Reinventing the spreadsheet for the AI SaaS era with Torben Schulz @Rows

saas.unbound is a podcast for and about founders who are working on scaling inspiring products that people love, brought to you by saas.group, a serial acquirer of B2B SaaS companies.

In episode #27 of season 5, Anna Nadeina talks with Torben Schulz, Founder & COO at Rows, the spreadsheet that thinks outside of the cell!

Torben’s early experience included being a teaching assistant at Harvard for a leadership course. He later co-founded Eat First, a vertically integrated meal delivery startup that ran kitchens, designed meals and handled delivery in markets such as London and Berlin. While Eat First taught him a great deal about operations, Torben decided his next venture should target higher-margin problems — which eventually led to Rows.

Why build a better spreadsheet?

The motivation behind Rows is straightforward: spreadsheets are everywhere (1–2 billion users), but the core experience has changed little in decades. Torben points out that major milestones like Google Sheets (online collaboration) predate modern APIs, SaaS, smartphones and AI — leaving an opportunity to rethink how spreadsheets work today.

“Our approach was a bit different… we wanted to build a better Excel.”

Rows: the spreadsheet that thinks outside the cell

Rows aims to be the best spreadsheet for business users — but reimagined with modern integrations and AI. Key things Rows offers:

• Easy data import with more than 50 native integrations (CRM, marketing tools, data warehouses, databases and bank accounts)
• Ability to drop in PDFs and images and make a spreadsheet out of them
• An AI analyst that responds to natural language prompts to analyze data, build reports and generate formulas
• A flexible UI that mixes document-like pages and draggable elements (tables, charts) for dashboarding
• Mobile-first controls and a side-panel prompt interface so users can work on the go

Rows supports both side-panel prompting and cell-level natural language input. You can type equals in a cell and ask for a lookup or a different function, and Rows will create or replace the formula for you — lowering the barrier for non-formula experts.

“You can just type equals and say… and it will create the VLOOKUP formula directly in the cell.”

AI in Rows: building an “AI analyst”

Rows layers its functionality on top of LLM APIs (GPT-family models and others) and treats the model as an agent that can inspect a document, understand available spreadsheet actions and execute them on the backend. The goal is consistent value delivery: have the assistant solve common business analysis tasks reliably so users can trust it for day-to-day reporting.

To accomplish this, the Rows team combines qualitative feedback and usage analytics. They monitor errors, implement self-healing mechanisms, and iterate on problem areas flagged by users. Torben also draws parallels to the rise of coding assistants: the breakouts for developers and non-technical users are signals that a similar explosion can happen for spreadsheet users.

Notably, Rows does not route the AI analyst through human support — the product is designed to solve problems directly via the model. The focus is on making the AI experience forgiving and consistently useful.

Integrations, data import and product-market fit

Integrations are central to Rows’ value: automation of data imports keeps reports fresh without manual CSV juggling. Rows’ first product primitives were generic web request functions; observing how alpha users employed those calls informed which integrations to build next.

Bank integrations were a clear success — bank account connectivity quickly became one of the most-used integrations. Rows serves business use cases (cash tracking, reconciliations, small business finance dashboards) rather than consumer personal finance.

Product-first engineering culture and rapid shipping

Rows is an engineering-heavy business: engineers and designers form the bulk of the team, and most resources are funneled into product development rather than traditional marketing or sales. The company ships frequently — sometimes weekly — and emphasizes:

• Ownership and autonomy for engineers
• Early demos and iterative feedback loops
• Quarterly roadmap planning that leaves room for flexibility

Torben attributes speed to a culture that balances structure (quarterly goals) and autonomy, with a bias toward shipping MVPs, demoing, collecting feedback and iterating quickly.

Killing features (and learning from them)

Like any product team, Rows has killed features that didn’t fit the core playbook. Examples include early lead-enrichment integrations and some enrichment workflows that raised privacy concerns and didn’t become sticky for their users. Torben notes the importance of weighing engineering effort, privacy and strategic fit when deciding whether to continue or deprioritize features.

One significant project they cancelled was a native desktop app, shelved in 2022. Torben says they may revisit a native app later, but it isn’t a priority for the current year.

Who Rows hires and why resilience matters

Two qualities Torben values most in hires:

• Motivation — people who are excited about the technical challenge, the product or the team.
• Resilience — the ability to cope with rapid change and ambiguity that come with building a startup.

Torben emphasizes that in startups, many situations will change quickly and the ability to adapt — not perpetual motivation for every single task — is critical to succeed and stay sane.

Growth channels and surprising wins

Rows grows largely organically through:

• Direct traffic and word-of-mouth
• Templates and community-shared spreadsheets
• Organic content on YouTube, TikTok, Twitter and other platforms

Two surprises for the team:

• The loginless experience. Letting visitors jump straight into the product without signing up tripled conversion to full signups versus the previous flow.
• Mobile availability of the AI analyst. Making the analyst available on mobile increased analyst usage roughly fivefold — proving that people will use spreadsheets on phones when the experience is built for it.

AI: where it helps and where it doesn’t (yet)

Rows treats the AI analyst as a primary interface for data work, not as an adjunct to human support. Torben argues that for a bottoms-up, self-serve spreadsheet product, the most important thing is the AI’s consistent delivery of value. The team focuses on tooling, fallbacks and monitoring to ensure the analyst helps a wide audience — from non-technical business users to power users who still validate outputs.

Biggest win, biggest mistake and a founder hack

Biggest win: building a product and team that Torben is proud of — a modern spreadsheet that people enjoy using.

Biggest mistake: early emphasis on backend primitives and automation while underinvesting in UI/UX. Rows rebalanced over time, recognizing that productivity tools scale best when their UI and UX are exceptional (examples Torben cites: Notion, Canva, Miro, Airtable).

Founder hack: prepare for a marathon — prioritize resilience and find sanctuary outside of work. For Torben, family time with three kids helps create the separation he needs to recharge. On company policy, he also recommends short notice periods in employment contracts to preserve team morale and mobility.

“The two qualities that we’re really looking for in people are motivation and resilience.”

Where to go next

If you want a closer look at how Rows works in practice — the side-panel analyst, cell-level natural language, integrations and mobile experience — watch the full saas.unbound episode with Torben Schulz on the SaaS Group YouTube channel. The conversation is a practical look at product strategy, rapid engineering culture and how AI can democratize data work for business users.