In February 2026, WIZ.AI marked its seventh year of operations. Established in Singapore in early 2019, the company has grown from a startup to a conversational AI provider serving over 300 enterprise clients in more than 17 countries, with support for over 17 languages and dialects [7]. 

The company’s development occurred against a backdrop of widespread AI implementation failures: MIT research in 2025 found that 95% of enterprise AI pilots fail to deliver measurable return on investment, with vendor partnerships proving twice as successful as internal builds [17]. WIZ.AI’s partnership-driven approach, which emphasizes co-creation and continuous optimization, positioned the company to address this industry-wide challenge. 

This case study examines the development of WIZ.AI, analyzing its initial strategy, technological development, global expansion, and role in enterprise AI adoption, with particular attention to how its partnership model has enabled it to deliver measurable ROI where most AI initiatives fail. It reviews the decisions, challenges, and strategies that have shaped the company’s position in the conversational AI market, providing insights for entrepreneurs, investors, and business leaders in the AI sector.

The Genesis: Starting with a Global Vision (2019)

WIZ.AI was co-founded by Jennifer Zhang (President) and Jianfeng Lu (Chairman) with the objective of applying AI to customer engagement. Zhang’s background in venture capital, including roles as a Managing Partner at GCC Capital and General Partner at Cybernaut Zfounder Ventures, provided experience in cross-border business and global markets [1]. 

This perspective influenced the company’s early strategy, which co-founder Jianfeng Lu summarized as: “If you want to become a global startup, you must begin as a global startup” [5].

This mindset led to the strategic decision to launch WIZ.AI in Singapore, a move that allowed the company to tap into a diverse talent pool and a supportive ecosystem for innovation, while avoiding the hyper-competitive markets of the US and China in its early stages [5]. The initial focus was on solving a fundamental business problem: the inefficiencies in B2C communication. 

As Jennifer Zhang explained, “What we try to solve is really the B2C communication problem for enterprises and SMBs so when we approach their customers, they will always need customer engagement and we try to actually automate that” [1]. The core product, the “Talkbot,” was a conversational voice AI designed to automate customer engagement across multiple touchpoints—voice calls, messages, email, and WhatsApp—while also providing conversation analysis and customer behavior insights [1, 3].

Early Challenges and Technical Innovation (2019-2021)

The company’s early development was shaped by technical challenges that informed its technology strategy. The team identified that existing voice AI technologies had an error rate of nearly 40% in their customers’ specific use cases, which prompted the development of a proprietary Voice AI [5]. This investment in in-house technology was a key decision that led to improved performance and market differentiation.

Another operational bottleneck was the data annotation process, which initially took up to four months. To address this, WIZ.AI developed a crowdsourcing platform to recruit and manage annotators from various countries. This initiative reduced annotation times to less than three weeks, enabling faster language localization and market expansion [5]. The company’s technology stack, comprising Automated Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS), was engineered to deliver a more natural conversational experience. 

Jennifer Zhang described the components: “Number one is what we call automated speech recognition, which is like a person’s ear…the second one we consider as NLP, which is like the human brain…last part is what we call the people’s mouth, which is the text to speech models” [1]. According to the company, over 90% of users were unaware they were speaking to an AI [3]. Southeast Asia served as an initial market for WIZ.AI to refine its technology and operational processes before expanding globally [5].

The Partnership Imperative: Solving the AI ROI Crisis (2019-Present)

From its inception, WIZ.AI recognized a fundamental challenge in the enterprise AI market: the gap between technological capability and business value realization. This insight would prove prescient. In 2025, MIT’s NANDA initiative published research revealing that 95% of enterprise generative AI pilots fail to deliver measurable return on investment [17]. The study, based on 150 interviews with leaders, a survey of 350 employees, and analysis of 300 public AI deployments, identified a critical finding: purchasing AI tools from specialized vendors and building partnerships succeeded about 67% of the time, while internal builds succeeded only one-third as often [17].

The core issue, according to MIT researchers, was not the quality of AI models but rather a “learning gap” for both tools and organizations. Generic self-serve AI tools like ChatGPT, while effective for individual use, stalled in enterprise settings because they did not learn from or adapt to specific workflows [17]. Lead author Aditya Challapally noted that successful implementations shared common traits: “They pick one pain point, execute well, and partner smartly with companies who use their tools” [17].

WIZ.AI’s approach directly addressed this challenge through a partnership-driven implementation model. Rather than just offering a self-serve product, the company positioned itself as a co-creation partner, working closely with clients to understand their specific pain points, customize solutions, and continuously optimize performance based on real-world results. 

This same approach extended to customer relationships, where WIZ.AI invested in understanding local nuances, industry-specific challenges, and organizational workflows before deploying solutions.

The partnership model had several key components. First, WIZ.AI established local teams—R&D, product, and delivery—in each market before sales teams, ensuring deep contextual understanding [1]. 

Second, the company developed managed services offerings through partners like ePLDT, allowing enterprises to focus on core business while WIZ.AI handled the complexity of AI implementation [10]. 

