Axoniq, a company trusted by over 65,000 companies globally and with more than 70 million downloads, transforms how organizations develop AI native applications that seamlessly evolve and scale to meet tomorrow’s business challenges. Pulse 2.0 interviewed Axoniq CEO and Board Member Jessica Reeves to gain a deeper understanding of the company.
Jessica Reeves’ Background
Jessica Reeves, CEO & Board Member, Axoniq
Could you tell me more about your background? Reeves said:
“My path to becoming CEO of Axoniq is non‑traditional, and I wouldn’t have it any other way. I was adopted from Korea as an infant, raised in rural Ohio, and lost both my father and brother unexpectedly when I was young. Those experiences shaped how I approach leadership. I learned resilience early, how to operate in uncertainty, and how to create opportunity rather than wait for it.”
“I started my career in HR, which turned out to be an advantage in technology leadership. Understanding people, incentives, and organizational dynamics became the foundation for everything that followed. That human‑centered perspective stayed with me as I moved into technology operations and scaling companies.”
“Before Axoniq, I was COO at Anaconda, where I helped scale the company into a unicorn with more than $150M in ARR. That experience reinforced a lesson I carry into my current role. Market leadership doesn’t come from clever technology alone. It comes from solving real enterprise problems in production environments.”
“What drew me to Axoniq is that we’re solving the next version of that same challenge. Enterprises now need an AI infrastructure that is auditable, scalable, and integrated into real business processes. Axoniq brings several years of proven event‑driven architecture, millions of developers in our ecosystem, and real Fortune 100 traction. We’re at the inflection point where AI infrastructure becomes its own market category.”
“My background isn’t a liability. It’s a competitive advantage. I bring perspective shaped by adversity, a bias toward execution, and a leadership style grounded in reality rather than hype.”
“My role is to convert our architectural advantage into category‑defining growth. That responsibility breaks down into four core areas.
First is strategy and market positioning. We’re not just building software. We’re defining what the backend for enterprise AI looks like. I’m responsible for articulating why event‑driven architecture is foundational to AI success and positioning Axoniq as the category leader.
Second is capital allocation and growth. Following our Series A, we’re balancing aggressive product innovation with focused market expansion. Roughly 60% of our investment goes into product engineering, particularly our agentic AI capabilities and Dynamic Consistency Boundaries, which give enterprises architectural flexibility as systems evolve. The remaining 40% supports U.S. market entry with enterprise sales leaders who understand AI infrastructure and open source.
Third is team building. We’re intentionally assembling a diverse leadership team, including women leaders of Asian descent at the executive level. This isn’t about optics. It’s about building better companies. Diverse teams make stronger decisions, especially in a field as homogeneous as AI infrastructure.
Fourth is bridging open source and enterprise. Millions of developers rely on the open source Axon Framework. My responsibility is to ensure the community continues to thrive as we build a durable enterprise. Those goals reinforce each other.
Ultimately, success means enterprises can’t imagine building AI systems without Axoniq, just as they can’t imagine building applications without databases today.”
Favorite Event
What has been your favorite event working for the company so far? Reeves shared:
“Our Amsterdam conference last October, where we launched the Axoniq Platform. We built it in three months, from concept to production.”
“That moment captured what makes Axoniq different. We don’t just sell event‑driven architecture. We run on it ourselves. The same technology that lets our customers move fast without breaking things is what enabled us to ship a complete three‑layer platform in a single quarter.”
“Watching customers experience that was powerful. This wasn’t theoretical. If we can go from zero to a production‑ready platform in 90 days using our own infrastructure, it completely reframes what’s possible for enterprises that stop fighting legacy systems.”
“That launch wasn’t just a milestone. It was proof.”
Core Products
What are Axoniq’s core products and features? Reeves explained:
“Axoniq provides the backend infrastructure that makes enterprise AI work in the real world. We recently launched the Axoniq Platform, the first unified platform with a native explainability layer built in. It allows teams to learn, build, monitor, and analyze applications end-to-end.”
“The platform has three core components.
The first is our event‑sourced memory foundation, anchored by Axon Framework 5. It preserves every business decision as an event with full causal history. Dynamic Consistency Boundaries allow organizations to redefine data and transactional boundaries without losing historical context, reducing data evolution timelines from quarters to weeks.
The second is governance and traceability through Axon Server 2025.2.0, our high‑performance, event‑native data store. It captures all system activity and makes it queryable in real time, which is essential for regulated industries.
The third is our AI‑assisted orchestration layer with agent capabilities. Through Model Context Protocol extensions, AI agents can interact securely with enterprise systems. Agents gain structured memory and the ability to act transparently, with full auditability.
