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v2.4 — Automated Context Layer config now live

Auto-analyze ERPs and Databases to Reveal Untapped ROI

The New Standard for Enterprise Analytics is Agentic

Lumi's agentic analytics platform connects to all your data sources, automatically builds your semantic layer, and proactively surfaces the opportunities hiding in your data.

DATA SOURCES
Databases
Data Warehouses
ERPs
Unstructured Data
CONTEXT LAYER
Semantic Models
Entities & Relationships
Metrics & Definitions
Business Logic
Tribal Knowledge
User Feedback
Access Control
AGENTIC_ANALYTICS
Find opportunities to improve our pricing strategy. The objective is to increase revenues
On it. I’ll first generate a query to analyze price elasticity by category
Price Elasticity Query
4
SELECT    
    sales_line.item_id,
    sales_line.year-month,
    SUM(sales_line.quantity) AS total_units_sold,    
   SUM(sales_line.transaction_amount) / NULLIF(SUM(sales_line.quantity), 0) AS average_monthly_price
FROM
    sales_line
JOIN
 promotion.promotion_start_date,
    promotion.promotion_end_date,
    SUM(sales_line.quantity) AS total_units_sold,
Okay great. The query works. Will now generate a visual
Pricing Data Visual
Across 5 categories, 68% of SKUs have untapped pricing potential — with Rings and Jewelry showing the largest revenue upside from targeted reductions.
4
by Mary
Which Rings SKUs should I raise prices on, and by how much?
What's the total revenue impact if I action all Raise Price recommendations?
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Please review results; Lumi AI may make mistakes or misrepresent data.
INSIGHTS
Hey Jeremy, 



We identified a subset of high-volume SKUs (top 1%) where a small price reduction could materially increase units sold and drive a 9% revenue upside.
ALERTS
Recommendations sent to stakeholder.
TRUSTED_BY
OUTCOME_DRIVEN_ANALYTICS

Lumi AI users have identified over $150M of value-driving insights with autonomous analytics workflows

Configure Lumi to hunt for opportunities around metrics that matter. Define objectives around increasing revenues, decreasing costs, or freeing up working capital, and its agentic workflows spring into action. Self-service analytics is the starting point. Proactive analytics is the final destination.

HOW IT WORKS

An integrated solution for self-service analytics and proactive insight creation

01 / Build a rich context layer in minutes

Use Magic Wand to auto-generate semantic models tailored to your data model and objectives.

02 / Give every team self-service data access

Enable conversational analytics for the whole business, with guardrails set by your data team.

03 / Reveal opportunities dashboards miss

Set objectives and let Lumi autonomously analyze operational data for hidden opportunities.

04 / Pin, auto-refresh, and share insights

Save any finding to a board that stays current without a dashboard request for collaboration and sharing.

Agentic analytics empowers the business user to explore & frees up the data team to work strategically

Jordan Kuhns, CIO @ Growmark

ENTERPRISE_READY

Built for the security standards data leaders require

SOC 2 compliant with enterprise-grade access controls, so your team moves fast without compromising governance.

SOC 2 Type II compliant

Independently audited security controls

Isolated private tenants

Your data never touches other customers' environments

Role-based access controls

Enforce data permissions at the user level

Data stays in your network

Private gateways keep data within your boundary

WHAT_TEAMS_SAY

Data & business teams both love using Lumi

Whether it’s for conversational self-service analytics at scale, agentic workflows to cut analysis time by a factor or ten, or uncovering  new opportunities hidden in large operational datasets.

Ready to see what's buried in your data?

Most teams find their first seven-figure opportunity within 30 days of deployment.

00:00
Platform Overview
00:27
Prompting & Exploration
02:12
Multi Threaded Analysis
03:30
Identifying the Root Cause
04:47
Trend Analysis Over Time
07:11
Working with Boards
07:55
Insight Summary