Third, WIZ.AI committed to continuous learning and iteration, with partners like ePLDT’s Amil Azurin noting in a press release on their partnership: “It’s crucial—the willingness of both parties to really learn from everyday experience. We’re really learning from the past conversations, learning more about the Filipino culture, nuances, humor” [10]. This approach contrasted sharply with the self-serve model that MIT found to be failing across the industry, and it positioned WIZ.AI to deliver the measurable ROI that most AI initiatives were unable to achieve.

Building Competitive Advantages Through Localization and Innovation (2020-2022)

As WIZ.AI scaled, Jennifer Zhang identified three main differentiators for the company. The first was a focus on localization. “Number one, it’s that we are really localized. So a lot of players in our industry, actually they’re just sending sales teams [in specific markets]. But then their product team is just centralized in one place and their tech team is also centralized in place,” Zhang explained [1]. 

In contrast, WIZ.AI built R&D, product, and delivery teams in each market before establishing sales teams, ensuring that solutions truly addressed local challenges. “In some countries, the pronunciation of the name, for example, in Thailand, it’s very very difficult. Then we need to spend a long time conquering that kind of challenge,” she noted [1].

The second differentiator was its work in voice interface design. “The technology for most of the time, you see AI, it’s actually a very cool code or application, especially for us, because we do a lot of things like human touchpoint engagement. So actually there’s a lot of ‘arts’ that are engaged,” Zhang explained. 

“For example, how you design the opening for the conversation, how you actually design a boundary for when your boss needs to collaborate with their human beings, how that boundary can be designed nicely” [1]. This focus on the user experience, rather than just the underlying technology, became a hallmark of WIZ.AI’s approach.

The third advantage was the company’s ability to build AI models from smaller data sets. “In the beginning when we actually started in the Singapore market, nobody really spent a lot of time on the Singlish model and we actually invested a lot in that,” Zhang recalled. 

“Once we were able to get the mixed language with Chinese, English, and local accent Hokkien mixed together, if we could actually build the Singlish model with very small data—remember Singapore just has five million people—and we could use the small data and actually build complicated models, that means in other markets we are much more flexible” [1]. This capability proved essential for rapid expansion into diverse markets with limited training data.

The fourth differentiator was WIZ.AI’s partnership-driven implementation model, which contrasted with the self-serve product approach common in the AI industry. 

Rather than just offering a standardized product that customers had to adapt to their workflows, WIZ.AI invested in understanding each client’s specific context, pain points, and operational nuances before deployment. The company established local teams for R&D, product development, and delivery in each market, ensuring solutions were built with deep contextual understanding [1]. 

This partnership model, while more resource-intensive than self-serve alternatives, would later prove aligned with industry research showing that vendor partnerships succeeded at twice the rate of internal builds or generic AI tools [17].

Scaling Across Markets and Languages (2022-2023)

By 2022, WIZ.AI supported ten languages, including Singlish, Mandarin, Tagalog, Thai, and Bahasa Indonesia. Its expansion was often customer-driven, with the company entering new markets based on client needs [1]. 

As Zhang described it, “Actually most of the time, the customer drives us when they grow or when they find good use cases, find them in Southeast Asia, then they push forward, and when they go to Latin America, they will become one of our partners” [1]. This approach was supported by a diverse team representing ten different countries, further enhancing the company’s ability to localize its solutions effectively.

While WIZ.AI started in the financial services sector, it quickly expanded into other industries, including telecommunications, e-commerce, and healthcare, securing major clients like DBS, Singtel, SeaMoney, and Carro [1, 3]. 

In 2023, the company launched TalkGPT, a generative AI-enabled customer engagement solution powered by a 13-billion parameter Large Language Model (LLM) [5]. This development, along with its work on domain-specific LLMs and the accumulation of 11 patents in conversational AI, contributed to its technological standing [5, 7].

The Digital Native Advantage (2022-2023)

The post-COVID era saw an acceleration of digital transformation, creating opportunities for WIZ.AI’s growth. “I think there are two parts. One’s really about digital transformation for the enterprise customer. Especially after COVID, everybody has the mindset that we need to do this automation or digital transformation, and this really gave us an opportunity,” Zhang explained [1]. 

The company effectively targeted two key customer segments: fast-growing “digital natives” in Southeast Asia and Latin America who were eager to adopt modern, scalable solutions, and traditional enterprises looking to reinvent their customer journeys.

“We’re working with a lot of what we call digital natives. Especially in Southeast Asia, Latin America, and some other areas, they’re growing quite fast. And once they grow, their first choice actually is not to follow the previous infrastructure, like how people [work] with call centers, and how people actually structure things. They actually want to use something easy to adapt,” Zhang noted [1]. 

WIZ.AI’s solutions were reported to deliver up to a 90% reduction in operating costs and a 30x increase in ROI [5]. A partnership-based approach, where WIZ.AI grew alongside its customers into new markets, further fueled its expansion.

