Pecunio AI — Financial Model Platform

Pecunio • AI Financial Model Platform

Platform Demonstration

Enterprise Financial Modelling with AI-Powered Analysis

March 2026 | Mock data — Global Consumer Health Division

01 — Platform Overview

How Pecunio Works

Connect your accounting system. The platform builds a financial model. An AI agent answers questions over it.

Data Sync

ERP / GL → PostgreSQL
Accounts, journals, bank txns

→

Model Seed

Raw data → nodes, series,
edges, category mapping

→

AI Agent

33 tools, LangGraph,
reasoning + narrative

→

Calc Engine

Deterministic ops,
cell provenance

→

Validation

11 reconciliation checks,
tieouts, variance

Key principle: The AI agent handles reasoning, narrative, and tool selection. A deterministic calculation engine handles all financial math — no LLM touches any number. Every cell traces back to source data through an auditable provenance chain.

02 — Financial Model

CEO Summary — Model View

The model auto-generates from synced accounting data. Users interact via AI agent or direct tab navigation.

Global Consumer Health Division — Financial Model

12 months actual (Jan – Dec 2025) | Connected to ERP | Base Scenario

Guide

CEO Summary

P&L

Cash Flow

Balance Sheet

Revenue

P&L Explorer

AR / AP

KPIs

Variance

Scenarios

Health

Knowledge

Ops

$847.2M

Revenue

+8.3% YoY

$142.6M

Net Income

16.8% net margin

62.4%

Gross Margin

+1.2pp vs prior

$224.8M

Forecast Run-rate

Next 3 months

38 days

DSO

-2 days vs prior Q

+3.2%

Revenue MoM

Dec vs Nov 2025

83.2%

Cost Ratio

-0.8pp improvement

$528.8M

Gross Profit

12 months actual

$34.7M

Open AR

$8.2M overdue >60d

4 ops

Active Operations

2 drivers, 2 overrides

8 PASS 2 WARN 1 FAIL Revenue ties to GL · Cash ties to bank · Monthly P&L reconciled

Performing Well

Revenue +8.3% YoY driven by OTC Pharma (+14.2%)
Gross margin expanded 120bps on procurement savings
Operating leverage improving — OpEx grew only 6.1%

Needs Attention

Medical Devices COGS spiked 22% in November
$142K OpEx variance vs GL — likely 3 unsynced journals
Consumer Wellness declined 3.1% (seasonal softness)

03 — Virtual CFO Agent

AI Agent Answering Questions Over the Model

Users ask natural language questions. The agent queries the model, runs analysis tools, and returns structured answers with source data.

Virtual CFO — Financial Q&A

Ask questions about your financial model in natural language

Virtual CFO Agent — Connected to Financial Model

What drove the revenue increase this year? Break it down by segment.

vnext_revenue_dashboard

Total revenue grew +8.3% YoY to $847.2M. Here’s the segment breakdown:

Segment	FY2025	FY2024	YoY Change	Contribution
OTC Pharmaceutical	$512.4M	$448.6M	+14.2%	60.5%
Medical Devices	$246.2M	$224.2M	+9.8%	29.1%
Consumer Wellness	$88.6M	$91.4M	−3.1%	10.5%
Total	$847.2M	$764.2M	+8.3%	100%

OTC Pharma was the primary growth driver (+$63.8M), benefiting from the new product line launched in Q2 and expanded distribution to 340 additional retail locations. Consumer Wellness declined due to seasonal softness in Q3 — management expects recovery in Q1 2026.

Are we going to have any cash flow issues in the next quarter?

vnext_get_model · cashflow

Based on the forecast model, no cash flow issues anticipated. The forecast projects strong positive cash generation:

$14.6M

Net Cash / Month (avg)

$183.1M

Projected Cash (Mar 26)

2.4x

Cash Coverage Ratio

However, there are two items worth monitoring:

AR overdue >60 days: $8.2M (3 customers) — suggest collection follow-up
Q1 CapEx spike: $6.4M budgeted for lab expansion in January. Ensure drawdown aligns with milestone payments.