The result is AI that can show its work. Every decision has a traceable causal chain, before, during, and after model inference. Explainability becomes a systems architecture capability rather than a fragile model‑level add‑on.”
Challenges Faced
Have you faced any challenges in your sector recently? Reeves acknowledged:
“The biggest challenge isn’t technical. It’s educational. Most enterprises still focus on models and applications while treating infrastructure as an afterthought. They’re building AI on assumptions that don’t hold at enterprise scale.”
“We see the same issues repeatedly. AI systems rely on point‑in‑time database snapshots instead of business context over time. AI is bolted on rather than treated as a native participant in business workflows. Companies optimize inference speed while ignoring data‑gathering latency, which is often the real bottleneck.”
“We’ve addressed this through our developer community and through category education. When organizations hit scaling walls, developers who already know Axon bring us into the conversation. We also position AI infrastructure as foundational, not optional.”
“On a personal level, I bring a different voice to these discussions. As a woman and Asian‑American CEO in AI infrastructure, I talk openly about who builds this technology and why it matters. We’re not just changing how AI works. We’re changing who gets to shape it.”
Evolution Of The Company’s Technology
How has the company’s technology evolved since launching? Reeves noted:
“Axoniq began in 2016, solving event sourcing and CQRS for complex enterprise systems, long before AI made those capabilities essential.”
“What started as a solution for consistency and auditability became the foundation for enterprise AI. AI systems face the same problems we were already solving, i.e., real‑time context, traceability, integration, and scale.”
“We proved the architecture through millions of downloads of the open source Axon Framework. With the Axoniq Platform, we now deliver a unified system. Axon Framework 5 introduces Dynamic Consistency Boundaries and native asynchronous processing. Axon Server 2025.2.0 provides a runtime built for agentic workloads. Our Agent capabilities give AI systems structured memory and secure interaction.”
“With the launch of the Axoniq Platform, we’re delivering a complete, unified system. We’ve moved from reactive to proactive: our Agent capabilities don’t just respond to events but enable autonomous AI that operates safely within business constraints while maintaining full explainability.”
“The key insight? We didn’t pivot to AI. We built the foundation AI needs long before the hype cycle. What we built for operational forensics turned out to be the perfect foundation for AI – complete decision history, the ability to replay exact sequences, and full context. This consistency is why our approach can’t be fast followed.”
Significant Milestones
What have been some of the company’s most significant milestones? Reeves cited:
“Getting 80% Fortune 100 adoption has been huge. This isn’t from aggressive sales. It’s developers using our open source framework who pull us into AI conversations when their companies hit scaling walls. It creates a moat competitors can’t replicate.”
“Our Series A funding gives us the runway to simultaneously scale product innovation and U.S. market expansion. We’re not choosing between breakthrough technology and market execution. We’re doing both with strategic sequencing.”
“The Axoniq Platform launch is transformative. We’re the first to deliver a unified platform with native explainability built in.”
“Our community scale matters deeply. Millions of developers and thousands of GitHub contributions create a community-driven innovation engine. When enterprises evaluate AI infrastructure, they already have internal advocates.”
“We’ve achieved meaningful product validation that matters. One large U.S. bank customer reduced audit preparation time by 80%. A large German retailer scaled to 7,000 partners and 60 million products, processing millions of daily updates with ease.”
“But the milestone I’m most proud of is assembling a leadership team that reflects the diversity I want to see in tech. Our executive team includes multiple women leaders of Asian descent. We’re proving that you can build world-class AI infrastructure companies with perspectives that have historically been excluded from these conversations.”
Customer Success Stories
Can you share any specific customer success stories? Reeves highlighted:
“A good example comes from the financial services industry. A Fortune 100 firm struggled with fraud detection because its AI relied on stale database snapshots. By the time anomalies were flagged, the damage was already done.”
“After implementing Axoniq, their AI had real‑time access to transaction event streams. Detection accuracy improved, false positives dropped, and every decision became traceable. When regulators audited the system, transparency became a competitive advantage.”
“In broader terms, teams often start with Axoniq for a specific use case and return when broader AI initiatives hit architectural limits. When AI fails due to infrastructure, the conversation quickly moves to the executive level.”
“What’s consistent across success stories? Companies see their AI actually working reliably at scale, and the conversation shifts from ‘nice technology’ to ‘competitive necessity.’ They move faster, make better decisions, and operate with confidence, including in regulated environments where competitors struggle.”
Funding/Revenue
Are you able to discuss funding and/or revenue metrics? Reeves revealed:
“We recently closed our Series A, which gives us the runway to execute on product innovation and market expansion. While I can’t share specific figures, I can share how we’re investing.”
