● Powered by MiMo V2.5 Pro

AI-Powered Financial
Intelligence Platform

Automate invoice processing, detect anomalies in real-time, and generate compliance reports — reducing manual finance ops by 90%.

0
M+ Documents Processed
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% Extraction Accuracy
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Enterprise Clients
0
% Cost Reduction
Interactive Demo

See It In Action

Upload a financial document or select from sample data to see MiMo's analysis engine in real-time.

📄 Document Upload
🧾 Invoice Parsing
🔍 Anomaly Detection
📁

Drop financial documents here

or click to analyze sample Q4 financial report

Supported: PDF, XLSX, CSV, JPG, PNG • Max 50MB

Analysis Complete

✓ Processed
Platform Capabilities

Built for Finance Teams

Every feature designed around real workflows — not generic AI demos.

📄

Smart Document Extraction

Multi-model OCR pipeline extracts line items, totals, tax codes, and vendor details from any invoice format — even handwritten receipts.

99.2% accuracy
🔍

Anomaly Detection Engine

Statistical + ML anomaly scoring across transaction patterns. Flags duplicate invoices, unusual amounts, vendor fraud, and policy violations.

Real-time alerts
📊

Auto-Reconciliation

Matches bank statements to invoices with fuzzy logic. Handles partial payments, currency conversions, and multi-entity books.

3-second matching
📋

Compliance Reports

Generates SOX, IFRS, and GAAP-ready reports automatically. Audit trail with full document lineage and timestamp verification.

Audit-ready
💬

Natural Language Queries

Ask questions in plain English: "Show all vendor payments over $10K last quarter" — get instant structured results with source citations.

MiMo V2.5 Pro
🔗

API & Integrations

REST API with OpenAI-compatible SDK. Native connectors for QuickBooks, Xero, SAP, and 30+ ERP systems.

One-line setup
Real Impact

Use Cases & Results

🏢 Enterprise AP Automation

Mid-market SaaS company processing 8,000 invoices/month across 12 entities. Manual entry took 3 FTEs and 5 days per close cycle.

92%
Less manual work
5→1 days
Close cycle
$180K
Annual savings

🛡️ Fraud Detection for Fintech

Digital banking platform with 200K+ daily transactions needed real-time fraud scoring without adding latency to payment flows.

340ms
Avg detection
$2.1M
Fraud prevented/yr
0.03%
False positive rate

📑 Audit Prep for Accounting Firm

Regional firm handling 45 client audits/year. Document gathering and reconciliation consumed 60% of senior staff time.

70%
Faster prep
3x
More clients/yr
$420K
Revenue increase

🌍 Multi-Currency E-Commerce

Global marketplace with 15 currencies, 200+ vendors, and complex tax jurisdictions. Reconciliation was a monthly nightmare.

99.7%
Match rate
15→0
Currency errors/mo
$95K
Saved on FX alone
Architecture

How It Works

📤

Upload

PDF, CSV, XLSX, or API feed

→
🧠

MiMo Extract

Multi-model OCR + NER

→
🔍

Analyze

Anomaly + compliance scan

→
🔗

Reconcile

Auto-match to ledger

→
📊

Report

Dashboard + export

Developer Experience

One-Line Integration

analyze.py
import mimo_finance as mf

# Initialize with your MiMo API key
client = mf.Client(api_key="mimo-...")

# Upload and analyze a financial document
result = client.analyze("invoices/q4_batch.pdf")

# Results include extracted data + anomaly scores
print(result.total_amount) # $847,293.50
print(result.anomalies) # [Anomaly(dup_inv, severity=0.94)]
print(result.confidence) # 0.992

# Natural language query over your financial data
answer = client.query("What vendors had payments over $50K in Q4?")
for vendor in answer.results:
    print(f"{vendor.name}: {vendor.total}")