Brian Schiff: AI is revolutionizing customer support, automation can reduce call volumes by 90%, and pricing models are evolving for accessibility | SaaS Interviews

AI-driven automation in customer service is transforming industries, handling 300 million calls and reshaping business strategies.

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Add us on Google by Editorial Team Apr. 22, 2026

Key takeaways

• AI is revolutionizing customer support, becoming a key technology in modern business environments.
• Automation in customer service can significantly reduce call volumes, particularly in industries like transportation.
• Deep integration and handling edge cases are crucial for successful enterprise software development.
• Offering software without upfront costs can make advanced technologies accessible to companies of all sizes.
• The pricing model for AI services ranges significantly, reflecting the complexity and scale of customer needs.
• Automating 300 million phone calls demonstrates the significant impact and scalability of AI technologies.
• The acceptance of AI in automating conversations is becoming widespread and is seen as inevitable.
• Companies must develop a strategy for AI to remain competitive in customer experience.
• B2B applications should leverage the latest technology to deliver measurable value to customers.
• AI technologies are better suited for large consumer businesses with high contact volumes.
• The shift in perception towards AI automation indicates a strong trend that could influence future business strategies.
• Understanding pricing models and customer profiles is essential for navigating the competitive landscape in enterprise software.
• The necessity for businesses to engage with AI reflects the growing importance of technology in customer interactions.
• Strategic decision-making is crucial in determining the applicability of technologies in specific market segments.

Guest intro

Brian Schiff is the co-founder and CEO of Flip, a verticalized AI voice assistant that automates customer service calls for over 250 brands in transportation, retail, and healthcare, recently reaching $12M ARR. He pivoted the company’s original Cornell ridesharing app—banned on campus—into voice AI after recognizing its dead end, now handling 300 million calls and raising a $20M Series A at a $100M valuation.

AI’s transformative role in customer support

• AI is a transformative technology with significant applications in customer support.

  — Brian Schiff

• The current landscape of AI applications in business highlights two major use cases: AI coding and AI customer support.
• AI’s role in customer support is part of a broader trend towards automation in business environments.

• I think when people write AI is the technology of our lifetimes…

  — Brian Schiff

• The importance of AI in modern business is underscored by its potential to enhance efficiency and customer satisfaction.
• Companies are increasingly focusing on AI to streamline operations and improve customer interactions.
• The transformative potential of AI is evident in its ability to automate routine tasks and free up human resources.
• AI’s impact on customer support is part of a larger shift towards digital transformation in various industries.

Automation in the transportation industry

• We automate somewhere between eighty five and ninety percent of the calls that transportation companies receive.

  — Brian Schiff

• Automation significantly reduces call volumes, allowing companies to focus on more complex customer needs.
• The scalability of automation in transportation demonstrates its effectiveness in handling high volumes of routine inquiries.

• We’re able to automate all of those routine calls…

  — Brian Schiff

• Automation helps transportation companies stay at the cutting edge by improving efficiency and customer service.
• The success of automation in transportation highlights the potential for similar applications in other industries.
• Understanding the scale of automation is crucial for appreciating its impact on customer service.
• Automation in transportation is part of a broader trend towards leveraging technology to enhance operational efficiency.

Challenges in enterprise software development

• Building enterprise software with deep integrations and handling edge cases is extremely complex.

  — Brian Schiff

• Successful enterprise software development requires experience in managing integrations and anticipating issues.
• Deep integration is essential for providing seamless customer experiences and addressing potential challenges.

• It’s one thing to have enough of an integration with Shopify…

  — Brian Schiff

• Handling edge cases is a critical component of enterprise software development, ensuring reliability and performance.
• The complexity of enterprise software development underscores the importance of expertise and experience.
• Integrating various software systems poses significant challenges, requiring careful planning and execution.
• Anticipating and navigating issues is crucial for delivering effective enterprise software solutions.

Accessibility and pricing models in AI solutions

• Their software can be implemented without upfront costs, making it accessible for companies of all sizes.

  — Brian Schiff

• Offering no-cost setup and integration makes advanced AI solutions more accessible to a wider range of companies.
• The accessibility of AI solutions can disrupt traditional pricing models in enterprise software.

