AI Data Analyst Agent – An AI analyst for your business data

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How it flows

Ask in plain language, get an answer you can act on

Inputs

CRM
Sales data
Ad platforms
Stock, orders
Spreadsheets

AI Data Analyst

Understands · Calculates · Compares

A clear answer
Charts & reports
What to look at
Report history
Data sources
Access control

Outcomes

The Agent only answers within the data your business grants access to.

The questions businesses need answered

  • How did revenue change this week versus last week?
  • Marketing spend is up — did leads go up with it?
  • Which products are selling and which are sitting in stock?
  • Which metrics are below target this month?
  • Is there anything in today's report I should look at?
Capabilities

What an AI Data Analyst Agent can do

  1. 1

    Consolidate data from several sources

    Connects the systems you already use to bring together sales, marketing, customer or operations data.

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    Limits & controls: The integration scope is set per project and depends on what each system allows.

  2. 2

    Ask questions straight to the data

    Managers ask in plain language instead of filtering spreadsheets or building a report from scratch.

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    Each answer can be followed by a deeper question in the same conversation, rather than starting another report.

  3. 3

    Analyse and compare figures

    Compares across time, product, branch, campaign or department to show what actually changed.

  4. 4

    Generate reports automatically

    Prepares daily, weekly or monthly reports from the template and metrics you choose.

  5. 5

    Flag changes worth checking

    Detects metrics crossing the thresholds you set — cost rising, conversion falling — so the right person takes a look.

  6. 6

    Help you look for the cause

    Suggests the factors that may be involved and the data to check next.

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    Limits & controls: The Agent never asserts a cause from a coincidence between two metrics.

  7. 7

    Permissions and traceability

    Sets who may see which data, and keeps the source and processing history within the scope deployed.

Delivery

How Naventic delivers it

  1. 01Survey the goals and the management questions
  2. 02Check the data sources
  3. 03Build the Agent around your operations
  4. 04Test against real figures
  5. 05Hand over and improve

Testing compares the Agent's answers against reports your business has already signed off, starting with the metrics that matter.

Good fit

Which businesses is it for?

  • Retail & e-commerce

    Revenue, products, orders and stock.

  • Agencies & marketing

    Campaign spend, leads and channel performance.

  • Store chains

    Comparing results across branches.

  • Service businesses

    Customers, bookings, revenue and return rate.

  • B2B companies

    Opportunities, contracts and pipeline progress.

  • Multi-department companies

    Consolidated KPIs and management reporting.

A conversation with the AI Data Analyst Agent

AI Data Analyst Agent

Give me an overview of this month's revenue.

Revenue report — September

420m VND

Revenue

+12%

vs last month

Revenue is up on last month. Product group A contributes most of the increase in the sample data.

Did marketing spend rise by the same amount?

Marketing spend — September

+20%

Spend

+12%

Revenue

Marketing spend rose 20% over the same period, ahead of the 12% revenue increase. Those two figures alone are not enough to call the campaign ineffective. I can cross-check leads, new customers and revenue by channel if that data is connected.

Every figure in this conversation is illustrative, not a real result from Naventic or a client.

How is it different from a dashboard?

A regular dashboard

AI Data Analyst Agent

Shows the charts someone set up in advance

Answers new questions within the data it may access

You find and filter the information yourself

You ask in plain language

Reports follow a fixed template

Produces explanations and reports on request

You have to spot the change yourself

Raises alerts from the rules you set

The two do not replace each other: a dashboard suits day-to-day monitoring, the Agent makes the data easier to explore. Naventic can combine both in one system.

Other solutions

Services overview

Frequently asked questions

Do we need anyone who can code?＋

No. Managers ask in plain language, like sending a message; connecting the data, defining the metrics and setting permissions is Naventic's work during delivery.

Can it connect to Excel, Google Sheets or our CRM?＋

Spreadsheets and systems with an API or another suitable connection can be in scope. Naventic checks each source during the survey before defining the integration scope.

Does the AI make business decisions?＋

No. The Agent presents figures, comparisons and things worth checking; the decision stays with your managers. It also never asserts a cause from a coincidence between two metrics.

Is access to our data controlled?＋

Yes. You decide who may see what; permissions are enforced in the data layer, and the system keeps the source and processing history within the scope deployed.

What if our data is incomplete or metrics are defined differently?＋

The Agent says what is missing instead of producing a number nobody can verify. The survey usually starts by reviewing the sources and agreeing how each metric is calculated.

Turn your data into something managers can act on

Every business has its own systems and way of running. Share your data sources and the metrics you track so Naventic can propose a fitting solution.

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