“Roughly 60% goes into product engineering and 40% into U.S. market expansion. That balance reflects a lesson from scaling Anaconda: differentiated technology without execution stalls, and growth without differentiation burns cash.”
Total Addressable Market
What total addressable market (TAM) size is the company pursuing? Reeves assessed:
“We’re not pursuing an existing market. We’re creating a new category. By 2028, we expect AI infrastructure to be a distinct, tens-of-billions market category, where enterprises budget for it like they do for databases or security.”
“The immediate addressable market is Fortune 100 companies spending $50 million to $200M annually on AI initiatives that are failing due to infrastructure limitations. The expanding market includes every enterprise implementing AI that faces the same architectural challenges we solve. We’re not waiting for consultants to define this market. We’re defining it. By the time the quadrants are created, we’ll already be category leaders.”
Differentiation From The Competition
What differentiates Axoniq from its competition? Reeves affirmed:
“Our defensible edge isn’t just technology. It’s also an architectural philosophy. Eight years of event-driven depth sets us apart. While competitors bolt AI onto existing architectures, we’ve been solving the core problem since 2016. You can’t fast-follow eight years of architectural thinking and community validation.”
“There’s also a fundamental philosophical difference. The entire cloud industry is built on stateless, horizontal scaling. But enterprise AI needs to be stateful and contextually aware. This isn’t a feature gap they can patch. It’s a fundamental architectural difference that requires a complete rethink.”
“Our community moat is significant. Our open source community creates switching costs that proprietary platforms can’t match. Millions of developers understand our patterns, contribute to our ecosystem, and advocate internally. Hyperscalers can’t replicate community-driven innovation.”
“Here’s something people don’t talk about enough. AWS, Google, and Microsoft make money selling compute and storage. They’re incentivized to build AI systems that consume more resources. We make money when AI systems run efficiently and reliably. Our event-driven approach reduces infrastructure costs, which directly conflicts with their business models.”
“I’ll add something unconventional here. Our differentiation includes who’s building this company. As a woman CEO with a non-traditional background leading a diverse executive team in AI infrastructure, we bring perspectives that are systematically excluded from these conversations. That diversity isn’t virtue signaling. It enables better product development and strategic decision-making.”
Future Company Goals
What are some of the company’s future goals? Reeves emphasized:
“Over the next year, we’re expanding Fortune 100 deployments and building a strong U.S. enterprise sales organization.”
“Over the next two to three years, we’re achieving category-defining recognition and revenue milestones that prove the market exists. Companies on our platform will operate at fundamentally different speed and scale, making decisions in milliseconds with full auditability and real-time optimization. We’ll expand into adjacent markets where event-driven AI architecture creates a competitive advantage.”
“Long-term vision? By 2028, enterprises will budget for AI infrastructure like databases or security. We’ll have created a market category, not just a successful company. Success means redefining enterprise software in the age of artificial intelligence. And doing it with a team that represents the diversity of the global technology community.”
Additional Thoughts
Any other topics you would like to discuss? Reeves concluded:
“A couple of things. There’s a massive gender gap in GenAI roles. Studies show AI development is overwhelmingly male-dominated, with some recent industry conferences, for example, seeing 95% male attendance. Yet the industry is building infrastructure that will shape how businesses operate for decades. Who builds this technology matters because it determines whose perspectives and priorities get embedded into systems.”
“At Axoniq, we’re intentionally building differently. For example, our executive team includes multiple women leaders and folks who descend from all parts of the world. We’re actively recruiting women developers in a field that systemically excludes them. To be clear, this isn’t us just being socially responsible. It brings tangible competitive advantages. Diverse teams make better decisions, build more resilient products, and understand broader market needs.”
“I want to be explicit about this. If you’re a woman in tech, particularly in infrastructure or AI, Axoniq is a place where your perspective matters. We need more women leading these conversations, not just participating in them.”
“Also, as someone adopted from Korea, raised in rural Ohio and eventually a tech CEO, I want to address the immigration conversation. I created value in the US economy. Helped build a unicorn at Anaconda and is now building category-defining infrastructure at Axoniq. My non-traditional background and outsider perspective contributed to that success, not despite it but because of it.”
“The tech industry benefits enormously from diverse perspectives and immigrant contributions. When we exclude people based on origin rather than ability, we don’t just lose their individual contributions. We lose the innovation that comes from different ways of thinking.”
“I’m proof that resilience, drive, and non-traditional paths can create extraordinary outcomes. And I’m committed to building a company that recognizes talent wherever it comes from.”
