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AI Data Dashboards

Ask your numbers a question.

Your data is spread across a POS, an accounting package, a CRM and several spreadsheets. We join it up, build the views you need, and let you ask questions without waiting for someone to run a report.

From $3,999

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In short

An AI data dashboard brings data from your separate systems, such as sales, accounting, operations and marketing, into one place, then adds an AI layer so you can ask questions in plain English and get answers with the numbers behind them. FIMM cleans and connects the data first, builds the dashboards your managers need, adds a guarded question-answering layer, and sets up weekly AI-written summaries and alerts when something unusual happens.

Business intelligence Natural-language queries Data warehouse BigQuery Weekly AI summaries Anomaly alerts
What we build

What we build.

A

Data preparation

We pull data from your systems, fix duplicates and naming mismatches, and agree on definitions like what counts as revenue or an active customer. Skipping it is how dashboards end up disagreeing with the accounts.

B

A single data store

Your data lands in one well-organized warehouse, typically BigQuery or Postgres on GCP or AWS, refreshed on a schedule so everyone works from the same numbers.

C

Dashboards for each role

Owners see the whole business, location managers see their store, finance sees margins and cash. Each view shows the few numbers that person acts on.

D

Plain-English questions

Ask "which locations had falling repeat sales last month?" and get an answer with a chart. Queries are read-only, limited to approved tables, and show the calculation so answers can be checked.

E

Weekly AI summaries

Every Monday, a short written summary of what changed, what went well and what needs a look arrives by email or Slack, generated from the same governed data.

F

Anomaly alerts

Sudden drops in sales, spikes in refunds or stalled orders trigger an alert to the right person, so problems surface in days instead of at month end.

How it ships

How a data dashboard project runs.

Data preparation comes first because AI on messy data gives confident wrong answers; we reconcile against your existing reports before anyone relies on the new numbers.

01

Inventory

We list your data sources, the questions you need answered, and the definitions everyone should share.

02

Prepare

Data is extracted, cleaned and loaded into a single store, with checks that it matches your source reports.

03

Build

Dashboards, the question layer, summaries and alerts are built and reviewed with the people who will use them.

04

Hand over

Training, documentation and a refresh schedule, with optional ongoing support as your systems change.

Frequently asked

Common questions.

What does an AI data dashboard cost?
Projects start from $3,999 as a one-time build. Hosting and model usage are third-party costs and are billed separately.
Which systems can you connect?
Common sources include Shopify, Square and other POS systems, QuickBooks and Xero, HubSpot and other CRMs, Google Analytics, ad platforms, and spreadsheets. Anything with an API, a database or a regular export can usually be included.
Can AI give wrong answers about our numbers?
It can if left unguarded, so we limit it. Questions run read-only against approved tables with agreed definitions, and every answer shows the query and data behind it. For anything critical, the fixed dashboards remain the source of truth.
Why not use Power BI or Looker instead?
Those are good tools, and we can build on them if you already use one. The real work is the data preparation and definitions underneath; once that is done, the choice of display tool matters much less.
Our data is a mess. Is that a problem?
It is normal, and it is why data preparation is the first phase. We find the duplicates, gaps and conflicting definitions and fix them at the source where possible, so the dashboards and the AI rest on numbers you trust.
Who owns the data and the dashboards?
You do. The warehouse can sit in your own cloud account, and you receive full access, documentation and the code we write. Nothing locks you in to us for future changes.
How often does the data refresh?
A common starting point is an overnight refresh, which suits weekly summaries and daily dashboards. Sources that support it can refresh hourly or close to real time, which matters for things like stock levels or same-day orders.
Can managers see only their own location or team?
Yes. Access is set per person, so a location manager sees their own store while owners and finance see everything. The same rules apply to plain-English questions, so nobody can ask their way into numbers they should not see.
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something.

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