Aug 7th, 2025
How SpellBook's VP of Finance transformed 8-10 Hours of manual data work into minutes with Julius
By Laura Clugston · 4 min read
“Julius has been a game changer for us because now I'm able to just upload our data set, and that 8 to 10 hours a week has turned into a couple of minutes.”
- Aman Samra, VP of Finance
At SpellBook, the leading generative AI tool for legal professionals, VP of Finance Aman Samra was drowning in spreadsheets. As the company scaled to serve thousands of legal professionals streamlining document drafting and review, the finance team faced a familiar yet frustrating challenge: massive datasets that demanded hours of manual processing just to extract basic insights.
When high-volume growth meets manual data processing
SpellBook's success created an unexpected problem for their lean finance team. As a high-volume business processing extensive legal document workflows, the company generated datasets with over 100,000 lines of data regularly. For Aman, whose background was in finance rather than data science, this meant spending 8-10 hours every week on a painful, manual process.
"We would extract data from Snowflake and import upwards of 100,000 lines into Excel files," explains Aman. "I was spending 8 to 10 hours cleaning, extracting, and making the data useful for our stakeholders."
The process was not only time-consuming but also limiting. As VP of Finance, Aman needed to focus on strategic capital allocation decisions, but instead found himself trapped in Excel spreadsheets.
"My go-to tool was Excel, and you can imagine, as a VP of Finance, I'm not a data expert by any means," says Aman. The lack of specialized data science skills on the lean team meant that critical business insights were either delayed or simplified to fit within Excel's limitations.
Discovering a data scientist in your pocket
The solution came through an unexpected channel. "You guys have done an amazing job through your organic marketing, so I found you guys through Twitter," Aman recalls about discovering Julius.
What happened next transformed SpellBook's entire approach to data analysis. Julius provided something the company had been missing: accessible data science capabilities that didn't require specialized training or additional headcount.
"Julius is just my data scientist in my pocket," explains Aman. "At SpellBook, we are a very lean team. Generally, if you can't hire someone, having a tool like Julius on hand is basically having a data scientist on our team."
The onboarding process validated Julius's promise immediately. "I signed up, gave it a test piece of data, and the visualizations and data that we had was super reliable and super accurate," says Aman. "As simple as just typing in what I wanted, it was amazing."
From finance insights to company-wide data empowerment
What started as a solution for finance quickly expanded across SpellBook's organization. Aman, who oversees not just finance but also business operations and revenue operations, began extending Julius access to other teams facing similar data challenges.
The RevOps team, dealing with hundreds of thousands of lines of CRM data, found immediate value. "Our RevOps lead is using it to understand deal data. We have probably two or 300,000 lines of data, and he also is not a data scientist. But now we do have a data scientist through Julius," Aman explains.
Even more significantly, SpellBook's C-suite began using Julius directly to extract their own insights. "We want to encourage individuals to use data and be empowered by data," says Aman. "But oftentimes they don't have comfortability with using large data sets or have the background in data science. And so now we can get our C-suite team to extract insights much quicker."
Measuring what matters: NRR and sales efficiency breakthroughs
Julius enabled SpellBook to tackle sophisticated analyses that were previously challenging with their manual approach. Two critical use cases demonstrated the platform's transformative impact:
Net Revenue Retention (NRR) analysis: SpellBook needed to understand how their customer success management affected revenue retention. Using Julius, they discovered that CSM-managed accounts had NRR 50% better than non-CSM accounts. The analysis revealed that specific cohorts would likely achieve 300-400% NRR, leading to increased investment in customer success systems.
Sales efficiency optimization: With nearly 50 sales representatives generating high-volume data, understanding individual performance became crucial. "What we do now with Julius is we have our raw sales data by rep and we basically have it help us understand who are the best performing reps, what their trends are going to be looking like in the future," explains Aman. This analysis now takes minutes instead of hours of manual Excel work.
The strategic impact: time as the ultimate currency
For a startup like SpellBook, the transformation extends far beyond operational efficiency. "At a high growth startup, time is your most valuable resource," emphasizes Aman. "The amount of time that you're spending on manual processes when something could be automated, there's an opportunity cost."
The 8-10 hours Aman saves weekly now go toward strategic initiatives that directly impact business growth. "My role as VP of Finance is to understand where to allocate capital the most efficiently and have the highest ROI impact," he explains. "Those 8 to 10 additional hours, along with the quick turnaround and feedback that we have from Julius, allows us to understand where we should invest our capital and scale certain channels and teams."
The ripple effects reach the highest levels of decision-making. "We're able to get C-suite really bought in much quicker. And as a startup, you need to make decisions really quickly. That has made a huge impact on our team, allowing us to make decisions more quickly and more efficiently with data that's actually reliable and accurate."
Beyond Excel: unlocking advanced analytics for finance teams
Julius has fundamentally changed how SpellBook thinks about data visualization and analysis. "If you think about Excel or even Google Sheets, they're very limited in terms of the charts and visualizations you can create," notes Aman. "Some of the cool features that have come up with Julius like creating heat maps, regression analysis—they're super valuable for our stakeholders."
The native data cleaning capabilities have been particularly transformative. Rather than spending hours preparing data for analysis, the team can focus immediately on extracting insights and making decisions.
"Just imagine yourself becoming a data scientist," Aman suggests to other finance professionals. "A lot of our skill sets are focused and we've grown up with Excel, but we've moved over to a very data-native world. And a lot of us don't have those backgrounds in Python or SQL. And so now I can just become a data scientist without actually needing to go to school for all those skill sets."
