Product

AI, Meet Business Context

Sapien applies advanced AI to your data while understanding and accounting for the structures, definitions, and constraints that actually create impact for your business.

Faster and more productive analytics

Sapien understands your data and business context upfront, enabling teams to analyze faster, reuse logic, and focus on insight instead of rebuilding work.

Go deeper and create insight

Sapien goes beyond surface-level reporting by breaking performance into clear drivers, root causes, and quantified impact you can trust.

Explore data you haven’t even tapped yet

Sapien makes it easy to investigate new data sources and dimensions by automatically understanding structure and relationships across your systems.

Analytics + Business Context and Judgement

Sapien is designed to work the way the world’s best business analysts do: by building context, asking disciplined questions, and following logic to defensible conclusions. Each module reflects a step in that analytical process, working together as a single, cohesive system.

01

Connect

Establish durable, live access to operational and financial data so all analysis runs on current, governed sources — not one-off extracts.

Connect ERP, warehouse, and operational systems through reusable connectors
Sync source data continuously to keep analysis and dashboards current
Support structured finance, manufacturing, supply chain, and market data
Reuse connectors across environments and entities
Stand up new integrations in hours or days

Data Connections

Demo Manufacturing Co

Leading manufacturer of precision components

QuickBooks

Accounting & GL

NetSuite

ERP & Operations

Salesforce

CRM & Revenue

SAP

Manufacturing ERP

Excel

Spreadsheet Data

02

Teach

Create shared structure, meaning, and business context so data reflects how the company actually operates and thinks.

Map company structure, entities, segments, and performance metrics
Teach Sapien table, column, and field meaning in natural language
Define hierarchies, rollups, and drill-down paths
Capture definitions, formulas, and assumptions as reusable knowledge
Centralize business logic that normally lives in people's heads

Company Engine/Learning

147 columns learned

Data Context

ERP 5

General Ledger

Purchase Orders

Inventory Transactions

Accounts Payable

Cost Centers

Learning semantic representation...

ERP / General Ledger

General Ledger

5 columns

0/5 columns represented

Sapien learns each field's business meaning from ledger distributions, joins, and historical analyst usage patterns.

Column Meaning Representation

account_codeText

Learning meaning from transaction behavior and adjacent financial fields...

account_descriptionText

Learning meaning from transaction behavior and adjacent financial fields...

cost_centerText

Learning meaning from transaction behavior and adjacent financial fields...

entry_amountNumber

Learning meaning from transaction behavior and adjacent financial fields...

posting_dateDate

Learning meaning from transaction behavior and adjacent financial fields...

03

Automate

Turn high-value analyses into repeatable workflows that run consistently every period without rebuilding logic.

Encode complex analyses into reusable workflow agents
Run standard processes like P&L reports and cost drivers automatically
Apply consistent logic across periods, entities, and scenarios
Generate structured outputs with quantified drivers
Reuse analytical workflows across teams

Modules/Monthly P&L Report

Available Modules

Monthly P&L Report

Revenue, margin and EBITDA by site

Run

Cost Driver Analysis

Material, labor and overhead breakdown

Variance Report

Budget vs actuals with driver attribution

04

Inquire

Ask disciplined analytical questions in natural language and receive structured, explainable outputs — not just answers.

Ask business questions in plain English across all connected data
Run multiple investigative questions in parallel
Switch between direct answers, driver analysis, and exploration modes
Drill into charts, tables, and calculations interactively
Save insights and build chains of investigation over time

What would you like to explore today?

Focus

DirectAsk

What is the average actual cost per unit at Site 5 compared to Site 1 for Product Type 1?

What is the average quoted material cost per unit across all vendors at Site 5?

What is the average scrap rate at Site 2 compared to Site 3?

05

Verify

Explain what changed, why it changed, and how much it mattered through traceable causal analysis.

Decompose outcomes across time, entities, and operational dimensions
Isolate root causes behind trends and anomalies
Connect operational drivers to financial results
Quantify the impact of each driver
Preserve transparent calculation paths for audit and review

Analyses/Site 4 Profit Drivers

Break down the drivers of profit change for site 4, go into detail and compare to other sites...

Site 4 is the only large site growing profit, with GP up $739.94K (10.91%) H1 2024 to H1 2025.

Site 4 Gross Profit Walk: H1 2024 → H1 2025

Dive Deeper

Ask a follow-up question...Ask

06

Monitor

Continuously track what matters with live dashboards and proactive monitoring instead of periodic reviews.

Create dashboards from metrics, tables, charts, and written insights
Refresh dashboards automatically as new data arrives
Monitor metrics, workflows, and patterns continuously
Detect anomalies and emerging risks proactively
Keep recurring questions permanently answered

Dashboard

2024 Budget vs Actual Costs Monthly

2024 Total Budgeted Manufacturing Spend

0.00M

Across all five manufacturing sites

2024 Total Manufacturing Spend

0.00M

Actual Costs Exceeded Budget by 23%

The entire variance is driven by $207K in price mix, with volume contributing essentially zero.

Budget vs Actual Cost Variance by Site

Total budget of 89.63M rolls up to total actual of 110.05M across sites.

Hover + click Add item to create a monitoring table.

07

Forecast

Extend analytical logic into forward-looking scenarios using the same definitions and structure as actuals.

Forecast using actuals-aligned data mappings and metric definitions
Model scenarios at the same level of detail as reporting
Iterate rapidly on assumptions and what-if cases
Compare multiple scenarios side by side
Update forecasts automatically as new actuals arrive

Forecast

Product Category

Actuals			Forecast
2025-08-01	2025-09-01	2025-10-01	2025-11-01	2025-12-01	2026-01-01	2026-02-01	2026-03-01
14.5M	12.9M	10.9M	10.9M	9.3M	9.4M	9.4M	10.1M
22.3M	18.6M	20.0M	20.0M	20.9M	17.8M	22.7M	23.3M
20.1M	19.4M	15.7M	15.7M	11.1M	12.3M	11.0M	14.7M
8.1M	6.6M	6.5M	6.5M	5.5M	6.8M	5.9M	7.3M

Projection

Pending onlyCollapse

Apply

08

Present

Deliver decision-ready insight that survives outside the tool and stays consistent with live logic.

Export tables, charts, and structured analyses
Share dashboards and workflow outputs across teams
Preserve driver breakdowns and assumptions in exports
Support leadership, board, and operating reviews
Keep shared outputs aligned with underlying analytical logic

Share Analysis

PDF ReportExcel WorkbookSlide Deck

Include

Executive Summary

Driver Breakdown

Source Data Tables

Charts & Visualizations

Share with team

ACRLDP+ Add people

Copy LinkExport & Share

FAQ

Frequently asked questions

See it on your data

We don’t demo on synthetic data. Send us a real export and we’ll have Sapien running on your chart of accounts, your definitions, your numbers — in hours.