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.

Replacing the Management Consultant With Decision Intelligence

Executives run on McKinsey-style decks and Power BI. DataBlueprint connects them read-only and answers the questions neither system can.

Executives run on McKinsey-style decks, Power BI, and Tableau. Each system reports on its own slice. None of them answer the questions that drive executives' weekly decisions. McKinsey-style decks tracks operations. Power BI tracks money. The link between them lives in spreadsheets and memory. DataBlueprint connects every system, builds a Knowledge Graph of your business, and answers questions across all of it. It is a private LLM powered by AWS Bedrock, with read-only access to your systems. You ask a question. You get a Decision Brief with the numbers and the source rows behind them.

What Is Decision Intelligence?

Decision Intelligence is a category. It is not Business Intelligence with a chatbot bolted on. Business Intelligence shows historical numbers in dashboards. Decision Intelligence answers business questions across every system you run. DataBlueprint is the Decision Intelligence platform from Inzata Analytics. It connects to McKinsey-style decks, Power BI, and the rest of your stack through read-only connections. It builds a Knowledge Graph that maps how your customers, jobs, transactions, and people relate. A private LLM powered by AWS Bedrock reads that Knowledge Graph and answers questions in plain language. Every answer cites the rows it used. The Knowledge Graph stays in your environment. AWS Bedrock contractually guarantees your inputs and outputs are never used to train or improve foundation models.

What Executives Cannot Answer Today

The current stack reports the obvious numbers. The hard questions sit between systems. Here are five questions executives ask every week that McKinsey-style decks, Power BI, and Tableau cannot answer on their own:

Which customers, jobs, or accounts produce the highest true margin after labor, parts, and overhead?
Which McKinsey-style decks records have not been reconciled with Power BI this month, and what dollar amount is at risk?
Where did our gross margin actually move this quarter, broken down by line, region, and source system?
Which staff or producers contribute the most revenue per hour after non-billable time?
Which renewals, repeat clients, or recurring jobs are trending down before the loss shows up in Power BI?

None of those answers live in one report. They live across McKinsey-style decks, Power BI, and Tableau. Stitching them together by hand takes days. By the time you have the answer, the decision has moved on.

What Executives Leaders Can Ask DataBlueprint

DataBlueprint connects McKinsey-style decks, Power BI, and Tableau and answers cross-system questions in seconds. Every answer is a Decision Brief: the number, the trend, the contributing rows, and the recommended next action. Examples of questions executives ask DataBlueprint:

Margin by customer. Combine McKinsey-style decks jobs, Power BI invoices, and labor cost to rank customers by true contribution margin.
Reconciliation gaps. List every McKinsey-style decks transaction that has not posted to Power BI in the last 30 days, with dollar value.
Producer or staff productivity. Show revenue and margin per person, per hour, blended across McKinsey-style decks and Power BI.
Trend variance. Identify the three line items that drove this month's gross margin movement and explain why.
Retention risk. Flag accounts whose activity in McKinsey-style decks has dropped while their billing in Power BI stayed flat.
Capacity vs demand. Compare scheduled capacity in McKinsey-style decks to forecasted demand and surface the next bottleneck.

Every answer cites the source rows. You can click through to the underlying records in McKinsey-style decks and Power BI to verify before acting.

How Decision Intelligence Differs From Dashboards

Side by side:

Dashboards show fixed charts. DataBlueprint answers any question in plain language.
Dashboards live in one tool at a time. DataBlueprint reads McKinsey-style decks, Power BI, and Tableau together.
Dashboards require a data team to build new views. DataBlueprint builds the Knowledge Graph automatically.
Dashboards show what happened. DataBlueprint explains why and recommends what to do next.
Generic AI tools guess. DataBlueprint uses a private LLM powered by AWS Bedrock with read-only access to your real data, and cites every row.

BI shows the past. Decision Intelligence answers the next question.

Getting Started

Connecting McKinsey-style decks, Power BI, and the rest of your stack takes about an hour. Every connection is read-only. DataBlueprint never writes back to any system. The Knowledge Graph builds automatically from your real records. The private LLM powered by AWS Bedrock runs against that graph inside your environment. Your data never leaves your environment. AWS Bedrock contractually guarantees your inputs and outputs are never used to train or improve foundation models. Within a day, executives are asking questions across McKinsey-style decks, Power BI, and Tableau and getting Decision Briefs back with traceable answers.

Frequently Asked Questions

What does DataBlueprint do for executives?

DataBlueprint connects McKinsey-style decks, Power BI, and Tableau through read-only connections, builds a Knowledge Graph of your business, and uses a private LLM powered by AWS Bedrock to answer cross-system questions. Executives get Decision Briefs with the numbers and the source rows behind them.

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

BI tools display dashboards on data you have already prepared. DataBlueprint reads McKinsey-style decks, Power BI, and Tableau directly, builds the Knowledge Graph for you, and answers any business question in plain language. Every answer cites the rows used.

Does DataBlueprint write to McKinsey-style decks or Power BI?

No. Every connection is read-only. DataBlueprint never writes back to McKinsey-style decks, Power BI, or any other system. It reads, models, and answers.

Is my data used to train AI models?

No. AWS Bedrock contractually guarantees your inputs and outputs are never used to train or improve foundation models. The Knowledge Graph DataBlueprint builds is intentional. It maps your business to give your private LLM context. That stays in your environment.

How long does it take to connect McKinsey-style decks and Power BI?

About an hour for the initial connections. The Knowledge Graph builds automatically from your real records. Most executives are asking real questions the same day.

Who is DataBlueprint built for in executives?

DataBlueprint is built for executives who run executives on McKinsey-style decks, Power BI, and Tableau and need cross-system answers their current reports cannot give. Inzata Analytics builds DataBlueprint for operators, not data teams.

Start With DataBlueprint

Executives get Decision Briefs across McKinsey-style decks, Power BI, and Tableau in a day, not a quarter. Connect read-only, ask the questions McKinsey-style decks and Power BI cannot answer, and act on traceable answers from a private LLM powered by AWS Bedrock.

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