Why Dashbud?
Every business runs on data. You already have it — probably more than you want to think about right now:
- Spreadsheets and other local and cloud-hosted data files
- Myriad business platforms: CRM, POS, ERP, marketing, advertising
- Dedicated data resources such as databases and data lakes
So how do you use that data? How do you grab the data you need and turn it into information you can act on?
Every approach has trade-offs →Every approach has trade-offs:
| Approach | Positives | Negatives |
|---|---|---|
|
SaaS Dashboards
QuickBooks, Google Analytics, etc. | Built in, no setup |
|
|
BI Tools
Power BI, Tableau | Powerful, enterprise-grade |
|
|
Spreadsheets
Excel, Google Sheets |
|
|
|
AI Workflows
Claude, ChatGPT |
|
|
- + Built in, no setup
- − Clunky interfaces, can't mix data sources
- + Powerful, enterprise-grade
- − Hard to learn, expensive, require a data team
- + Flexible, existing expertise
- − Fragile, hard to update/share, competence tax
- + Fast and surprisingly capable
- − Calculations opaque, privacy/security concerns
- − Doesn't scale, vibe-coding problem
You can build a reporting workflow in Claude or ChatGPT. Get it to write a Python script, hook up a cron job, pipe the output to email. It works! But there are serious issues to be aware of.
What happens next?
- Who maintains the script? Who modifies it when requirements change?
- What happens when someone else wants a different view — filtered, grouped differently?
- This is the competence penalty — anyone who has created a great spreadsheet knows the perils of becoming its owner. But worse: now it's code, and code you didn't write yourself.
You can build yourself a report. But now you're the data team, the DevOps team, and the support desk — none of which is your actual job.
Flexibility, scope, and accuracy
- AI workflows are fine for simple reports. Complications arise when you make a calculation — even just combining two numbers. Calculations involve assumptions and need to be audited.
- Who checks the calculations? AI wrote you a Python script. Can you read it and guarantee it's correct?
- This is the dueling reports problem: Candace's report says x, Mike's says y. Except worse, because AI makes the reports more opaque and difficult to audit.
You can build yourself a report. But even the least complexity requires you to audit and justify the calculations, and AI workflows make this more difficult.
Privacy and security
- Generalist AI tools such as Claude Code aren't private or secure by default. When you invite them to look at your data, they will inspect sensitive data and may train on it.
- You can build a workflow that is secure, but it requires knowledge, discipline, and auditing.
- For any regulated industry — finance, healthcare, legal — allowing your team to use generalist AI tools with your data is a terrible idea and may be illegal.
AI can power your analytics without seeing your data. That's what Dashbud does.
How Dashbud helps
vs. SaaS platforms
- Well-designed conversational interface — not an afterthought.
- Works across multiple data sources — not siloed.
vs. BI tools
- Same analytical power and polished display formatting.
- Interactive charts and dashboards out of the box.
- Weeks of platform training not required.
vs. Spreadsheets
- Flexible reporting without the fragility.
- Built-in data updates, versioning, rollback.
vs. AI workflows
- Same AI-powered outputs — but the infrastructure is built for you.
- Calculations are auditable SQL.
- Business rules and assumptions are shared: decided by agreement, not an AI script.
Switching is easySwitching to Dashbud is easy
Your spreadsheets →
Upload them. Ask questions in plain English. Replace complex, fragile tables with stable reports.
Your SaaS platforms →
Connect via API. See all your data in one place. Stop switching between dashboards.
Your database / ERP →
Connect directly. No exports, no ETL. Reports update live.
Your AI workflow →
Keep the intelligence. Lose the maintenance. Share the results with your whole team.
Designed for privacy, security, and trust
AI never sees your raw data.
Dashbud's agents only see field names and schema — never the actual values in your database.
Deterministic reports.
Dashbud's agent writes a SQL query once. After that, it's a traditional report. Same question, same answer, every time.
Full audit trail.
Every data import is tracked and can be rolled back. Your data stays in your database or in Dashbud's managed infrastructure.
No third-party sharing.
We don't share your data with third parties. We don't use it for AI training.
Ready to see your data in a new light?
Connect your data and start building reports in minutes — not months.