Automating Professional Services: Caddi CEO Alejandro Castellano on Using AI to Tackle Admin Work

Value Drivers

Peter Ho welcomed Alejandro Castellano to the podcast to discuss how he uses technology to make operations and businesses work smarter. Alejandro shared his background, starting with a childhood dream of being an inventor in Lima, Peru, leading him to study electrical engineering. He pursued entrepreneurial ventures early, starting an EdTech company in college where he learned the basics of running a business. This first company connected him with business people, leading to an opportunity to join a family office, which he described as his "on the streets MBA," where he learned how businesses grow from one to ten million in revenue across various industries. Despite this valuable experience, he always wanted to build something more disruptive in software, promising himself he would pursue a master's in computer science in the US. He eventually attended Cornell Tech, specializing in computer vision and machine learning, with a focus on entrepreneurship.

After completing his master's, Alejandro had the idea to combine his two experiences: the operational knowledge from the family office, particularly in non-tech professional services, with the exploding potential of generative AI to improve these operations. He applied to the Allen Institute for AI incubator, AI2, choosing it because they had invested in AI startups before AI was mainstream, trusting their approach. Moving to Seattle for the incubator, he began exploring his idea. The motivation to start a company stemmed from his preference for working on something he owned or had a stake in, a mission that led him to seek the "best place to build companies in the world".

Observing bottlenecks in admin and back office work in various businesses, Alejandro saw an opportunity to apply generative AI. He initially thought legal would be a good starting point due to AI's text analysis capabilities. Through conversations with attorneys, he identified common manual admin tasks that technical solutions could solve, but which firms lacked the resources to build. He realized this opportunity extended to other professional services like finance and accounting. This led to the core idea of Caddi: an extremely easy-to-use system that could watch a user's screen and replicate their process, like having a consultant ask to be shown a task and then automating it.

Caddi works by having users record their screen interactions while performing a process; Caddi then documents the steps and replicates the process via software, such as API calls. This approach is different from traditional UI-based RPAs, which can break if the user interface changes and might make errors in decision-making, posing a significant liability in sensitive industries like legal and finance. Caddi's hybrid model starts like an RPA but generates actual code, making it extremely reliable.

A key differentiation for Caddi is its focus on professional services users who are non-technical, often highly regulated, cautious about data, and value their time immensely. Caddi was designed to be customizable, allowing each firm to automate processes exactly the way they work today, rather than forcing them to adopt a standard pattern. They position Caddi as a "new AI employee" that users can teach manual processes to, which Caddi then performs reliably, saving time and cost and enabling employees to focus on revenue-generating activities. Caddi also facilitates process standardization across an organization and provides visibility into automated tasks. While they started exploring legal, their current clients are primarily in the financial services industry, as the pattern of needing operational support for expert practitioners is similar across professional services. Their revenue model is subscription-based with different tiers depending on platform usage, offering unlimited seats to encourage widespread adoption within a firm.

Caddi recently raised $5 million in funding, a process Alejandro described as challenging but ultimately quick, taking about three weeks to find lead investors. The AI2 incubator was immensely helpful, providing diverse advisor perspectives (VC, entrepreneur, technical) and, crucially, a network that provided warm introductions to investors, making the fundraising process significantly easier.

Key Takeaways

· Combine your unique background with technological shifts to identify opportunities. Alejandro combined his experience in operations within non-tech businesses from a family office with the "explosion" of generative AI to see a need for improving operations in professional services. This suggests that looking at how your specific skills and past experiences intersect with emerging technologies can reveal promising market gaps.

· Focus on a specific customer segment and deeply understand their unique needs and constraints. Caddi initially focused on professional services like legal and financial advisory. Alejandro emphasizes that these users are often non-technical, highly regulated, have concerns about data security, and value their time immensely. Tailoring the product's ease-of-use and reliability, as well as the go-to-market strategy, to these specific characteristics is crucial for differentiation and adoption.

· Prioritize reliability, especially in sensitive industries. In fields like legal and finance, even small errors can be very costly. Caddi addressed this by developing a hybrid approach that, while starting with recording user actions, generates validated code to ensure processes are replicated reliably, offering a significant advantage over less dependable methods. Making the solution reliable is paramount for building trust with these customers.

· Leverage incubators and their networks for guidance and fundraising. Alejandro found the AI2 incubator incredibly helpful, not only for diverse advisor perspectives covering business, technology, and entrepreneurship, but also for providing warm introductions to investors within their network. This network significantly eased the fundraising process, demonstrating the value of connecting with established communities.

· Balance visionary dreaming with grounded realism. Founders need a "reality distortion field" to dream big and believe they can change the world. However, Alejandro stresses the importance of being "quite real, quite transparent, and humble" when receiving customer feedback, analyzing usage data, and assessing the company's actual progress. The ability to switch between these two mindsets is vital for navigating the entrepreneurial journey.

Chapter Summary

(00:01:02) Host Peter Ho introduces Alejandro Castellano, CEO of Caddi, focusing on using tech for smarter business operations. Shares background: Peru, engineering, first company A plus Tutoring, and "on the streets MBA" experience in a single-family office.

(00:03:23) Pursuit of US education led to a Master's in AI at Cornell Tech and joining the AI2 incubator in Seattle. The idea for Caddi combined his operations experience with generative AI's potential to automate manual admin/back-office tasks in non-tech professional services.

(00:06:50) Identified that professionals were overqualified for manual admin tasks. Realized an opportunity in industries like legal and finance. Caddi's concept aims for ease of use by watching and replicating processes, using a recording app to capture steps and build automations via software.

(00:11:11) Caddi differentiates from RPA/no-code by focusing on professional services lacking tech talent. Unlike UI-based RPA, Caddi generates reliable custom code, crucial for accuracy in legal/finance where errors are costly.

(00:15:23) Caddi's value proposition: act as a reliable AI employee, freeing up time for higher value tasks, offering standardization and visibility. Business model is subscription for financial services and law firms with unlimited seats.

(00:17:40) They recently raised $5M, lead investor Sunil Nagaraj (Uig), also AI2 network. Differentiation lies in specializing for the professional services segment's specific needs and constraints (e.g., regulation, hesitation to adopt new tech, value of time).

(00:22:40) Scaling in this segment requires credibility and case studies. The AI2 incubator provided significant help with advisors and warm investor introductions. Keeping current on AI means constant experimentation.

(00:30:12) Advice for entrepreneurs: balance the dreamer's reality distortion field with being realistic and transparent about operations.

Resources:

Black Swan by Nassim Nicholas Taleb

https://www.amazon.com/Black-Swan-Improbable-Robustness-Fragility/dp/081297381X

Caddi

https://www.trycaddi.com/

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Peter Ho

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