Mal Vivek, Founder and CEO of Zeb – Interview Series

Mal Vivek leads Zeb as Founder & CEO and serves on the advisory board of G8RTech. Previously, she held senior leadership roles at AVASOFT, building enterprise collaboration and migration products on Microsoft 365. Earlier, she co-founded Girls Make Apps and worked in computational biology and machine learning at Memorial Sloan Kettering Cancer Center.

瑞伯 is an AI-driven digital transformation firm and AWS Premier Tier Partner, offering AI, migration & modernization, data & analytics, application development, and security solutions across industries like retail, fintech, logistics, and healthcare.

You’ve had a diverse journey—from co-founding Girls Make Apps to leading AVASOFT and now founding zeb. What inspired you to start zeb, and how does your past experience shape your vision today?

In my time in the system integrator space, I saw most vendors operating transactionally as either ticket takers or strategy consultants delivering expensive decks without substance. With the AI boom coming, I saw a gap for organizations who could understand the technology, stay ahead of it, AND translate its use to actual business applications. My vision for zeb was to create an AI-centric technology transformation organization with industry expertise and the agility to productionize AI at scale. My experience with Girls Make Apps taught me a lot about the importance of making technology accessible, which directly influences zeb's mission to democratize AI for businesses of all sizes.

What gaps in enterprise AI implementation did you see in the market that zeb was specifically built to address?

The main issue is that most companies build AI in silos without understanding that connecting systems and processes is needed more than ever before to advance value. For true transformation, organizations need to integrate AI into existing processes rather than treating it as separate. At zeb, we serve every aspect of the technology stack to transform companies end-to-end, ensuring AI becomes part of the process and remains useful and owned by the client. The biggest gap was companies building AI without the right data foundation or understanding of integration complexity.

Women-led AI companies raised over $1.6B in 2024 but still account for less than 15% of total funding. From your perspective, what unique strengths do women entrepreneurs bring to enterprise AI?

I think the biggest strength women have is our ability to multi-task which is crucial when dealing with balancing a large scale transformation with AI adoption fears. There's a lot of fear that arises when companies use AI, and women are really strong at taking an empathy-first approach to navigate human-centered challenges while driving technological innovation. We take action to make positive change while questioning if there are better ways for things to be done.

How do programs like WBE (Women’s Business Enterprise certification) and WOSB (Women-Owned Small Business program) help level the playing field for women-led tech companies?

Programs like WBE and WOSB are so necessary for widening the aperture of opportunity as they recognize and provide connection for large enterprises to women-led businesses. They’re essential for creating systemic change we believe in. Having the privilege of opportunities is not something I take for granted, and I feel a pressing responsibility to extend that power to those I can. These programs help create the kind of access and recognition that can transform entire industries.

Can you walk us through the proprietary AI-powered implementations zeb has developed? How do they differ from off-the-shelf AI solutions?

Definitely – in general our solutions are custom-built for each organization rather than the limited configurability that an off the shelf one-size-fits-all approach provides. This has led to a wide range of solutions catered to business needs – for one of our customer, a large enterprise supply chain company, we built a self service chat interface integrated with Teams that enabled their operations team to ask any question realtime of transactional shipment and cost data. For another customer in the ISV space, we build automated workflows that aggregated different sources of marketing data and enriched it to provide additional context that they could externally surface to their end customers in an agentic AI architecture. We're also working on several agentic agent-to-agent communication workflows with orchestrations and incentive chains that can automate functions previously requiring multiple teams and expertise levels for several enterprises all customized to their roles and business context.

How do you ensure that the AI you deploy is designed to elevate teams and processes rather than replace them?

We assess where AI can aid companies by freeing up human creativity and putting AI to work on repetitive processes that waste human capital. While AI replaces some lower-order functions, most implementations still require humans in the loop, and your value is determined by how you adapt and use AI tools to enhance workflows. We start small with skeptical customers, prove value on short-term engagements, then build trust to tackle bigger challenges together. This approach serves as a show and tell of how we augment rather than replace.

What are some of the most compelling examples of zeb’s AI solutions transforming workflows—whether in healthcare, retail, or financial services?

Our solution accelerators built in partnership with AWS, Databricks and ServiceNow have taken on a life of their own with customers creating incredibly interesting use cases that challenge our teams. One customer used our SuperInsight accelerator to design custom alerts based on customer acquisition trend data. Another wanted to build a custom “brain” representing each customer's marketing campaigns and history so AI could interact with that context. We had another customer in the healthcare space, wanting to use NLP and pattern identification to assess trends in patients’ habits that impact their chronic pain levels. We serve manufacturing/supply chain, retail, digitally native businesses, and hedge funds/private equity—I think our diverse customer base shows that any business with an open mind for change and innovation is a good fit for AI.

Funding remains a challenge for women-led startups. Where do you see the biggest investment opportunities for women-led AI ventures in the next few years?

I believe the biggest opportunities for women-led AI ventures are the same as the biggest opportunities for AI ventures in general – where we see the most traction is in cybersecurity, healthcare and web 3.0. The key is focusing on businesses that create real value and ROI without underestimating the pull of routine process in the businesses these leaders are seeking to disrupt. I know fantastic women leaders in all of those sectors and they are great for a unified reason: they have deep experience being the customer of the product they are looking to build and as such don’t make false or wishful assumptions about the AI ability to change process overnight.

What role do you see zeb playing in shaping enterprise adoption of generative AI over the next 3–5 years?

Changes will be dramatic even in the next two years—we've barely scratched the surface of what's possible. This is the first time since the dot com bubble we've had a technology that works with massive impact plus market pressures pushing every company to adopt or get surpassed. In 5 years, zeb will be in a category of its own, proving constant innovation and scale aren't mutually exclusive. We've already launched zeb labs our keystone R&D initiative in the last year which provides our internal teams and customers with objective input on results from AI advances – we plan to continue growing this initiative and contributing meaningfully to research around model safety, governance and model reward and incentive frameworks which we feel will be critical as adoption continues to rise.

What advice would you give to young women entering AI who aspire to build companies like zeb?

The main misunderstanding about being a young founder is the inherent limitations people place on you—advice like pick fewer partners, do one thing really well. These are limitations people impose, but it's possible to do both, and in today's AI landscape it's necessary. My biggest advice is don't let people confine you to boxes or limit your vision based on traditional thinking. The world has changed overnight with AI and the old rules don’t apply unilaterally anymore – everyone around you is right where you are figuring it out for the first time too.

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