In a world where AI becomes a standard (one that customers simply expect), the phrase “AI-powered” in a digital product’s description doesn’t thrill anyone anymore nor determine success. What does that, however (or at least can), is how companies use artificial intelligence — and that’s what matters most. 

Businesses with a deep understanding of artificial intelligence’s capabilities and truly innovative ideas on how to utilize it are the ones who will conquer industry markets and lead transformations that are yet to come. One such is Caju AI, a company we were happy to support in building their groundbreaking generative AI platform this year.

Caju AI uses generative AI to empower customer-facing workforces by redefining the nature of customer interactions. It allows companies to reach the ocean of unstructured data hidden in those interactions, organize it, and use it as a source of actionable business insights. Thanks to that, organizations can boost their customer service and move their operational excellence to a level that wasn't achievable before.

I felt like it would be a huge waste not to use the opportunity to dive deeper into such an inspiring business’ mindset. So, I reached out to Otavio Freire, Caju AI’s co-founder and CEO, to ask him a few questions about the product and its “behind the scenes.”

A screenshot presenting a "Key Metrics" view - "Organization Overview" tab from Caju AI - a generative AI platform dedicated to customer-facing workforces
Karolina: How was the idea of Caju AI born? Who and how came up with it? I’m always curious how such undertakings start — was it at first a general idea that needed to simmer in your heads for a while to gain some clearer shape, or was it more like an “Eureka!” moment after noticing a problem or a need?

Otavio: Technological advancements in AI sparked the inception of Caju AI. Our tenure in the AI domain, specifically in analyzing human conversations, was marked by a growing sense of possibility entwined with moments of frustration due to the limitations of existing approaches. The advent of OpenAI’s GPT-3 model was a pivotal moment, illuminating a path of new possibilities — it was our ‘Eureka!’ moment.

This breakthrough in large language models coincided with a deep understanding of how customers could improve their customer-facing interactions if they genuinely understood the conversations taking place to improve products and services. Here, we recognized the potential to transcend beyond the rudimentary outputs of “traditional” data analytics, such as basic metrics and word clouds. 

We envisioned a solution that could delve into the nuances of conversation, extracting meaningful insights about these customers to propel the business forward. Thus, Caju AI was born out of a desire to harness the latest AI to create something that could genuinely ‘understand’ communications in a sophisticated and impactful way.

Karolina: Thank you for sharing this. Being able to follow your thought process helps me better understand the mission of Caju AI. And it’s really inspiring! What also intrigues me here is how you validated your product-market fit. Was it a long process?

Otavio: To validate product-market fit, we adopted a multi-phase approach. Initially, we developed an alpha version of our product, which we presented to potential customers to gather their feedback. This early interaction was crucial, as it informed the adjustments and feature developments that shaped our first official release, version 1.0.

Post-launch, we continued to validate our product by engaging with a broader customer base, which affirmed our value proposition and significantly expanded our sales pipeline. Our efforts have culminated in a series of early customers and a robust pipeline with numerous opportunities, indicating a solid product-market fit.

Karolina: Sounds like a smart approach — but no wonder, considering all of you in Caju’s Leadership Team are seasoned entrepreneurs.
And what did your journey from the first idea to creating the PoC look like? How long did it take to build the PoC and find investors to proceed with the project? Considering the generative AI boom started in November 2022, and in February 2023 you were already past the PoC phase and ready to build the product, it seems like it all happened very quickly, right?

Otavio: Our journey from concept to Proof of Concept (PoC) was rapid and rigorous. In early 2023, we distilled our vision into actionable plans and swiftly transitioned into development. Within an astonishingly short period, we had our prototype up and running — crafted by the founders themselves — a testament to our team’s diverse skills and unwavering dedication, involving many early mornings, late nights, and weekends dedicated to development.

This initial prototype wasn’t just a technical validation; it embodied our core product concepts, giving us a concrete foundation to demonstrate our technology’s potential to early investors and customers.

A set of screenshots presenting Caju AI - a generative AI platform dedicated to customer-facing workforces
Karolina: Wow. It all sounds really impressive! There’s one more thing regarding this rapid course of events that I’m curious about.
In February, when you were about to start the project, there were still very few generative-AI-powered products in the market. Yes, the interest in Gen AI was growing super fast, but there were lots of doubts and questions around it — we came across many companies that were rather researching options and observing — not rolling up their sleeves and getting to work as you did. In a sense, you were pioneers in this field. How did you feel about that? Wasn’t it scary to be the early adopter?

Otavio: Our foray into the generative AI landscape blended conviction and strategic insight. We weren’t deterred by the pioneering nature of our endeavor, primarily due to our deep-rooted expertise and thorough initial testing. This groundwork gave us a clear glimpse into the transformative potential of generative AI. We understood early on that embarking on a less traveled path carries risks and opens doors to unprecedented opportunities.

We saw this in the early days of the Internet when we were part of a firm that built application servers and ultimately had an IPO. Our team’s background, which is rich in technological prowess and market acumen, equipped us with a unique vantage point. We were convinced that the potent capabilities of Generative AI were not just theoretical but immensely practical and ripe for application. This understanding mitigated trepidation, replacing it with a calculated excitement to lead and define a new chapter in enterprise technology evolution.