Going Global: The South America Story (2023-2025)

In 2023, WIZ.AI expanded into the US, the Middle East, and South America, establishing a presence in Mexico, Argentina, and Brazil [5]. The Brazilian AI market was projected to reach USD 11.6 billion by 2030, with 79% of enterprises viewing AI as a strategic component, providing a favorable market context for this expansion [5]. WIZ.AI’s success in the region was driven by its ability to address local market challenges, including data governance and compliance with regulations like Brazil’s LGPD, scalability issues for SMEs, and the leadership and strategy gap in AI adoption [5].

The company’s experience in Southeast Asia provided a useful framework for this expansion. As Zhang shared in 2023, “The good learning for us is actually because we tapped first into the Southeast Asia market, when we actually used the same customer for piloting similar solutions it landed pretty well in Latin America…What we realized is that even in the Middle East, the contracts are bigger, but there are less challenges when we’re deploying in multiple countries there” [4]. This insight reinforced WIZ.AI’s belief that solutions built for emerging markets could translate effectively across similar contexts globally.

Strategic Partnerships and Client Success Stories (2023-2026)

As WIZ.AI expanded globally, the company built a portfolio of strategic partnerships and client success stories that demonstrated the tangible value of its conversational AI platform across diverse industries and use cases. These partnerships validated a key finding from MIT’s 2025 research: that vendor partnerships and specialized AI tools succeed at nearly twice the rate of generic self-serve products or internal builds [17]. 

Unlike the 95% of AI pilots that fail to deliver ROI, WIZ.AI’s partnership-driven model—characterized by co-creation, deep customization, and continuous learning—enabled the company to deliver measurable business outcomes at scale. Each partnership reflected WIZ.AI’s commitment to understanding specific pain points, adapting solutions to local contexts, and optimizing performance based on real-world feedback rather than deploying one-size-fits-all technology.

Fuse Financing and GCash: Transforming Digital Lending in the Philippines

One of WIZ.AI’s key partnerships has been with Fuse Financing Inc., the lending arm of GCash, a major finance app in the Philippines operated by Mynt, a $5 billion company. Beginning in 2023, this collaboration has evolved over three years from deploying VoiceBot for high-volume routine collection calls to expanding into Quality Assurance automation in February 2026 [9]. The partnership addresses one of the lending industry’s biggest challenges: labor-intensive processes that limit scalability and consistency.

In the official press release, Tony Isidro, President and CEO of Fuse Financing Inc., explained the partnership’s evolution: “Our partnership with Wiz.AI has already transformed how we manage high-volume collection calls, and with this renewed collaboration, we’re excited to explore new frontiers in automation. By integrating voice AI into our QA processes, we’re not only improving operational efficiency but also ensuring a more consistent and personalized customer experience. This innovation will also support our audit process to ensure our agents remain responsible, while helping us gain insights into how we can further enhance the way we serve our customers and continuously improve our service. We highly value our customers’ dignity and maintain zero tolerance for harassment or abusive practices” [9].

The strategic significance of this partnership extends beyond operational efficiency. Pebbles Sy, Chief Technology and Operations Officer of Mynt, also emphasized the broader impact: “Fuse’s success in leveraging voice AI is a perfect example of how the GCash ecosystem uses smart technology to solve core friction points for financial inclusion. This partnership ensures our lending platform is scalable, trustworthy, and efficient, allowing us to safely serve millions more Filipinos” [9]. For WIZ.AI, the partnership demonstrated its ability to deliver enterprise-grade solutions that combine digital precision with human expertise while setting new standards for responsible AI deployment in financial services.

ePLDT: Scaling AI Across Multiple Industries in the Philippines

Another partnership was with ePLDT, the ICT subsidiary of PLDT, a large telecommunications company in the Philippines. This partnership utilized WIZ.AI’s managed services model, with ePLDT acting as a digital transformation advisor to enterprises. The reported results included the deployment of over 35 voice agents, handling 3.7 million customer interactions, an 85% reduction in average handle time, a 78% improvement in cost efficiency, and a 92% increase in customer satisfaction [10].

In the official press release, Amil Azurin, Chief Commercial Officer of ePLDT, highlighted the importance of cultural localization and continuous learning: “It’s crucial—the willingness of both parties to really learn from everyday experience. We’re really learning from the past conversations, learning more about the Filipino culture, nuances, humor. That’s what’s really important, really learning everyday” [10]. The partnership enabled ePLDT to serve clients across banking, insurance, retail, government, contact centers, and telecommunications, with ambitious targets to reach 70+ voice agents, 8+ sectors, 15+ use cases, and 10 million annual customer interactions by 2028 [10].

Security Bank: Bringing AI to Traditional Banking

In November 2025, WIZ.AI formalized a strategic partnership with Security Bank, one of the Philippines’ leading universal banks established in 1951. The partnership focused on digital transformation initiatives, particularly in collections operations, demonstrating WIZ.AI’s ability to work with traditional financial institutions [11]. 