What if OTC Pharma revenue grows 10% next quarter based on the product launch plan we uploaded?

vnext_preview_ops

I’ve modelled a 10% growth driver on OTC Pharma for Jan–Mar 2026, referencing the uploaded Q1 2026 Product Launch Plan (87% confidence). Here’s the preview:

Operation	Target	Before	After	Delta
set_driver growth +10%	OTC Pharma (Jan–Mar)	$159.3M	$180.6M	+$21.2M

Net impact on forecast Net Income: +$19.1M across Jan–Mar 2026.
Source: Knowledge doc “Q1 2026 Product Launch Plan.pdf” — Assumption #7

Should I commit this operation? You can undo it later from the Ops tab.

Yes, commit it. Also increase R&D to $9.5M/month for the same period to cover the clinical trials.

vnext_commit_ops

Done. 2 operations committed to Base scenario:

Op #3 OTC Pharma revenue +10% growth (Jan–Mar 2026)
Op #4 R&D override to $9,500,000/mo (Jan–Mar 2026)

Full provenance recorded. Both operations tagged as agent-created with knowledge doc source. You can undo either from the Ops tab.

Run the reconciliation checks — did anything break?

vnext_run_checks

8 PASS 2 WARN 1 FAIL

PASS Revenue ties to GL · PASS Cash ties to bank · PASS Monthly P&L reconciled · WARN COGS $24K variance (within threshold) · FAIL OpEx $142K variance in November

Action required: Operating Expenses variance of $142,180 in November. Likely cause: 3 journal entries posted after last Xero sync. Run a re-sync then re-check.

Show me the provenance for OTC Pharma revenue in January.

vnext_get_model · pnl · provenance

CellOTC Pharmaceutical Sales · Jan 2026

Value$58,420,500

StatusForecast

Baselineavg_6m → $53,109,500

Ops Applied1 driver

Xero P&L Jul–Dec 2025 → avg_6m baseline = $53,109,500
+ Op #3: set_driver(growth, +10%) = $53,109,500 × 1.10 = $58,420,500

Source: Knowledge doc “Q1 2026 Product Launch Plan.pdf”
Assumption #7 · 87% confidence · Approved by [email protected]

Every forecast cell works this way — baseline from actuals, then operations applied in order. You can drill into any cell from the P&L tab.

How this works: The agent has 33 registered tools covering model views (P&L, cash flow, balance sheet), forecasting (preview/commit ops, baselines, scenarios), analysis (revenue dashboard, KPI metrics, variance), drilldown (ledger lines, customer concentration), quality checks (11 reconciliation tests), and knowledge integration (document upload, assumption extraction).

