On-premise Decision AI that better understands financial and manufacturing enterprise data

PolarPulse analyzes financial and manufacturing data on your internal network without sending sensitive enterprise data externally,

generating real-time charts, evidence-based reports, and task-specific Agents — a Secure Decision AI.

Problem

Enterprises hold high-value data, but AI adoption is still hard.

We hold vast amounts of internal data, but security regulations, air-gapped networks, unrefined data structures, and the lack of integration standards across systems keep delaying any AI adoption that's actually usable in our day-to-day work.

CFO, Financial Group Subsidiary

It's hard to send sensitive business data to external APIs like ChatGPT or Claude.

Accountant, IT Service Company

ERP, MES, documents, contracts, disclosures, and equipment logs are scattered, so we can't put them directly to use in decision-making.

Manufacturing Process Lead

From a single natural-language question, instantly generate charts, reports, and task Agents

Dynamic Insight Chart

Generate real-time dynamic charts from a single natural-language question. Executives and operators can instantly see the KPIs, anomalies, and root-cause analyses they need — no complex BI setup required.

Real-time KPI chart generation from natural-language queries
Drill-down across ERP/MES/DB sources
Analysis at account, transaction, process, equipment, product, and inventory level

Evidence PackRule VersioningAudit Trail

Dynamic Insight Report

Surface the most urgent action items with supporting evidence. Not a simple summary — an executable report with root-cause analysis and prioritization grounded in your internal data.

Auto-detection of anomalous transactions, risks, and bottlenecks
Automated root-cause analysis and improvement suggestions
Automated financial review, audit, and compliance reporting

TraceabilityRBACPrompt Policy

Domain Vertical Agent

Build Agents tailored to finance and manufacturing workflows. Connected to internal systems via the MCP standard, extending beyond analysis into real-world task execution.

Finance Agent: credit review, IB due diligence, risk, compliance
Manufacturing Agent: process, inventory, quality, equipment root-cause analysis
Q&A grounded in internal data

Depreciation JELedger ReconcileAudit Pack

Private-by-design Security

On-premise/VPC options, block external data transmission

SSO/RBAC/audit logs/change history built-in

Sensitive data masking and permission-based responses

Traceable output: minimize answers without evidence

How it works

STEP 01

Connect

Data Connection

Connect data from existing systems — ERP, MES, SAP, Oracle, CSV, equipment logs, contracts, disclosures, internal reports, and more.

STEP 02

Understand

Understand enterprise data

Transform enterprise data into AX-Ready Data that AI can understand — built on Schema, Ontology, Knowledge Graph, Semantic Search, and SQL/Cypher.

STEP 03

Act

Analyze & act

From a natural-language question alone, generate real-time charts, risk analyses, process-improvement proposals, inventory-optimization suggestions, and Action Item reports.