In the official press release, Balaji Vijayan, SVP and Retail and Business Banking Risk Management Head at Security Bank, articulated the bank’s vision: “At Security Bank, our mission has always been to provide BetterBanking. Our promise is rooted in understanding our customers’ needs. We deliver solutions that make a real difference. With WIZ.AI, we aim to improve our collections efficiency. We achieve this through seamless human-bot synergy. This maintains personalized service while leveraging intelligent automation” [11].

Telecommunications Partnerships: Smartfren and Beyond

In October 2024, WIZ.AI announced a strategic partnership with Smartfren for Business, Indonesia’s leading ICT company [12]. 

In the official press release, Clara Lim, WIZ.AI’s Managing Director, described the alignment: “Our partnership with Smartfren highlights the great potential of combining expertise. We are aligned with our vision for the future. Therefore, I am excited to see how our combined efforts will push boundaries and drive innovation” [12]. 

Tony Wijaya, Chief of Enterprise Business at Smartfren for Business, also emphasized the operational benefits: “With WIZ.AI’s technology and our infrastructure, we deliver innovative AI solutions. Our partnership enables relevant solutions across industries. Furthermore, we optimize operational efficiency for long-term corporate success” [12].

Client Success Stories Across Industries

Beyond these partnerships, WIZ.AI reported several client success stories with measurable business impact. IHH Healthcare, one of Asia’s largest hospital networks, achieved a 65% reduction in operational stress during peak hours by deploying intelligent Talkbot solutions across Mount Elizabeth and Gleneagles Hospitals in Singapore [13]. 

Toyota Financial Services Philippines boosted customer engagement by 300% using AI agents for debt recovery and insurance renewals in the highly competitive automotive finance market [14]. SeaMoney, a leading digital finance platform in Southeast Asia, achieved up to 50% conversion rate increases through GenAI agents deployed across SMS and WhatsApp channels [15]. GoTo Financial, a leading digital ecosystem in Indonesia, demonstrated the transformative power of AI agents in financial services operations [16].

These success stories validated WIZ.AI’s value proposition across diverse use cases and industries, from healthcare and banking to telecommunications and e-commerce. They also demonstrated the company’s ability to deliver on its promise of up to 90% cost reduction and 30x ROI increases, while maintaining the high-touch, culturally sensitive approach that had become a hallmark of its service delivery model.

Technology and Infrastructure Partnerships: Building the Ecosystem (2025)

Beyond customer partnerships, WIZ.AI pursued strategic collaborations with technology infrastructure providers to strengthen its platform capabilities and expand its reach. These partnerships reflected the company’s recognition that delivering enterprise-grade conversational AI required not only application-layer expertise but also robust infrastructure and ecosystem integration.

In June 2025, WIZ.AI announced a partnership with Agora (NASDAQ: API), a global provider of real-time engagement technology serving over 1,700 organizations worldwide [18]. The collaboration combined Agora’s real-time communication infrastructure with WIZ.AI’s culturally-aware conversational AI to deliver enterprise-ready AI agent solutions. 

In the official press release, Tony Zhao, CEO of Agora, articulated the partnership’s vision: “Together, WIZ.AI and Agora aim to push the boundaries of real-time, emotionally intelligent, and high-availability AI communications globally” [18].

The Agora partnership addressed a fundamental challenge in conversational AI: how to achieve global scale while maintaining cultural sensitivity. Agora provided the technical foundation—ultra-low latency voice processing, intelligent interruption handling, noise suppression, and adaptive quality optimization—while WIZ.AI contributed six years of experience building culturally-adapted AI for Southeast Asia’s complex linguistic landscape [19]. 

The partnership enabled AI agents that could handle complex inquiries across voice, video, and text channels while maintaining cultural context and business process integration. As one analysis noted, the collaboration represented “a recognition that the infrastructure and application approaches aren’t competing philosophies—they’re complementary necessities” [19].

In December 2025, WIZ.AI announced a partnership with Intel Corporation to improve voice AI capabilities across Asia [20]. The collaboration focused on optimizing voice agents for businesses in banking, retail, and telecommunications, combining WIZ.AI’s conversational AI expertise with Intel’s computing infrastructure. While details of the partnership were limited, it signaled WIZ.AI’s commitment to leveraging best-in-class hardware and infrastructure to enhance performance and scalability.

WIZ.AI also deepened its regional R&D capabilities through strategic initiatives in key markets. In March 2025, at the Vietnam-Singapore Business Forum, WIZ.AI signed an MOU with HEKATE to establish an AI R&D Centre (Southeast Asia) in Da Nang, Vietnam [21]. CEO Jianfeng Lu participated in discussions with business leaders from high-tech, finance, banking, and AI sectors, including representatives from Temasek, J.P. Morgan, Sygnum Bank, UOB, Warburg Pincus, NVIDIA, Google, and The State Bank of Vietnam. 

The initiative reinforced WIZ.AI’s commitment to building local R&D capabilities before expanding sales operations—a core principle of its localization strategy. The Vietnam R&D Centre focused on AI-driven innovation across languages, visions, and machine learning, positioning Vietnam as a hub for AI talent development in Southeast Asia [21].

