What is a Decision Topic?

A Decision Topic is anything leadership wants Decision AI to keep watching - a KPI, a customer segment, a contract renewal window, a board question, or a specific risk. Each Decision Topic runs continuously against your Knowledge Graph and produces a Decision Brief whenever something material changes. In the DataBlueprint product UI, Decision Topics appear simply as 'Topics' in the left navigation.

What is a Decision Brief?

A Decision Brief is a board-ready summary produced when a Decision Topic refreshes. It includes the question, the finding, the supporting evidence (with row-level traceability to source systems), and a recommended next move with projected impact.

What is an AI credit?

Credits power DataBlueprint's Decision AI activities - asking questions, refreshing Decision Topics, generating Decision Briefs, and running risk scans across your Knowledge Graph. Consumption depends on the complexity of the request.

What is a Knowledge Graph?

A live, unified map of every entity in your business - customers, contracts, products, costs, people - and the relationships between them, built automatically from every system you connect.

How is DataBlueprint different from a BI tool like Tableau or Power BI?

BI tools show tables and dashboards and require a data team to model and maintain them. DataBlueprint understands business relationships across all your systems, answers strategic questions in plain language, and surfaces recommended actions with traceable evidence. BI tells you what happened; Decision AI tells you why and what to do.

Is DataBlueprint read-only?

Yes, by default. DataBlueprint connects to all source systems in read-only mode. Agent write-back to systems like HR, CRM, and PSA is opt-in per system on the Business tier and requires explicit per-action approval.

Where does AI inference run?

All AI inference runs on a private LLM powered by AWS Bedrock, inside your AWS environment. Prompts, completions, and query results are never sent to OpenAI, Anthropic public endpoints, Google, or any external model provider. AWS Bedrock contractually guarantees customer inputs and outputs are never used to train shared models.

Why a Knowledge Graph Is the Tool CFOs Have Been Waiting For

Variance analysis, working-capital risk, customer profitability — the questions CFOs ask every month live across systems no single tool can join. A Knowledge Graph fixes that.

Talk to a CFO long enough and the same frustration always surfaces: the numbers are correct, but the story behind the numbers takes a week to assemble. Why did margin slip? Which customers are eroding? Where is cash actually stuck? The data exists, but it lives in five systems that do not speak to each other.

A Knowledge Graph is the missing piece.

The CFO's actual problem

A CFO does not need another dashboard. They need an answer to "why." The why almost always crosses systems:

Revenue lives in the ERP
Customers and contracts live in the CRM
Labor and utilization live in the PSA or HRIS
Receivables live in finance
Cost of goods often lives in a separate procurement or inventory system

No BI tool joins these without weeks of analyst work. Every variance question becomes a project.

What the graph changes

DataBlueprint connects to all of these systems read-only and builds a Knowledge Graph that links a single Customer to its contracts, invoices, jobs, technicians, payments, and disputes. A private LLM powered by AWS Bedrock reads that graph when you ask a finance question.

So the CFO can now ask, "Show me the ten customers whose gross margin dropped most this quarter and explain why," and the answer arrives as a Decision Brief — with the breakdown, the contributing systems, and the suggested action — in minutes, not weeks.

Three questions a graph finally makes answerable

True margin by customer. Not the contract margin. The actual realized margin after labor overruns, change orders, write-offs, and unbilled time.
Working-capital exposure by segment. Which segments are stretching DSO and why — driven by dispute reason, sales rep, or product line.
Forward-looking churn risk. Customers whose usage, support tickets, and payment behavior are quietly trending to attrition.

None of these are dashboard questions. They are graph questions.

What you do not have to do

You do not have to consolidate your systems. You do not have to migrate to a new ERP. You do not have to hire a data team. The graph is built on top of the systems you already run, through read-only connections, and refined with a private LLM powered by AWS Bedrock.

CFOs who try DataBlueprint usually describe the same moment: the first time a variance question gets answered before the meeting starts, instead of two weeks after.