Activant Capital brought together at SaaStr Annual a group of break-out next-generation AI enhanced vertical software leaders: the CEOs from Owner.com, Alloy Automation, and DoNotPay.
At SaaStr Annual they shared their experiences and insights on implementing AI in vertical software companies.
Adam Guild, CEO Owner
Adam Guild leads Owner.com, a comprehensive platform helping restaurant owners succeed in the digital space. Under his leadership, the company has developed innovative AI-powered solutions for restaurant websites, online ordering, CRM, and marketing automation. Owner.com has distinguished itself by consolidating dozens of point solutions into a single, integrated platform that helps small business owners compete effectively online.
A huge congrats to Team @owner for a record start to 2025!!
🚀 New restaurants up +31% in 1 month!
🥂 Sales up 22%!
🤖 Ai up 76%!Join a rocketship. Join @owner pic.twitter.com/zaiPTpMEbM
— Jason ✨👾SaaStr 2025 is May 13-15✨ Lemkin (@jasonlk) February 1, 2025
Sarah Du, CEO Alloy Automation
Sarah Du is the CEO of Alloy Automation, a Series A company backed by Andreessen Horowitz. Her company specializes in API integration platforms that enable SaaS companies to launch integrations faster and automate complex business processes. Under her leadership, Alloy Automation has pioneered the use of AI to streamline API integration and documentation processes.
Josh Browder, CEO DoNotPay
Josh Browder is the founder and CEO of DoNotPay.com, an innovative consumer-focused AI platform. What began as a solution for fighting parking tickets has evolved into a comprehensive platform that helps consumers assert their legal rights and negotiate with large companies. Under his leadership, DoNotPay has pioneered the use of AI for consumer advocacy, including developing sophisticated AI negotiation systems.
The Transformation of Vertical Software
The software industry is experiencing a significant transformation, particularly in vertical-specific solutions. The first generation of vertical software, built approximately 15 years ago, is now ready for disruption. This change is driven by advances in AI technology and changing customer expectations.
The panelists emphasized that vertical software is particularly well-suited for AI implementation due to its contained workflows and specific use cases. This makes it easier to develop AI solutions that can drive concrete outcomes for customers while maintaining reliability and accuracy.
Practical Applications and Results
Several compelling examples of AI implementation were shared during the discussion:
Customer Service and Support
DoNotPay has successfully automated 60% of their customer service workload through AI implementation. Their system can handle complex tasks such as negotiating with service providers on behalf of customers, though this requires careful management to ensure the AI remains truthful and effective.
Restaurant Industry Solutions
Owner.com has developed an AI website generator that implements industry best practices automatically. Their platform helps restaurant owners, who typically earn less than $50,000 annually in profit, create professional online presences without significant investment in time or resources.
Integration and Automation
Alloy Automation has leveraged AI to streamline API integration processes, enabling faster deployment of business process automation solutions. They’ve seen particular success in using Large Language Models (LLMs) to translate API documentation into practical implementations.
Impact on Business Operations
Team Structure and Management
The implementation of AI has led to interesting changes in organizational structure. For example, Owner.com operates with a notably flat structure, maintaining a ratio of one product manager to sixteen engineers. Engineers are empowered to make technical decisions and write their own product requirement documents, functioning essentially as “mini-founders” within the organization.
Technology Stack Decisions
The panelists emphasized the importance of maintaining flexibility in AI implementation. Rather than committing to single solutions, successful companies are:
- Testing multiple AI models continuously
- Using self-served platforms for rapid experimentation
- Empowering engineers to make model-selection decisions
- Avoiding long-term vendor lock-in
Data Management
Data quality and integration have emerged as critical factors in successful AI implementation. Companies need to:
- Ensure secure data handling
- Maintain clean data for model training
- Integrate effectively across multiple systems
- Enable real-time data access where needed
Evolution of Business Models
The integration of AI is driving changes in how vertical software companies approach pricing and business models:
Pricing Strategies
Traditional subscription-based pricing is being supplemented or replaced by:
- Outcome-based pricing tied to specific results
- Usage-based models measuring API calls or throughput
- Hybrid approaches combining fixed and variable components
- Value-based pricing aligned with customer savings or gains
Customer Expectations
The release of foundation models like ChatGPT has significantly influenced customer expectations. Business customers now expect:
- Immediate results and value
- Seamless automation
- Personalized experiences
- Clear ROI metrics
Implementation Challenges and Solutions
Managing AI Risk
Companies are developing various approaches to ensure responsible AI use:
- Building guardrails to prevent AI hallucination
- Implementing multiple models to cross-check results
- Maintaining careful monitoring of AI outputs
- Balancing automation with human oversight
Integration Considerations
Successful integration of AI requires attention to:
- Data quality and availability
- System compatibility
- User experience design
- Performance monitoring
- Security requirements
Future Trends
The panelists identified several key trends that will likely shape the future of vertical software:
Dashboard Evolution
Traditional dashboards are expected to become less relevant within 3-5 years, replaced by:
- AI agents that understand industry best practices
- Voice interfaces for natural interaction
- Proactive optimization and recommendations
- Personalized insights delivery
Market Adoption
Contrary to some expectations, AI adoption is happening rapidly across various sectors:
- Traditional businesses are actively seeking AI solutions
- Small and medium-sized businesses are embracing AI capabilities
- Enterprise customers are beginning to expect AI features
- Cross-industry adoption is accelerating
Conclusion
The integration of AI into vertical software represents a significant opportunity for both providers and users. Success in this space requires a balanced approach that combines technical innovation with practical business considerations. Companies that can effectively implement AI while maintaining focus on customer outcomes and operational efficiency will be well-positioned for success in this evolving landscape.
The key to success lies in maintaining flexibility, focusing on customer outcomes, and building strong, adaptable teams. As the technology continues to evolve, companies must stay agile and responsive to changing market needs while ensuring their AI implementations deliver real value to their customers.