These technology partnerships and infrastructure investments demonstrated WIZ.AI’s ecosystem approach to market leadership. Rather than attempting to build all capabilities in-house, the company strategically partnered with specialized providers in complementary areas—real-time communication infrastructure (Agora), computing hardware (Intel), and regional R&D capacity (Vietnam). This approach enabled WIZ.AI to focus on its core strengths in conversational AI and cultural localization while leveraging partners’ expertise in infrastructure, hardware optimization, and talent development. The strategy aligned with the company’s broader philosophy of partnership-driven implementation, extending the co-creation model from customers to the entire technology ecosystem.

Enterprise AI Transformation Leadership (2024-2025)

As WIZ.AI scaled, its leadership team was adjusted to support its growth as a global enterprise software company. Alex Song transitioned from COO to Chief Revenue Officer, indicating a greater focus on revenue growth and market expansion [6]. The company reported that Fortune 500 companies and unicorn startups accounted for 60% of its client portfolio [6]. In June 2025, Robin Li, an enterprise technology executive with over 20 years of experience, joined as Senior Director of AI Strategy and Partnerships [7].

WIZ.AI positioned itself as an “enterprise-ready AI agent platform,” forming strategic partnerships with companies like AWS, NetSuite, and FileAI to deliver AI transformation solutions [6]. 

By 2025, the company was actively participating in AI transformation events across the region, with Alex Song explaining their value proposition in Manila: “WIZ.AI is a conversational AI company, and our focus is on helping customers improve customer engagement. Specifically, we help customers increase their revenue…we also help customers save costs by using AI agents to handle repetitive tasks more efficiently. This is especially valuable for large-scale enterprise customers. Our AI talkbots, for instance, can handle one million phone calls—whether outbound or inbound—in just one hour” [6].

The company’s strategic focus remained on delivering practical ROI, solving existing business problems rather than just selling futuristic concepts. As Zhang emphasized in 2023, “People have experienced AI personally, but adopting it in an enterprise setting is different. There’s a journey from consumer apps to enterprise solutions, and we need to ensure reliability. We should focus on existing use cases and solve pain points from the past. Don’t just sell the future; solve the problems from the past” [4].

How AI Transformation Insights Shape Product and Growth Strategy

WIZ.AI’s deep engagement with enterprise AI transformation has fundamentally shaped both its product development roadmap and growth strategy. The company’s leadership has developed a nuanced understanding of the gap between AI builders and enterprise buyers, which directly informs how they approach innovation and market expansion.

Partnership-Driven Implementation vs. Self-Serve Products

A defining strategic choice for WIZ.AI has been its commitment to partnership-driven implementation rather than pursuing a pure self-serve product model. This decision has proven particularly prescient in light of industry-wide AI implementation challenges. The MIT NANDA study’s finding that 95% of AI pilots fail to deliver ROI identified a key culprit: generic self-serve AI tools that, while effective for individual use, “stalled in enterprise settings because they did not learn from or adapt to specific workflows” [17].

WIZ.AI’s partnership model directly addresses this “learning gap.” Rather than offering a standardized product that customers must adapt to their needs, WIZ.AI invests in understanding each client’s specific context, workflows, and pain points before deployment. This approach manifests in several ways. The company establishes local R&D, product, and delivery teams in each market before sales teams, ensuring solutions are built with deep contextual understanding rather than imposed from headquarters [1]. 

WIZ.AI also offers managed services through partners like ePLDT, where the complexity of AI implementation is handled by experts while clients focus on core business operations [10]. Most importantly, the company commits to continuous learning and iteration, with both WIZ.AI and its partners “learning from everyday experience” to improve performance over time [10].

This partnership approach has trade-offs. It is more resource-intensive than a self-serve model, requiring significant investment in local teams and ongoing customer engagement. It also limits the speed of customer acquisition compared to viral self-serve products. However, the MIT study’s finding that vendor partnerships succeed at 67% compared to only 33% for internal builds validates WIZ.AI’s strategic choice [17]. By focusing on delivering measurable ROI through deep partnerships rather than maximizing user acquisition through self-serve products, WIZ.AI has positioned itself among the 5% of AI implementations that actually succeed in creating business value.

From Technology-First to Problem-First Product Development

The company’s evolution reflects a deliberate reprioritization from leading with technology capabilities to leading with business problem-solving. Zhang’s philosophy of “solving problems from the past” rather than “selling the future” has become embedded in WIZ.AI’s product development process [4]. 

This manifests in several ways. First, the company works hand-in-hand with customers to develop productized solutions. “We’re actually working hand in hand with customers on some of these cases, which we consider is very productized…then later we will drive more [adoption] with customers…when we collect enough customers insight and also their input, then that’s how we cross over all the different touchpoints of the whole user journey,” Zhang explained [1].

