool — Claude Code, Codex, Gemini CLI. Build your pricing and reserving models with the libraries you trust, connect to your datasources and collaborate with your team. No local setup required.
VS Code — Dev Environment Explorer
import streamlit as st
from mineo import DataSource
import plotly.express as px
st.set_page_config(layout="wide")
st.title("Claims Dashboard")
ds = DataSource("claims_db")
df = ds.query("SELECT * FROM claims")
# Layout
col1, col2 = st.columns(2)
col1.metric("Incurred losses", f"${df.incurred_losses.sum():,.0f}")
col2.metric("Claims", f"{df.claim_id.nunique():,}")
# Charts
fig = px.bar(df, x="month", y="incurred_losses", color="line_of_business")
st.plotly_chart(fig, use_container_width=True)
mineo-dev@workspace:~/project$
Successfully installed plotly-5.22 scikit-learn-1.5
Your app is live at https://claims-dashboard.mineo.app
✓ Deployed successfully
Chain notebooks into production workflows. Schedule recurring runs with cron, trigger via REST API, and monitor execution in real time. From daily loss runs to regulatory reporting — build reliable workflows without infrastructure overhead.
/ Projects / insurance / Daily claims refresh Elements
Resource Config
Scheduling
API
The biggest unlocks come when MINEO's building blocks share the same logic — the same notebook becomes a daily pipeline, an internal dashboard, or an answer in a Threads conversation.
Build the loss ratio analysis once in a collaborative notebook, then schedule it as a pipeline so the morning report lands in your claims team's inbox every day.
Claims handlers query case data conversationally with Threads while managers get the same numbers in an always-on Live App dashboard.
Prototype the pricing model in a Cloud Dev Environment, refine it in a notebook with the actuarial team, and ship it as an internal Live App without rewriting.
Use MINEO to talk to your claims and policy data, build models, deploy internal apps and automate regulatory reports — all from the same workspace.