Supaboard

Analytics for people who have work to do.

[Supaboard @Supaboardai]

It's funny how often "data-driven" companies still make decisions based on whoever talks first in a meeting.

The data usually exists.
The answer usually exists.
Neither arrives fast enough.

[Supaboard @Supaboardai]

@boardyai building supaboard, making data queryable in plain english for non-tech teams. need boardy pro for this

[Supaboard @Supaboardai]

is making dashboards really that difficult?
Maybe not?

[Supaboard @Supaboardai]

@kurtbuhler might give a try to supaboard : )

[Supaboard @Supaboardai]

@mdancho84 might try using https://t.co/DvCxinrlun :)

[Supaboard @Supaboardai]

The biggest competitor to most BI tools isn't another BI tool.

It's asking a coworker.
Think about it.

When people need an answer quickly, they rarely open a dashboard first.

They message someone.
The winning analytics products will be the ones that are easier than asking a colleague : )

[Supaboard @Supaboardai]

well, it is what it is,
maybe check it out yourself?
https://t.co/DvCxinrlun

[Supaboard @Supaboardai]

It was designed around data, not decisions.

This is the biggest one.

Most BI tools were built for exploring datasets.

Modern teams care about making decisions faster.

The future of analytics isn't more dashboards, more filters, or more charts.

It's reducing the distance between a question and an answer.

[Supaboard @Supaboardai]

Insights live in silos.

The data is in one place.
The dashboards are in another.
The conversations happen somewhere else.
Nobody has the full picture.

[Supaboard @Supaboardai]

Every report needs an analyst.

The best analytics platforms scale knowledge, not requests.

[Supaboard @Supaboardai]

It takes longer to find an answer than to ask a colleague.

If people trust Slack messages more than your BI tool, you've already lost.

[Supaboard @Supaboardai]

It shows what happened, not why.

Most dashboards are great at reporting.

Very few help explain what's actually driving the numbers.

[Supaboard @Supaboardai]

It expects everyone to know SQL.

SQL isn't going away, but business users shouldn't need to learn database syntax to understand their business.

[Supaboard @Supaboardai]

Every question starts with a dashboard.

People don't think in charts. They think in questions.

"Why did revenue drop?"
"What's driving churn?"
"Which campaigns are working?"
If users have to hunt through dashboards before getting answers, something is wrong.

[Supaboard @Supaboardai]

7 reasons your BI tool feels outdated in 2026
(thread below)

[Supaboard @Supaboardai]

The evolution of business intelligence over the years:

2010: Companies built dozens of dashboards and waited weeks just to get basic answers.

2015: Everyone pushed self-service BI but teams were still stuck waiting on analysts for reports.

2020: We had too many tools yet almost no one could actually make fast decisions with data.

2023: ChatGPT arrived and suddenly people wondered why they couldn't just ask questions to their own business data.

2026: You type one plain English question and get instant insights, charts, and answers.That's exactly why we built Supaboard. Natural language analytics that actually works for non-technical teams. No SQL.

No tickets. No long waits.Just real answers in seconds.
What year does your company's data setup still feel stuck in? Drop it below.

[Supaboard @Supaboardai]

Something I've noticed over the last year:

Companies are collecting more data than ever, but most employees still struggle to answer basic business questions.

How many customers did we gain last month?

Which channel is performing best?

Why did revenue dip this week?

The issue isn't a lack of data. The issue is that accessing it is still harder than it should be.

We've spent years solving storage, infrastructure, and visualization. The next challenge is making information actually accessible to the people who need it.

[Supaboard @Supaboardai]

@anupamrjp https://t.co/kmGplgq2Ys :)

[Supaboard @Supaboardai]

Most teams still wait days for a dashboard. We built Supaboard so anyone can ask “Why did revenue drop last week?” in plain English → get charts + why + what to do next.

No SQL. No data team. Just answers.

Try it today https://t.co/kmGplgq2Ys

[Supaboard @Supaboardai]

The most interesting AI story right now isn't a new model.
It's electricity.
Every week there's news about bigger data centers, more chips, more infrastructure, and larger investments. The industry is pouring hundreds of billions into AI infrastructure.

A few years ago the question was:
"Can AI actually do useful things?"
Today the question is:
"Can we build enough infrastructure to keep up with demand?"

That's a huge shift.
The bottleneck is no longer ideas.
It's compute. Power. Data.

The companies that win the next phase of AI may not be the ones with the smartest models.
They might be the ones that can actually run them at scale.