Second, WIZ.AI has embraced a platform ecosystem vision that enables customer self-service and knowledge sharing. “I think all SaaS companies will become platform ecosystems, to invite more people to create things,” Zhang predicted [1]. This vision extends to potential revenue-sharing models where customers who design effective workflows could benefit financially, creating a flywheel effect for product innovation and adoption.

Balancing Foundation Models with Domain Expertise

WIZ.AI’s approach to the LLM revolution demonstrates strategic pragmatism. Rather than viewing large foundation models as a threat, the company sees them as complementary to domain-specific expertise. As Alex Song explained in 2025, “Most large language models are built on general knowledge from publicly available sources. They’ve already been trained on a vast amount of internet data. However, in the commercial world, a lot of valuable industry-specific knowledge is proprietary and not publicly available. That’s one of the key differentiators” [6].

This insight has led WIZ.AI to develop a hybrid approach: leveraging the reasoning capabilities of large foundation models while maintaining proprietary domain-specific models trained on industry data. The company’s 13-billion parameter LLM and domain-specific models for languages like Bahasa Indonesia represent this balanced strategy [5]. This approach allows WIZ.AI to offer both cutting-edge AI capabilities and the deep vertical expertise that enterprises require for mission-critical applications.

Security and Compliance as Product Features, Not Afterthoughts

WIZ.AI’s focus on highly regulated industries—banking, financial services, insurance, telecommunications, and healthcare—has made security and compliance core product features rather than add-ons. “Our customer base overlaps significantly with the financial services sector…We primarily serve BFSI (banking, financial services, and insurance), e-commerce, healthcare, and telecommunications—industries that are highly regulated,” Song noted [6].

The company offers both SaaS and on-premise deployments, with strict adherence to data residency requirements and regulatory mandates regarding data retention. “Since we handle conversational data—often including highly sensitive financial information—many customers prefer to install our solutions on-premise to ensure data never leaves their environment,” Song explained [6]. This security-first approach has become a competitive advantage, particularly as enterprises become more cautious about AI adoption.

Geographic Expansion Driven by Market Readiness, Not Just Market Size

WIZ.AI’s geographic expansion strategy is informed by an understanding of AI adoption readiness across different markets. Robin Li’s observations about the differences between China and Southeast Asia are instructive. “In China right now there’s a top-down trend that all of the leaders are trying to push the new technology into their business because they’re facing more challenges about business growth and also about cost saving. But in Asia right now, companies normally, the industry people and customers, they’re waiting for the new trends from the AI technology startup companies,” Li explained [7].

This understanding has led WIZ.AI to tailor its go-to-market approach by region. In markets with top-down AI adoption (like China and increasingly the Middle East), the company can focus on executive-level selling and large contracts. In markets with bottom-up adoption (like Southeast Asia and parts of Latin America), WIZ.AI emphasizes proof-of-concept deployments, customer education, and building reference cases. The company’s success in translating Southeast Asian solutions to Latin America validates this market-readiness framework [4].

The Platform Vision: From Point Solutions to Ecosystem

Looking forward, WIZ.AI’s product strategy is evolving from offering point solutions to building a comprehensive conversational AI platform. This vision encompasses several dimensions. First, expanding beyond voice to other interfaces. “We are starting with the phone because the phone channel is the most challenging one because of the quality and also the application [is wide], and it’s also limited by infrastructure. But in the future, I think we can drive more applications—what about the metaverse in the future…it’s quite promising for the next 10 years,” Zhang envisioned [1].

Second, enabling agentic AI frameworks that integrate multiple AI agents with hybrid LLMs, APIs, and enterprise systems. As Song described, “Initially, AI agents were designed to handle specific tasks or use cases. But today, conversations are shifting toward agentic AI frameworks. This means integrating multiple AI agents with hybrid large language models, APIs, and different enterprise systems. By doing this, AI agents can become even smarter, solving complex problems and driving greater efficiency” [6].

Third, maintaining the company’s commitment to continuous technological innovation while ensuring commercial viability. “Our ambition is to actually go global, and figure out more applications and use cases for industries, and also I think we [want to] push the boundary of technology development and models [through] real business use cases,” Zhang stated [1]. This balance between research and commercialization, between pushing technological boundaries and solving immediate business problems, defines WIZ.AI’s strategic approach.

Leadership Philosophy and Organizational Culture

WIZ.AI’s success is also rooted in its distinctive leadership philosophy and organizational culture. Zhang’s transition from venture capitalist to founder has shaped her approach to building the company. “Venture capital is a very interesting and challenging job, because those are the smartest people, and you actually need to make money from them too as a VC. When you come to the founder side, now it’s your own show. You need work by yourself, you are the creator, you need to solve your own problems,” she reflected [1].

This experience has led to a leadership style that emphasizes intellectual honesty, transparency, and cross-border collaboration. “I love the very important term called intellectual honesty. So my leaders, my teammates, know if I realize something is wrong, I need to speak out. So that culture can be straightforward. It’s important, especially for cross-border,” Zhang explained [1].

