Helen Hastings: How to Build an AI-Enabled Service That Replaces QuickBooks

What if the biggest accounting software monopoly could be rebuilt from scratch using AI? Helen Hastings proved it's possible by raising $20M from Accel to replace QuickBooks with an AI-enabled service that delivers accounting results in days, not weeks.

Key Facts

• User Interviews Conducted: 200+ before building any product (Helen Hastings)
• Seed Round Size: $4.7M raised pre-product as solo founder (Helen Hastings)
• Growth Rate: 20-60% month-over-month after launch (Helen Hastings)
• Series A Amount: $15M from Accel (Episode Description)
• Team Size at Launch: 6 people (3 engineers, 1 designer, 1 accounting expert) (Helen Hastings)

The Magic Wand Framework: How 200 User Interviews Shaped Quanta

Helen Hastings spent over a year conducting 200+ user interviews using open-ended questions before building any product, discovering that accounting delays and data loss were universal pain points for software companies.

Before writing a single line of code, Helen Hastings immersed herself in a rigorous user research process that would shape everything about Quanta. Starting in summer 2022, she dedicated months to full-time conversations with controllers, CFOs, and accounting managers at software companies.

Her approach was methodical: start broad, then narrow down. 'If you could wave a magic wand and change anything about your role, what would it be?' she would ask prospects. The key was avoiding bias by letting pain points emerge naturally before introducing any specific solutions.

The research revealed two critical problems: timing and data loss. Companies were getting accounting data 3-8 weeks late, making it useless for decision-making. Even worse, the manual processes lost crucial context - revenue reports showed '$1 million' with no breakdown of customer churn, upgrades, or product performance.

"People love to be helpful and once you have planted an idea in their mind, they just want to talk about that thing, even if it is not really a pain for them." — Helen Hastings

"I think it is more that you become so immersed in a space that you do not realize how much context you are gaining every day, and then suddenly you look back, and say, why does the world operate like this?" — Helen Hastings

• Started with open-ended questions to avoid biasing responses
• Focused on software companies where she had network credibility
• Transitioned from broad pain points to specific solution validation
• Leveraged referrals to expand the interview network organically

Raising $4.7M Pre-Product: The Solo Founder's Fundraising Playbook

Helen raised $4.7M from Accel as a solo founder with no product or revenue by leveraging relationships built during her previous role at Affirm and demonstrating deep domain expertise through extensive user research.

Most founders assume they need a co-founder and traction to raise significant seed rounds. Helen Hastings proved otherwise by securing $4.7 million from Accel while working completely solo, with no product built and zero revenue generated.

The key was relationship-building that predated her startup journey. While at Affirm, Helen had connected with an Accel partner through her manager when researching developer tools. This relationship continued as she conducted user research and explored co-founder opportunities.

Rather than running a traditional fundraising process, Helen's approach was organic. The Accel partner followed her research journey and saw conviction building before she even recognized it herself. This long-term relationship, combined with her demonstrated expertise in financial systems from building Affirm's internal accounting infrastructure, created investor confidence despite the lack of traditional startup metrics.

"I feel very grateful that I had a wonderful network of incredible venture capitalists, partners that I knew from previous parts of my career who followed along with the journey and honestly saw that I had conviction before even I knew that I did." — Helen Hastings

"I think I had this misconception of founders having everything figured out before they even raise their first dollar. But actually you are figuring out a lot of it as you go." — Helen Hastings

Why AI-Enabled Services Beat Pure SaaS: The Quanta Business Model

Helen chose an AI-enabled service model because early-stage companies want accounting work done for them, not software to do it themselves, allowing Quanta to be the complete financial source of truth from day one.

The conventional wisdom in Silicon Valley is that software has the best unit economics - high gross margins, infinite scalability, and minimal operational overhead. Helen Hastings deliberately rejected this approach for a compelling reason: customer preference.

Early-stage companies don't want accounting software; they want accounting work completed. This insight drove Quanta's service-first approach, where AI automation handles routine tasks while human experts manage edge cases and client relationships through dedicated Slack channels.

The service model also solved a critical strategic challenge. To build the 'financial source of truth' Helen envisioned, Quanta needed to own the complete data flow from day one, not compete as a point solution hoping to expand later. By handling all accounting work, they could ensure data accuracy and completeness that pure software couldn't match.

"Early stage companies, they do not want accounting software. They just want the work to be done. They want the peace of mind. They want it off their plate and that is what a service is." — Helen Hastings

"I do not believe that you can start as a point solution and eventually take it all over. You need to be the full source of truth from day one." — Helen Hastings

• Customers prefer work completion over software tools for accounting
• Service model enables complete data ownership from the start
• AI automation reduces manual work while maintaining human oversight
• Slack channels provide the relationship element customers expect

Rebuilding QuickBooks from Scratch: The Technical Foundation

Helen's team rebuilt QuickBooks' core functionality in under one year by leveraging her financial systems expertise from Affirm, though she emphasizes this wasn't a simple 'vibe code' project requiring careful architecture and scaling considerations.