04 — Financial Model

P&L Statement — Actual + Forecast

4 ops applied · Baseline: avg_6m · Click any cell for provenance

Global Consumer Health Division — Financial Model

6 months (Oct 2025 – Mar 2026) | 3 actual + 3 forecast

Guide

CEO Summary

P&L

Cash Flow

Balance Sheet

Revenue

P&L Explorer

AR / AP

KPIs

Variance

Scenarios

Health

Line Item	Oct 25	Nov 25	Dec 25	Jan 26 F	Feb 26 F	Mar 26 F	Total
REVENUE
OTC Pharmaceutical Sales	$52.8M	$54.1M	$56.7M	$58.4M	$60.2M	$62.0M	$344.3M
Medical Device Revenue	$22.6M	$21.9M	$22.3M	$22.3M	$22.3M	$22.3M	$133.7M
Consumer Wellness	$10.8M	$11.2M	$12.5M	$11.5M	$11.5M	$11.5M	$69.0M
Licensing & Royalties	$2.2M	$2.2M	$2.5M	$2.3M	$2.3M	$2.3M	$13.8M
Total Revenue	$88.5M	$89.4M	$94.0M	$94.5M	$96.2M	$98.1M	$560.7M
COST OF SALES
Raw Materials & API	($14.8M)	($15.1M)	($15.7M)	($15.2M)	($15.2M)	($15.2M)	($91.2M)
Manufacturing & Packaging	($8.5M)	($8.7M)	($9.1M)	($8.8M)	($8.8M)	($8.8M)	($52.7M)
Quality & Compliance	($3.4M)	($3.5M)	($3.6M)	($3.5M)	($3.5M)	($3.5M)	($21.2M)
Distribution & Logistics	($5.2M)	($5.4M)	($5.6M)	($5.4M)	($5.4M)	($5.4M)	($32.5M)
Total Cost of Sales	($32.0M)	($32.7M)	($34.0M)	($32.9M)	($32.9M)	($32.9M)	($197.6M)
Gross Profit	$56.4M	$56.7M	$60.0M	$61.6M	$63.3M	$65.1M	$363.1M
OPERATING EXPENSES
Sales & Marketing	($12.5M)	($12.8M)	($13.2M)	($12.8M)	($12.8M)	($12.8M)	($77.1M)
Research & Development	($8.6M)	($8.6M)	($9.1M)	($9.5M)	($9.5M)	($9.5M)	($54.9M)
General & Administrative	($4.8M)	($4.9M)	($5.0M)	($4.9M)	($4.9M)	($4.9M)	($29.6M)
Regulatory & Legal	($2.8M)	($3.0M)	($3.1M)	($3.0M)	($3.0M)	($3.0M)	($17.8M)
Total Operating Expenses	($28.8M)	($29.4M)	($30.5M)	($30.2M)	($30.2M)	($30.2M)	($179.4M)
Net Income	$27.7M	$27.3M	$29.5M	$31.3M	$33.1M	$34.9M	$183.7M

Forecast (baseline) Override / driver applied Negative value

Cell Provenance: Click any forecast cell to see the full calculation chain — source data, baseline method, operations applied, knowledge document reference, and approver. Every value is traceable to its origin.

05 — P&L Explorer

Customer Concentration — Revenue by Segment

Same P&L structure, pivoted by customer instead of account. Interactive treemap and drilldown table.

14.7%

Top-1 (CVS Health)
Single-client share

52.9%

Top-5
Concentration

64.5%

Top-10
Concentration

824

HHI Score
Low concentration

#	Customer	Segment	Revenue	Margin	% Total	MoM
1	CVS Health	Enterprise	$124.8M	63.0%	14.7%	+4.2%
2	Walgreens Boots Alliance	Enterprise	$98.2M	62.0%	11.6%	+2.8%
3	McKesson Corp	Enterprise	$78.4M	61.0%	9.3%	+1.9%
4	AmerisourceBergen	Enterprise	$62.1M	61.0%	7.3%	−1.2%
5	Cardinal Health	Enterprise	$54.6M	61.0%	6.4%	+3.5%
6	Kaiser Permanente	Health Systems	$42.8M	63.0%	5.1%	+6.1%
7	Rite Aid	Retail	$28.4M	60.0%	3.4%	−8.2%
8	HCA Healthcare	Health Systems	$24.2M	62.0%	2.9%	+1.4%
9	Walmart Health	Retail	$18.6M	60.0%	2.2%	+12.4%
10	Cigna Group	Insurance	$14.8M	58.0%	1.7%	+2.1%
	All Other (142 customers)		$300.4M	61.5%	35.5%
	Total		$847.2M	62.4%	100%

Portfolio is well-diversified: HHI of 824 indicates low concentration. No single customer exceeds 15% of revenue. The top-5 contribute 52.9%, a healthy distribution across major enterprise accounts.

Watch list: Rite Aid revenue declining −8.2% MoM — potential credit risk. AmerisourceBergen also trending down (−1.2%). Customer concentration treemaps available via the P&L Explorer tab.

06 — Cash Flow & Receivables

Cash Flow Statement & AR Aging

Direct method cash flow with 3-month forecast. AR aging analysis with collection risk flags.