The company actively encourages cross-regional collaboration, with team members from one country supporting projects in another, creating career development opportunities while spreading company culture. “For some of our Thailand projects, we are getting a Singapore colleague and also an Indonesian colleague support from sales to presales, from delivery side or training sides, so once they support one or two times actually they notice they have more career path towards regional leadership,” Zhang shared [1].

This flat organizational structure and emphasis on direct communication has proven essential for managing a globally distributed team. “Most of the time when you see the cross-border issues, they’re because you don’t know what happened from different countries, and also like you have too many layers and also you don’t have any sense about the local insight because of the layers in communication,” Zhang noted [1]. By keeping reporting lines short and encouraging transparency, WIZ.AI has been able to maintain agility and responsiveness even as it scales.

Financial Performance and Growth Metrics

WIZ.AI’s growth has been nothing short of impressive. The company achieved a revenue growth rate of over 100% in the 2024-2025 period [8]. A successful Series B funding round, which raised tens of millions of dollars, provided the capital to further scale its enterprise AGI solutions [8]. The company’s customer base has grown to over 300 global enterprises, with a geographic reach spanning more than 17 countries and support for over 17 languages and dialects [7]. The team has expanded to between 251 and 500 employees, with a core operating team of approximately 166 people [8].

The Road Ahead: Challenges and Opportunities

As WIZ.AI enters its eighth year, it faces a new set of challenges and opportunities in a rapidly evolving AI landscape. The commoditization of LLMs, the emergence of Model Context Protocols (MCPs) that are changing cost structures, and new pricing paradigms for AI products are all factors that will shape the company’s future strategy [7]. Key strategic questions for WIZ.AI include how to maintain its first-mover advantage in emerging markets, how to balance its horizontal platform strategy with the need for vertical specialization, and how to scale its customer base from over 300 to thousands of enterprises while maintaining the high-touch service that has been a hallmark of its approach.

The company must also navigate the tension between building proprietary technology and leveraging increasingly capable foundation models. As the AI landscape consolidates around a few major LLM providers, WIZ.AI’s ability to differentiate through domain expertise, localization, and vertical integration will be critical. The company’s investments in voice interface design, small-data modeling, and industry-specific applications position it well, but continued innovation will be essential.

Conclusion: Lessons from Seven Years

WIZ.AI’s development provides several takeaways for building a global AI company. A global focus from the start, a customer-driven expansion strategy, a focus on technical development, and a commitment to solving specific business problems have been central to its approach. The company’s ability to build AI models from small data sets, its work in voice interface design, and its focus on localization have been key competitive differentiators. By developing for emerging markets, using a partnership-based growth model, and balancing innovation with a focus on practical ROI, WIZ.AI has established a position in the enterprise AI market.

WIZ.AI’s leadership has emphasized intellectual honesty, transparency, and a problem-first rather than technology-first approach. As Zhang advised, “So when we’re working with VCs, sometimes I think I would love to actually have more problem solving partners, where we really bring to them our problems and they can help us a lot” [1]. This philosophy—of being honest about challenges, transparent about limitations, and focused on solving real problems—has enabled WIZ.AI to build trust with customers, partners, and investors alike.

As the company looks to the future, its ability to navigate the complexities of the evolving AI landscape while staying true to its founding principles will be critical to its continued success. The next chapter of WIZ.AI’s story will be written in the context of rapid AI commoditization, intensifying competition from hyperscalers, and the ongoing challenge of translating technological capability into business value. If the first seven years are any indication, WIZ.AI is well-positioned to meet these challenges head-on.

Discussion Questions

1. How can WIZ.AI maintain its competitive edge as large language models become more commoditized and foundation model capabilities improve?
2. What are the key challenges and opportunities for WIZ.AI as it continues to expand into new geographic markets, particularly in regions with different AI adoption patterns?
3. How should WIZ.AI balance the development of its horizontal platform with the need for industry-specific solutions and deep vertical expertise?
4. What role will strategic partnerships play in WIZ.AI’s next phase of growth, and how can the company maintain its differentiation while integrating with larger ecosystem players?
5. How can WIZ.AI continue to attract and retain top talent in the highly competitive AI industry, particularly as it competes with both well-funded startups and deep-pocketed tech giants?
6. As AI agents and agentic AI frameworks become more prevalent, how should WIZ.AI evolve its product architecture to remain at the forefront of conversational AI innovation?

Exhibits

Exhibit 1: WIZ.AI Company Timeline

Exhibit 2: WIZ.AI Competitive Advantages

References

[1] On Call with Insignia Ventures. “S04 Call #26: Driving Conversational AI Adoption Across ASEAN and Beyond, Pioneering Voice AI Development, and Leading a Global Company with WIZ.AI CEO Jennifer Zhang.” Insignia Business Review. August 23, 2022. https://review.insignia.vc/2022/08/23/s04-call-26-wiz-ai-ceo-jennifer-zhang-conversational-voice-artificial-intelligence/

