Which AI tools do you see as the biggest contenders to classic BI tools?

CES had an AI powered air fryer. I'm sure the AI powered air fryer will work marginally better and have a lot of features I rarely use. I don't think ultimately it would be worth the cost.

I feel the same way about BI tools incorporating AI.

I recently saw a demo of Amazon Quicksight embedded into a web app that's used for data entry.

It puts the analytics directly where the users are.

Quicksight has been around for ages, but I've never used it and years ago when it was announced I wasn't very impressed, so this was all new to me.

The demo looked good and refreshing compared to Power BI. I know it was just a recorded demo, but the capabilities are pretty compelling.

The demo was essentially a simple AI chat input for users to ask questions. QS generates visuals through natural language and can build custom dashboards in response to what users are currently focusing on.

It is similar to Databricks Genie AI, except more accessible to a broader user base.

I heard that the latest y-combinator cohorts normally have several companies trying to build something to compete with the traditional BI tools. There's a sense it's a market ready for disruption and I figure a handful of new companies will probably get big.

I found hex pretty interesting. https://hex.tech/. It might wind up being just for power users, but they're definitely trying something new and different.

Thoughtspot has been getting a lot of traction too.

Also, I work for Quodor Data https://welcome.quodor.com/benefits. Our product is in the works, but still going after that same market.

Naturally, my guess is that the big winners are yet to show up. AI is changing pretty quickly and the stuff that works the best a year from now is going to be very different from what has been working well so far.

Founder in the space here[1], hopefully I can pitch in with a useful perspective: There's definitely growing discontent with legacy BI in the market, but enterprises aren't always able to action on that feeling. These big players have been building thousands of features for years now and they check all the RFP boxes + they have real champions within their companies from folks who have made learning a certain platform their entire career.

The business user may not care where the answer comes from, but the data team who holds the purse string does. And yes these tools are incorporating AI, but I think they're actually struggling to do this right. Most of them are trying to build AI features on top of their intermediate languages[2] instead of SQL directly, but models simply aren't trained on those. These demo well but they don't work well in practice. So they have a serious achilles heal. I think over the next 5-10 years we're going to see the market share of a lot of these players start to erode, especially with newer competitive solutions popping up in the market like Sigma. I'm hearing more and more leadership conversations in the enterprise where it's not just a choice between Tableau, Thoughtspot, Looker and {name your other 2-3 big players}.

Then you have a whole new generation of BI tools that I would call "post-AI" (or right around then which have done a quick pivot into AI), which I'm very bullish on. And yes I'm certainly biased... These are tools that really put AI first and give the admins a good way to really control the output on tightly bounded datasets, rather than trying to boil the ocean and answer any business questions ever asked from the business. Believe it or not, I would actually put Databricks AI/BI Genie[3] in this bucket and also as one of the more interesting solutions out there. I know Databricks isn't new, but this product is, and I think this is much more of what future BI looks like than the old clunky drag-and-drop interfaces or trying to build a chatbot on top of some other non-SQL and non code-versioned YAML or JSON. Expect to see more of this coming from newer players.

[1] Fabi.ai

[2] LookML is an example of an intermediate language - https://cloud.google.com/looker/docs/what-is-lookml?hl=id

[3] https://www.databricks.com/product/ai-bi/genie

If AI agents become highly proficient in Excel or SQL querying—producing "trusted" reports—we’ll be entering a strange new world. I had similar doubts as a beginner in trading, but after just two months with Vector Algorithmics automated strategies, my portfolio has grown, proving the power of automation.

Zenlytic, Veezoo, Numbers Station, or Wallabi all look interesting in different ways. Self-service question answering, semantic layers, connectors, etc.

Last year, my company launched Alviss AI, a platform specifically designed to empower teams in predictive analytics and marketing mix modeling. It’s been a game-changer for us in handling complex business challenges and making data-driven decisions.

What sets Alviss AI apart is its tailored approach to different roles within an organization. For example, technical users can dive deep into customizable models, refine them, and manage sophisticated workflows. Meanwhile, non-technical users can access intuitive tools to extract actionable insights and create strategic plans without needing to understand the underlying technicalities.

Some standout features:

• Predictive Analytics & Optimization: It uses Bayesian Deep Learning to forecast demand, simulate scenarios, and optimize budgets for maximum ROI.

• Transparency & Attribution: With detailed attribution analysis, it measures direct and indirect impacts while offering uncertainty estimations to inform risk-aware decisions.

• Data Integration: It centralizes diverse data sources—marketing, sales, macroeconomic factors, weather, and more—giving a holistic view of business dynamics.

• Real-Time Reporting: Through a robust API, it integrates seamlessly with tools like PowerBI for real-time reporting and automation.

We’ve seen tremendous value in using Alviss AI to quantify the ROI of marketing campaigns, forecast market trends, and align strategies across teams. If you're exploring tools for predictive analytics and business intelligence, it’s definitely worth a look!

Check it out at https://alviss.io/

I built BlazeSQL.com, which does exactly this ("get answers easily, fast, and with reliable results"), but only for SQL Databases.

It connects to the DB, queries the information schema to pull the structure of the database, and lets users optionally add notes, descriptions, example queries, and any other context to help the AI assistant understand the DB.

Both non-technical and technical users can then simply tell the chatbot what they want, and it queries the database and optionally visualizes results.

Results can then be saved, shared, exported, added to a dashboard, or added to a weekly AI-generated e-mail reports that summarizes the changes. Any of these things can be done in 2 clicks.