Read also: The future of AI is here: Potential GPT-4 use cases and early adopter projects

Karolina: I can imagine that excitement. Being close to all Gen-AI-related topics from the beginning of the boom, I tasted some of it myself, even by only learning and writing about it.
And what about the process of searching for a tech partner for your project? One could assume that this part was pretty challenging as well, right? The technology was relatively new, so naturally, the field of software agencies with relevant experience wasn’t broad. How did you approach this problem? And what were your most important selection criteria?

Otavio: The quest for a tech partner adept in the nascent realm of generative AI was a journey marked by meticulous deliberation. We approached this challenge with a strategy prioritizing alignment in vision and technical synergy. Our primary criterion was more than technical expertise; we sought a partner with a collaborative spirit who would join us in the trenches and contribute to the creative process, not just execute tasks. We looked for teams proficient in generative AI and demonstrated a pioneering spirit and an eagerness to venture into uncharted territories alongside us.

We conducted an extensive search, engaging in in-depth discussions to ensure our potential partners were as invested in the project’s success as we were. The selection process was rigorous — 1) we evaluated portfolios for proven innovation, 2) we assessed the adaptability of teams, and 3) we sought evidence of proactive problem-solving capabilities. 

Our meetings emphasized the importance of a partnership where open dialogue and mutual inspiration were the norms. The result was a collaboration that transcended traditional client-vendor dynamics, evolving into a powerful alliance to break new ground in generative AI.

A screenshot presenting a "Key Metrics" view - "Sales Effectiveness" tab from Caju AI - a generative AI platform dedicated to customer-facing workforces
Karolina: After these words, it feels even better that it was us whom you chose as your tech partner! 
And now, after a few months of working hand in hand with Neoteric, what would you say was the most essential element of this collaboration?

Otavio: Reflecting on the months of collaborative efforts with Neoteric, the most vital element of our partnership has undoubtedly been the symbiotic blend of trust and shared vision. The team brought technical expertise and has deeply invested in understanding and contributing to our strategic objectives.

The importance of having a partner that resonates with our pioneering spirit cannot be overstated. The Neoteric team has been more than a service provider; they've been co-creators, invested in the product's success as much as we are. This relationship has fostered an environment where risk-taking is encouraged, and creative solutions are born from a shared commitment to excellence and innovation. 

The mutual respect and genuine partnership we’ve experienced with Neoteric have been instrumental in navigating the complexities of bringing a cutting-edge AI product to market.

Karolina: Thank you for that! A “true partnership” is one of our core values, and it’s really fulfilling to know our clients recognize us for that. 
But let’s get back to your product. Your website lists 5 industries you focus on — life sciences, financial services, healthcare, education, and manufacturing. Why specifically those? And does it mean Caju AI is explicitly made for them, or could it be adopted in businesses from other industries as well?

Otavio: Our decision to focus on the five industries — life sciences, financial services, healthcare, education, and manufacturing — was strategic and deliberate. These sectors represent our first customers, are integral to our expertise, and present unique communication challenges, particularly within regulated environments where understanding nuance is critical. Our experience and the technological leap afforded by advanced AI models allowed us to tailor Caju AI to address the specific needs of these industries.

However, the foundational AI technology of Caju AI is highly adaptable and can certainly be customized to fit a range of other industries. The product’s core capability lies in its sophisticated understanding of complex communication, a universal need across various sectors. So, while our initial focus is on these five industries due to their immediate and pronounced need for such technology, Caju AI holds the potential to revolutionize communication analysis and insights in many other domains.

A screenshot presenting a "Questions" tab from Caju AI - a generative AI platform dedicated to customer-facing workforces
Karolina: So, generally — without focusing on any specific industry — what business problems or needs is Caju AI meant to address? 

Otavio: Caju AI enhances enterprise operations by leveraging generative artificial intelligence to improve customer engagement via actionable intelligence. It addresses the need for better visibility and control over customer interactions, particularly those conducted via mobile messaging apps, which are critical yet challenging to monitor for quality, sales effectiveness, and risks.

By empowering human agents with advanced AI tools, Caju AI aims to facilitate deep, meaningful customer relationships and improve the scale and personalization of digital customer engagement while also addressing the complexities and high costs associated with maintaining a proficient and compliant customer-facing workforce.

Read also: Experts advise: How to identify the right use case for generative AI adoption?

Karolina: Amazing. I can’t wait to see how Caju AI will transform the world of business operations. But now, it looks like it’s time for my last question. Last but not least!
I know that you already have some active clients using Caju AI and that the interest in the tool is growing pretty fast. Is there any particular success, highlight, or maybe even observation you’d like to share?

Otavio: In my 25 years of experience in enterprise software, a few milestones have reshaped our engagement with technology — real-time internet communications, the advent of the iPhone, the rise of social media, and now generative AI.

The responses from our clients to Caju AI have been overwhelmingly positive; it's not uncommon for us to hear a resounding "WOW!" from users. This technology has been a game-changer, akin to equipping our clients with a team of a thousand analysts, liberating them from the mundane to focus on higher-level tasks. 

It’s been gratifying to see Caju AI not just meet but exceed expectations by empowering users with what they describe as a ‘super-power,’ enabling them to work smarter with a newfound agility and insight previously inconceivable.

Karolina: I’m not surprised to hear that. Digging deep into the details of Caju AI and our cooperation while I worked on the case study, I became a big fan of your product myself! Well, I guess all I can say is that I hope this path of success continues and Neoteric will remain your trusted partner in this journey.
Thank you for this inspiring talk, Otavio!

Otavio: It’s been a pleasure, thank you.