Company Video

Data Loops, with Blitzy CEO Brian Elliott

Brian Elliott, co-founder and CEO of Blitzy, talks with Aleks Jakulin about data provenance, civic data infrastructure, AI-assisted analysis, and why useful data needs a sustainable business model. Blitzy announced a $200M growth round at a $1.4B valuation in May 2026.

• Featuring Aleks Jakulin
• Hosted by Brian Elliott, co-founder and CEO of Blitzy
• Topic: data provenance, data excellence, civic data loops, AI-assisted analysis
• Source transcript: edited from automatic transcription

Why Listen

This conversation starts from a problem that sits underneath the AI boom: useful data does not appear by magic. Someone collects it, checks it, explains it, and keeps it current. If AI systems consume that work without a business model for the people and institutions maintaining it, the underlying knowledge system decays.

Jakulin frames the alternative as a data loop: better data leads to better visualizations, models, and decisions; better decisions create demand and resources for more data. The loop matters for enterprise analytics, civic dashboards, public decision-making, and data.Flowers' work turning raw data into useful products.

The interviewer matters here. Elliott is building Blitzy around autonomous enterprise software development, and Blitzy's 2026 financing made it one of the more visible AI infrastructure companies in the Boston/Cambridge ecosystem.

Best For

• Leaders thinking about the business model behind high-quality data.
• Civic technologists and public-sector teams building dashboards people actually use.
• Analysts evaluating where AI-assisted data work is already dependable.
• Organizations with valuable datasets that should become usable products.

Edited Transcript Highlights

Brian Elliott: What are the opportunities you are seeing, and what is everyone else missing right now?

Aleks Jakulin: The biggest problem is that we have to think not just about what we do with data, but who gets the data and what the business model is around that data. There is a lot of data available, but the creators of that data need a business model.

Brian Elliott: Your concerns are about data provenance?

Aleks Jakulin: We need a business model for the provenors of data. We also need to understand that access to data is a negotiation: what can you access, what can you not access, and what are the terms?

Brian Elliott: What did you learn from the COVID dashboard work in Slovenia?

Aleks Jakulin: A civic movement of experts made COVID data accessible through an online dashboard. It became the number one search term in the country, and about a quarter of the population used it weekly. People, experts, and the government coordinated around the same view of reality.

Brian Elliott: What is the data loop?

Aleks Jakulin: When people find data useful, they make better decisions and ask for more data. That creates more data, better visualizations, better models, better decisions, better functioning of society, and more resources for data.

Brian Elliott: Where do AI programming tools become dependable first?

Aleks Jakulin: General-purpose programming is still hard, but data analysis is much closer to dependable. When a tool succeeds often and gives immediate feedback, people can rely on it.

Brian Elliott: What are you building now?

Aleks Jakulin: data.Flowers turns data into products. Data by itself is not necessarily useful, but a product is useful almost by definition. Building a product around data is one important step in the data loop.