$130.2M

Current Cash
Dec 31, 2025

$14.6M

Avg Net Cash
per month

38 days

DSO
-2 days vs prior Q

$8.2M

AR Overdue >60d
3 customers flagged

AR Aging Buckets

Customer	Total	Current	1–30d	31–60d	61–90d	90+d
CVS Health	$8.2M	$5.1M	$2.1M	$620K	$360K	—
Walgreens	$6.4M	$4.0M	$1.4M	$580K	$390K	—
McKesson	$4.8M	$2.8M	$1.3M	$420K	$280K	—
AmerisourceBergen	$3.6M	$1.8M	$940K	$480K	$240K	$160K
Rite Aid	$2.8M	$840K	$620K	$512K	$480K	$360K
Total AR	$34.7M	$18.4M	$8.1M	$4.2M	$2.8M	$1.2M

Collection risk: Rite Aid has $360K in the 90+ day bucket — highest single-customer overdue balance. AmerisourceBergen also aging at $160K 90+ days. Both flagged for follow-up. Remaining portfolio is well within terms.

07 — Platform Capabilities

Feature Summary

Complete feature set of the Pecunio AI financial modelling platform.

Deterministic Forecasting Engine

Op-based: every change is a discrete, reversible operation
5 driver types: growth, fixed, ratio, allocation, step change
6 baseline methods: trailing averages, last month, YoY
Effective date ranges on all operations
Category-level drivers (apply to all accounts in a group)
Cell-level provenance: traces every value to source data + logic

Preview / Commit Approval Workflow

Agent recommends changes with before/after diffs
Human reviews impact before anything persists
Every committed op tracked: who created it, when, from what source
Undo any operation without side effects
Agent-created vs human-created ops distinguished
Analogous to SOX “read → recommend → approve” pattern

Data Quality & Reconciliation

11 automated checks: revenue ties, expense ties, cash balance ties
Section-level + account-level variance analysis
Known variance suppression (acknowledged discrepancies)
KPI snapshot integrity audits
Uploaded report cross-validation vs live data
NaN/infinity guards throughout the calculation pipeline

Knowledge Base & AI Context

Upload PDF, Word, Excel as business context
LLM extracts structured forecast assumptions from documents
Each assumption: title, rationale, confidence score, proposed op
Propose → approve → reject → commit workflow
Per-tab AI executive commentary generation
RAG context layers for policy/SOP-aware agent responses

33+ Agent Tools

Model views: P&L, cash flow, balance sheet, summary KPIs
Forecasting: preview ops, commit ops, change baseline, scenarios
Analysis: revenue dashboard, KPI dashboard, variance report
Drilldown: ledger lines, top contacts, customer concentration
Quality: reconciliation, accuracy audit, report validation
Context: knowledge docs, assumption extraction, executive briefing

Visualization & Reporting

Schema-driven rendering: backend defines visual structure
7 block types: charts, KPI grids, tables, status lists, key-value
Dual chart engine: Recharts + ECharts (treemaps, composed charts)
Conversation-aware rendering: auto-show/suppress based on intent
Customer concentration treemaps with segment grouping
27-component React workspace with 13+ tabs

Technology Stack

Backend

Python · Django · DRF
LangChain · LangGraph
PostgreSQL · 27 tables

Frontend

React · TypeScript · Vite
shadcn/ui · Tailwind CSS
Recharts · ECharts · SWR

Infrastructure

GCP Cloud Run · Cloud Build
OAuth2 API Integration
CI/CD · Auto-migrations

Platform Showcase

How Pecunio Works

CEO Summary — Model View

Global Consumer Health Division — Financial Model

AI Agent Answering Questions Over the Model

Virtual CFO — Financial Q&A

P&L Statement — Actual + Forecast

Global Consumer Health Division — Financial Model

Customer Concentration — Revenue by Segment

Cash Flow Statement & AR Aging

AR Aging Buckets

Feature Summary

Deterministic Forecasting Engine

Preview / Commit Approval Workflow

Data Quality & Reconciliation

Knowledge Base & AI Context

33+ Agent Tools

Visualization & Reporting

Technology Stack

Backend

Frontend

Infrastructure