Rebuilding a decades-old accounting platform might sound impossible, but Helen's background building financial systems at Affirm provided the crucial foundation. Her experience with ledgers - the core data structure of both payment systems and accounting - prepared her for the technical challenges ahead.

The rebuild wasn't just about replicating QuickBooks features. Quanta needed to handle real-time data processing, automate manual bookkeeping tasks, and integrate with modern SaaS tools that didn't exist when QuickBooks was designed. The team spent all of 2024 building this foundation before their public launch.

Critical to their approach was the 'engineers as bookkeepers' philosophy. During development, the entire engineering team manually processed transactions, learned accounting workflows, and identified automation opportunities. This deep domain understanding enabled them to build more intelligent automation than traditional software companies could achieve.

"QuickBooks is not something you can vibe code. The numbers need to be accurate. The foundation needs to be robust. The properties need to be built to scale." — Helen Hastings

"I really think that is the best way to build an automated product. Because the engineers have to understand the domain very, very deeply." — Helen Hastings

The Growth Paradox: When Success Becomes a Problem

After launching publicly, Quanta experienced 20-60% month-over-month growth but had to pause customer onboarding because saying 'yes' to too many customers overwhelmed their semi-manual processes and slowed product development.

Most startups dream of overwhelming customer demand, but for AI-enabled services, rapid growth can become a constraint rather than purely positive signal. Helen learned this lesson firsthand when Quanta's public launch in early 2025 generated more interest than they could handle.

The company was growing consistently at 20-60% month-over-month, but Helen made a critical error: saying 'yes' to customers they weren't technically ready to serve. Since Quanta operates with some manual processes while building automation, each new customer required engineering attention for edge cases.

This created a vicious cycle. More customers meant more manual work, which pulled engineers away from building automation, which meant even more manual work for the next batch of customers. Helen had to make the difficult decision to pause new customer acquisition, even turning away prospects ready to pay.

"When we first launched throughout 2025, we started growing consistently at twenty percent to sixty percent month over month. Which was really exciting and then we actually hit a point where we had way too many onboardings that we had to take a pause." — Helen Hastings

"It is tough when a customer is knocking on your door saying, I want to use you. Please let me give you money, take my money and you have to say no. It is really hard to do, but it is the best thing in the long run." — Helen Hastings

• Growth rates of 20-60% month-over-month after public launch
• Manual edge case handling created scaling bottlenecks
• Engineering team got pulled into customer operations
• Strategic pause on customer acquisition to build automation

Finding Product-Market Fit: The Boulder Rolling Downhill

Helen recognized product-market fit when customers continued using Quanta and converted to annual contracts even when the company's processes couldn't keep up with demand, demonstrating strong underlying value despite operational challenges.

Product-market fit for service businesses looks different than for traditional software. Helen uses the metaphor of rolling a boulder uphill - difficult at first, but once you find PMF, the boulder rolls downhill faster than you can chase it.

The defining moment came when Quanta had more onboardings than they could handle properly. Helen expected customers to churn due to suboptimal experiences during the scaling crunch. Instead, companies that started with monthly contracts converted to annual agreements, even while processes were still being refined.

This retention during imperfect execution proved the underlying value proposition. Companies were getting accounting data in days instead of weeks, with better quality and visibility than traditional providers. The core promise was so compelling that customers tolerated growing pains that would typically cause churn.

"Finding product market fit is like rolling a boulder up a hill. It is really hard but once you found product market fit, it is like the boulder is rolling down the hill and you are chasing to keep up with it." — Helen Hastings

"I thought, oh my gosh, they're all going to churn. We're not delivering on our promise here. They're going to hate us. But actually, they wanted to keep working with us." — Helen Hastings

Go-to-Market Strategy: Building Trust in Financial Services

Quanta's go-to-market success relied heavily on organic referrals within founder communities, investor networks, and partnerships with financial tools, as trust is crucial when handling sensitive accounting work.

Selling accounting services requires a different go-to-market approach than typical SaaS products. Trust becomes the primary barrier, not features or pricing. Helen built Quanta's growth engine around social proof and warm introductions rather than traditional outbound sales.

The most effective channel was organic referrals within founder communities - Harvard Business School WhatsApp groups, investor networks, and ecosystem partnerships with companies like Brex and Mercury. When founders asked their peers for accounting recommendations, existing Quanta customers became the best sales team.

Cold outbound had limited effectiveness because prospects needed validation that Quanta could actually deliver on promises of speed and accuracy. Too many accounting providers make similar claims without delivering results. The solution was case studies, referral programs, and leveraging the credibility of their investor network to build initial trust.

"Trust is very important in the accounting and finance space. We're still building our brand... proving, hey, you have someone one order removed that has seen how good we are and can back channel that they're actually higher quality, they're actually faster." — Helen Hastings

"Cold email only does so much, but proving, hey, you have someone one order removed that has seen how good we are... has been really great for us so far." — Helen Hastings

• Organic referrals within founder communities drove most growth
• Trust and social proof more important than features or pricing
• Partnerships with financial tools provided distribution channels
• Case studies and investor networks helped establish credibility

Traditional Accounting vs. Quanta's AI-Enabled Service