• One of the beauties is this works for companies of all size…

  — Brian Schiff

• The competitive landscape in enterprise software is influenced by pricing models and accessibility.
• Making AI solutions accessible to smaller companies can drive innovation and adoption across industries.
• Understanding pricing models is essential for navigating the competitive landscape in enterprise software.
• The accessibility of AI solutions reflects a broader trend towards democratizing technology.

Revenue models and customer profiles

• The average customer pays between $50,000 to $500,000 per year for our services.

  — Brian Schiff

• The pricing model for AI services reflects the complexity and scale of customer needs.
• Understanding customer profiles is crucial for tailoring AI solutions to specific business requirements.

• It’s usually somewhere between 50 500,000…

  — Brian Schiff

• The revenue model highlights the target customer base for AI services, focusing on established companies.
• The pricing model underscores the value and impact of AI solutions in addressing complex business challenges.
• The diversity in customer profiles reflects the adaptability and scalability of AI solutions.
• Understanding the revenue model is essential for appreciating the business potential of AI technologies.

Scale and impact of automation

• We have automated 300,000,000 phone calls to date.

  — Brian Schiff

• Automating 300 million phone calls demonstrates the significant impact and scalability of AI technologies.
• The scale of automation achieved by the company highlights its technological capabilities and industry significance.

• We just announced our $20,000,000 series a…

  — Brian Schiff

• The company’s operational scale reflects its ability to handle large volumes of customer interactions.
• The impact of automation is evident in its ability to streamline operations and enhance customer service.
• The scale of automation underscores the transformative potential of AI technologies in various industries.
• Understanding the scale of automation is crucial for appreciating its impact on customer service and business operations.

Imminent acceptance of AI in customer service

• The widespread acceptance of AI for automating conversations is imminent and inevitable.

  — Brian Schiff

• The acceptance of AI in customer service reflects a significant shift in industry perception towards automation.
• The inevitability of AI adoption highlights its growing importance in business strategies and operations.

• I think that the world has realized…

  — Brian Schiff

• The shift in perception towards AI automation indicates a strong trend that could influence future business strategies.
• The acceptance of AI is driven by its potential to enhance efficiency and customer satisfaction.
• Understanding the current landscape of AI adoption is crucial for anticipating future trends and opportunities.
• The acceptance of AI in customer service is part of a broader trend towards digital transformation in various industries.

The necessity of AI strategies for businesses

• Every company and customer experience leader needs to have a strategy for AI.

  — Brian Schiff

• Developing a strategy for AI is essential for companies to remain competitive in customer experience.
• The necessity for AI strategies reflects the growing importance of technology in customer interactions.

• Every company every cx leader out there needs to have an answer…

  — Brian Schiff

• Companies must engage with AI to stay relevant and effective in a rapidly evolving business landscape.
• The urgency for AI strategies underscores the transformative potential of technology in customer service.
• Understanding the competitive landscape in customer experience is crucial for developing effective AI strategies.
• The necessity for AI strategies highlights the importance of innovation and adaptation in business operations.

Leveraging technology in B2B applications

• B2B applications must leverage the latest technology to deliver value to customers.

  — Brian Schiff

• Leveraging advanced technologies is essential for B2B companies to remain relevant and effective.
• The competitive landscape in B2B technology is influenced by innovation and technological advancement.

• Ultimately I think the purpose of a B2B app is to deliver measurable value…

  — Brian Schiff

• Adopting the latest technology is crucial for delivering measurable value and enhancing customer satisfaction.
• The necessity for innovation in B2B applications underscores the importance of staying ahead of industry trends.
• Understanding the importance of technology in B2B applications is crucial for driving growth and success.
• Leveraging technology in B2B applications reflects a broader trend towards digital transformation and innovation.

Applicability of technology in different market segments

• The technology is particularly suited for large consumer businesses due to high contact volumes, but less so for B2B environments.

  — Brian Schiff

• Certain technologies are more applicable in specific market segments, highlighting strategic decision-making.
• The applicability of technology in different market segments is influenced by customer interaction volume.

• I think the first sort of realization is that this technology is great for large consumer businesses…

  — Brian Schiff

• Understanding the differences between B2B and B2C environments is crucial for strategic decision-making.
• The strategic decision-making process involves determining the applicability of technologies in specific market segments.
• The applicability of technology reflects the importance of tailoring solutions to specific business needs and environments.
• Understanding the applicability of technology is essential for making informed business decisions and driving success.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.