[2] On Call with Insignia Ventures. “S04 Call #32: Women in Tech’s Stories and Opportunity Creation with Growth-Stage CEO-Founders WIZ.AI’s Jennifer Zhang and Pinhome’s Dayu Dara Permata.” Insignia Business Review. October 25, 2022. https://review.insignia.vc/2022/10/25/season-4-episode-32-women-in-tech-pinhome-dayu-dara-permata-wiz-ai-jennifer-zhang/

[3] On Call with Insignia Ventures. “S04 Call #38: Leading Southeast Asia’s Enterprise Innovation Into Its Global Future with Intellect’s Theodoric Chew, Brankas’s Todd Schweitzer, and WIZ.AI’s Jianfeng Lu.” Insignia Business Review. December 21, 2022. https://review.insignia.vc/2022/12/21/season-4-episode-38-enterprise-innovation-intellect-wiz-brankas/

[4] On Call with Insignia Ventures. “Call 145 | Building the Future Where Every Company is An AI Company.” Insignia Business Review. November 21, 2023. https://review.insignia.vc/2023/11/21/season-5-episode-34-call-145-ai-in-business/

[5] Joquino, Paulo. “Going Global with AI: A Case Study of WIZ.AI and South America.” Insignia Business Review. May 16, 2025. https://review.insignia.vc/2025/05/16/going-global-wiz-ai-south-america/

[6] On Call with Insignia Ventures. “The Magic of ‘Small’: AI Transformation for Business | Call 178.” Insignia Business Review. March 5, 2025. https://review.insignia.vc/2025/03/05/ai-transformation/

[7] On Call with Insignia Ventures. “Driving conversational AI adoption from China to Singapore then the world with WIZ.AI Senior Director of AI Strategy and Partnerships Robin Li.” Insignia Business Review. September 25, 2025. https://review.insignia.vc/2025/09/25/wiz-ai-robin-li/

[8] Getlatka. “How WIZ.AI hit $18.3M revenue with a 166 person team in 2025.” Accessed February 2026. https://getlatka.com/companies/wiz.ai

[9] Mynt. “GCash lending arm Fuse advances AI use to strengthen responsible collections practices and protect customer dignity.” Mynt Newsroom. February 4, 2026. https://mynt.com.ph/newsroom/gcash-lending-arm-fuse-advances-ai-use-to-strengthen-responsible-collections-practices-and-protect-customer-dignity

[10] WIZ.AI. “Voice Agent for Digital Transformation: ePLDT & WIZ.AI Success Story.” WIZ.AI Blog. Accessed February 2026. https://www.wiz.ai/category/features/

[11] WIZ.AI. “Security Bank WIZ.AI Partnership: Conversational AI for Enhanced Customer Engagement.” WIZ.AI Blog. November 17, 2025. https://www.wiz.ai/security-bank-wiz-ai-partnership/

[12] WIZ.AI. “WIZ.AI and Smartfren for Business Partner to Revolutionize Customer Experience with AI.” WIZ.AI Blog. October 1, 2024. https://www.wiz.ai/enterprise-ai-solutions-wiz-ai-smartfren-customer-experience/

[13] WIZ.AI. “IHH Talkbots Reduced Operational Stress During Peak Hours by 65%.” WIZ.AI Client Stories. Accessed February 2026. https://www.wiz.ai/clients-stories/

[14] WIZ.AI. “AI Agents Customer Engagement: Toyota Financial Services Philippines Success Story.” WIZ.AI Client Stories. Accessed February 2026. https://www.wiz.ai/clients-stories/

[15] WIZ.AI. “SeaMoney’s Conversion Rates Soar Up to 50% with WIZ.AI.” WIZ.AI Client Stories. Accessed February 2026. https://www.wiz.ai/clients-stories/

[16] WIZ.AI. “AI Agent in Financial Industry: GoTo Financial Success Story.” WIZ.AI Client Stories. Accessed February 2026. https://www.wiz.ai/clients-stories/

[17] Estrada, Sheryl. “MIT report: 95% of generative AI pilots at companies are failing.” Fortune. August 18, 2025. https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/

[18] PR Newswire. “Agora and WIZ.AI Partner to Deliver Enterprise-Ready AI Agent Solutions.” June 18, 2025. https://www.prnewswire.com/news-releases/agora-and-wizai-partner-to-deliver-enterprise-ready-ai-agent-solutions-302484478.html

[19] Joquino, Paulo. “When Infrastructure Meets Localization: The Agora-WIZ.AI Partnership and the Future of Conversational AI.” Insignia Business Review. June 20, 2025. https://review.insignia.vc/2025/06/20/wiz-ai-agora/

[20] WIZ.AI. “WIZ.AI and Intel partner to improve voice AI in Asia.” LinkedIn. December 2025. https://www.linkedin.com/posts/wiz-ai_wizai-intel-voiceai-activity-7338424607114186752-MtlT

[21] WIZ.AI. “WIZ.AI Joins Forces to Establish the AI R&D Centre (Southeast Asia) in Da Nang, Vietnam.” LinkedIn. March 2025. https://www.linkedin.com/posts/wiz-ai_vietnam-singapore-finance-activity-7305827197632581632-XkiW