DBeater.

THE DBEATER PLATFORM

Your business data.
Let's think it through.

AI that learns your database, understands how your business connects and keeps track of change. One shared context, from your first question to your next decision.

Explore DBeaterHow it works

THE WHOLE PLATFORM

Built to work together.
For your business.

01DATA & MEANING

It learns the language of your data.

DBeater discovers your tables and how they connect. It works with you to clarify what “active customer,” “net sales” and your company's own codes mean.

  • A data map of your tables and fields
  • Questions for you when a definition is unclear
  • A shared data dictionary for your team
How does it find relationships?

Similar table names are only a starting point. DBeater checks whether records actually match and asks you to review uncertain relationships.

Are business definitions reused?

Your explanations and approvals are saved. New questions use the definitions your organization has confirmed, rather than guessing them again each time.

Product demo with sample data
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02ASK YOUR DATA

Ask a question. Find the answer in your data.

Ask, “Why did collections fall this month?” DBeater queries the relevant data and explains the result with tables and charts. You can also inspect the query and its sources.

  • Ask follow-up questions about an answer
  • Export results to CSV or Excel
  • Inspect the query in DBeaver
Save the questions you ask often.

Once you have verified an answer, you can pin its query plan. Asking again runs the same plan on current data. Important answers can be saved and revalidated when table structures change.

What if there isn't enough information?

DBeater may ask you to clarify the question, show which part of the answer is missing or explain why it cannot answer.

Product demo with sample data
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03METRICS & MONITORING

Notice the change before you ask.

Choose the metrics and processes you want to follow. DBeater learns their historical range, spots changes that need attention and groups related findings into one update.

  • You decide what gets monitored
  • Expected ranges and deviations based on past behavior
  • Related findings brought together in one summary
Not every change needs an alarm.

Rising sales and rising complaints mean different things. DBeater considers the business meaning of a metric, groups signs of the same event and filters out noise. Numbers in the summary are checked against source results.

How often does it check?

Daily, weekly and monthly checks are supported. Where the infrastructure supports it, data-change events can also trigger analysis. A topic you stop monitoring does not reopen on its own.

Product demo with sample data
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04BUSINESS RULES

Where's the record that should be there?

A paid order may still be waiting for shipment. A completed service may have no invoice. DBeater suggests business rules from past records and uses the rules you approve to watch for gaps and delays.

  • Missing records, delays, amount mismatches and process steps
  • Suggested rules checked against historical data
  • Issue tracking with a source record, an owner and a deadline
You approve the rules.

Not every table relationship is a business rule. Suggestions are tested on past cases and presented with supporting evidence. Rules need your approval to run. Rejected rules are not repeatedly suggested with different wording.

Take a closer look
Product demo with sample data
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05SIMULATE

Try it before you put it into practice.

What if prices, costs or demand change? Compare the baseline with a new scenario on synthetic data that reflects your dataset. See the most affected groups and the range of possible outcomes.

  • Synthetic data that doesn't copy real people
  • Impact by branch, channel or customer group
  • Visible assumptions and repeatable scenarios
What is a synthetic twin?

A test environment that preserves distributions and selected relationships in your data without copying real records. Personal fields are left out.

How should I interpret the result?

A simulation depends on the assumptions you choose. The interface separates measured information from assumptions and shows uncertainty. It does not guarantee what will happen in the real world.

Take a closer look
Product demo with sample data
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06INVESTIGATE & EVIDENCE

What happened? What might explain it?

Find the records, time period or branch where a change is concentrated. DBeater suggests a possible explanation and the next steps to check it.

  • Measured results separated from possible explanations
  • An investigation of metrics that change together
  • Follow the investigation with another question
Is changing together enough to prove a cause?

Two metrics moving at the same time does not mean one caused the other. DBeater also suggests alternative explanations and what you would need to test next.

Product demo with sample data
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07TODAY

Keep the day's important work in view.

Important changes, open issues and pending decisions in one place. Finance, operations and leadership each get a daily summary shaped around their responsibilities.

  • A daily agenda tailored to your role
  • Important metrics and recent changes
  • Work waiting for someone to take ownership or make a decision
Does everyone see the same summary?

The agenda follows each person's approved role and responsibilities. The financial impact of a change may go to finance, while an operational delay goes to operations.

Product demo with sample data
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08ISSUES & OWNERSHIP

Make it clear who takes it from here.

Turn an important finding into work with an owner and a response time. Follow who picks it up, where it stands and how it is resolved.

  • Routing by person, team and severity
  • Response times and escalation when needed
  • Tracking from ownership to resolution
Who decides where a finding goes?

DBeater can suggest roles and responsibilities. Real recipients and routing permissions require your approval. If there is no suitable approved recipient, the issue stays in draft.

Product demo with sample data
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09TRUST CENTER

See what your analysis relies on.

Definitions, table relationships, metrics, data quality and freshness are checked separately. See missing approvals and which analyses may be affected by a change.

  • Readiness checks across six areas
  • Impact analysis for table and column changes
  • A missing check is never treated as a pass
What does Change Review do?

It examines how a table or column change affects metrics, saved answers and rules. Discovery and validation can be run again after a change.

How is access managed?

Enterprise sign-in, role-based permissions and user management are supported. Source databases are accessed read-only. See the Security page for details.

Take a closer look
Product demo with sample data
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A FEW THINGS YOU MAY BE WONDERING

One platform.
Clear answers.

Where should we start?

Choose one data source and a few business questions. Verify the definitions and answers together. Then add the metrics, business rules and responsible teams you need.

Who confirms business definitions?

DBeater discovers tables and relationships. When a definition is unclear, it asks someone who knows the business. You decide what gets monitored and which rules run.

Is it publicly available?

DBeater has a working prototype, and we're preparing for enterprise pilots. Public installation files are not yet available.

DBeater Desktop

DBeater, on your desktop.
Coming soon.

About the first release macOS · Windows · Linux

LET'S TAKE A LOOK

How would DBeater
work for your business?

Let's talk about your data sources, the problem you want to solve
and the ideas you'd like to explore.

CONTACT

What's on your mind?

A question, a pilot idea or something specific you need. We'd like to hear it.

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DBeater

Let's figure it out.

Hi there.

What's on
your mind?

Let's get to know DBeater. Where would you like to start?

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