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Data protection first
IDT Financial Intelligence Platform
The problem we solve
In most mid-market companies, financial insight is assembled by hand. A CFO relies on one or more analysts who pull reports from QuickBooks, spreadsheets, and other tools, then manually stitch them into a narrative covering what happened last month, why it happened, what it means, and what to do about it. That work is slow and inconsistent, it lives in the heads of a few people, and it doesn't scale.
The tools that promise to fix this tend to force a difficult trade-off. Commercial BI and FP&A platforms give you dashboards but leave the judgment to you; they show you what the numbers are without telling you what to do about them. AI tools that do offer analysis typically send your most sensitive financial data to third-party model providers, where you have little control over how it's used, little visibility into how conclusions are reached, and limited protection if the vendor changes or withdraws the model you built your process on.
The result is that companies often end up choosing between insight and control. The IDT Financial Intelligence Platform is built so you don't have to make that choice.
What it is
An AI-powered financial intelligence platform that acts as a digital fractional CFO, deployed entirely inside your own AWS environment and running on domain-tuned models you own and control.
It combines three layers into one pipeline.
The first two layers give you a governed, real-time financial picture. The third layer is what turns this into an advisory product rather than a dashboard, producing financial judgment instead of just charts.
Layer | What it does |
|---|---|
1. Ingestion | Connects to your accounting system (QuickBooks, or any other platform we configure) or ingests financial data directly via CSV. The ingestion method is flexible; the point is getting your balance sheet, P&L, and supporting data into the system reliably. |
2. Business Intelligence | Reads your core financial statements, computes the key financial and economic metrics, and builds the dashboards and visuals automatically - powered by Amazon QuickSight. This is your always-current source of truth. |
3. The fractional-CFO brain | It reads the calculated financial and statistical results and explains what's happening with your financials, why it's happening, what to expect next, what actions deserve consideration, and which drivers warrant attention. |
What makes it different
The BI platform already runs in customer-owned AWS environments. The causal layer is being productionized for the same deployment model.
The language model works from selected, already-calculated results rather than raw transactions, general ledger data, invoices, or customer and vendor names.
Every financial figure, forecast, causal estimate, and statistical result is calculated before the language model is called. The model turns those finished results into plain-language explanations.
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Numbers stay authoritative. The LLM cannot change the underlying calculations or statistical results.
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Expert calibration. The analysis is configured to the customer's chart of accounts and accounting rules, then reviewed and calibrated with financial experts.
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Clear separation. Calculation, causal analysis, and narrative generation remain separate, so the reasoning behind an explanation can be reviewed.
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Model flexibility. The language layer is separate from the calculations, so changing the underlying model does not change the financial results.
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Financial professionals review the analysis, add context, and refine how it is explained without changing the underlying math.
The causal engine has already been tested on real company data through three expert calibration rounds. As it moves into production customer deployments, automated execution, drift monitoring, and run-level controls are being added around that existing process.
How it's deployed
The platform is designed around two deployment modes, depending on how your organization is structured.
Mode | Who it fits | How it works |
|---|---|---|
Multi-tenant | For organizations that need financial analysis across multiple companies from one platform. | The BI foundation already supports multiple isolated entities under one environment. The causal layer is being extended across the same structure for production customer deployments. |
Single-tenant | A single company that wants its own dedicated deployment | One deployment in your own AWS environment, giving you maximum isolation and control so your financial intelligence stays entirely within your walls. |
Multi-tenant is a core requirement for two of our buyers, not an afterthought:
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Holding companies and multi-entity organizations. If you have multiple LLCs or subsidiaries under one umbrella, you need each company's financial data isolated while still seeing the consolidated picture.
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Fractional-CFO service firms. If you provide CFO services to multiple clients, you need each client's data separated while managing the full client book from one platform.
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In both cases, the objective is the same: one financial intelligence platform with clear separation between entities and direct control over the underlying financial data.
