Letter to Shareholders from Smartbird CEO Nadia Carlsten
Rhea-AI Summary
Smartbird (NASDAQ: BIRD) CEO Nadia Carlsten outlines the company’s strategy following its transformation from footwear retailer Allbirds into an AI infrastructure provider. Allbirds sold its footwear assets, changed its name, brought in new leadership and raised capital to focus entirely on dedicated AI infrastructure.
Smartbird aims to serve enterprises that need customized, dedicated or on‑premises AI infrastructure for inference workloads, emphasizing performance, cost, security and control. The company offers a managed model, designing, procuring, deploying and operating clusters around customer requirements and remaining vendor‑agnostic on technologies.
According to Smartbird, as of June 30, 2026, access to over $200 million in capital from cash, a convertible facility and an ATM program supports its growth plans. The letter stresses disciplined capital allocation, a small technically deep team, new expert board nominees, and operating principles centered on customer needs and sustainable economics.
Positive
- Access to over $200 million in capital as of June 30, 2026
- Completed sale of legacy footwear assets and pivot to AI infrastructure focus
- Managed dedicated infrastructure model targeting enterprise AI inference workloads
- Vendor-agnostic approach to adopting new specialized AI hardware technologies
- Planned addition of two industry experts to the board of directors
Negative
- None.
Key Figures
Historical Context
| Date | Event | Sentiment | 24h Move | Catalyst |
|---|---|---|---|---|
| Aug 03 | Board nominations | Positive | +0.9% | Two technology industry veterans were nominated for election to Smartbird's board. |
| Jun 17 | CEO appointment | Positive | +39.1% | Nadia Carlsten became CEO as Smartbird advanced its AI infrastructure strategy. |
| Jun 15 | Dividend record date | Positive | +2.6% | Stockholders of record on June 25 became eligible for the asset sale dividend. |
| Apr 15 | AI financing facility | Positive | +582.3% | Smartbird executed a convertible financing facility to fund its AI infrastructure pivot. |
| Apr 07 | Product partnership | Positive | -2.7% | Allbirds launched a Canvas Cruiser collection through its Pantone partnership. |
24h Move is the share-price change in the day after each event; other market factors may also have contributed.
Historical reactions aligned with four of five recent announcements, while the April 7 partnership announcement diverged with a -2.7% reaction.
Key Terms
discontinued operations financial
inference technical
hyperscalers technical
convertible financing facility financial
ATM program financial
on-premises infrastructure technical
AI-generated analysis. How Rhea-AI works. Not financial advice.
PALO ALTO, Calif., Aug. 19, 2026 (GLOBE NEWSWIRE) -- Smartbird, Inc. (NASDAQ: BIRD), an AI infrastructure provider, has issued the following letter from Nadia Carlsten, CEO:
A New Beginning
Smartbird has a rare opportunity to build a new company at the start of a major infrastructure transition. Our origin is equally unusual: the company formerly known as Allbirds sold its footwear assets, changed its name, brought in new leadership and raised capital to go all in on AI infrastructure. This week we filed our Q2 2026 quarterly report, which includes the results of our discontinued operations of the retail business. This is a timely opportunity to address our shareholders and outline Smartbird's path forward.
Smartbird begins with advantages that most new companies spend years trying to assemble: capital, public market access, and the foundation of a global company. But these advantages are only a starting point: capital alone does not create customers, and a public listing does not create a moat. What matters is what we build with those advantages. I believe there is a significant gap emerging in the AI infrastructure market, and we are building Smartbird specifically to fill it.
The Next AI Infrastructure Wave
The first AI infrastructure boom was built for a small number of companies training frontier models. Their needs shaped infrastructure development: massive clusters backed by enormous capital commitments. Today, AI infrastructure spending, which is on track to surpass
But AI is moving beyond the companies building models and into the companies putting them to work. Having spent the last several years close to the buildout of computing infrastructure, I have seen firsthand how infrastructure needs change as AI moves from experimentation to production. Model training drove the first wave of demand. Increasingly, inference (AI running every day in products, workflows, and agents) is driving a different kind of demand. Enterprises that use little or no dedicated AI infrastructure today will need more of it, and their requirements will be different from those of the frontier labs the industry was initially built to serve.
That emerging shift is creating a second market for AI infrastructure. The last several years have been defined by the race to build the largest clusters for a small number of customers. I believe the next several years will be defined by bringing AI infrastructure to a much broader base of customers: the companies using AI rather than building it. That is the market we are choosing to serve.
The Gap We Fill
Enterprises should not have to choose between using standardized shared infrastructure and building bespoke compute systems themselves. For many workloads, shared cloud-based infrastructure will remain the sensible choice. But as AI becomes more strategic to the business, an increasing number of customers will need greater control over how and where their workloads run. They will need additional options, including dedicated and on-premises infrastructure designed around their specific requirements for performance, cost, security, and control.
That customer can take many forms: a pharmaceutical company running complex scientific simulations, a financial institution working with sensitive data, a government with data sovereignty requirements, an AI-native company that has outgrown a shared environment, or an enterprise watching the cost of its inference workloads climb as usage grows.
We want to enable those customers to focus on the products and services they are building with AI, not the foundational infrastructure. Smartbird provides dedicated infrastructure through a managed model: customers get infrastructure designed around their requirements, without having to build the expertise to operate it themselves. They tell us what they need AI to do; we design, procure, deploy, and operate the execution engine for them to build on. Dedicated infrastructure is not the answer for everyone and it does not need to be. But for organizations that need it, we are building Smartbird to be the managed infrastructure company they can rely on and grow with, so they don’t have to become infrastructure companies.
How Smartbird Wins
Hyperscalers win by standardizing infrastructure at enormous scale. But owning a lot of GPUs does not ensure a lasting advantage. Scale is not the only thing customers need.
We are choosing to compete where understanding the customer matters as much as scale. We want to serve organizations for whom AI infrastructure matters enough to think strategically about how it is designed, where it runs, and how much control they retain. For these customers, requirements that don’t fit neatly into a standardized infrastructure platform can be precisely what matters most. We are built to handle that complexity when it creates value for the customer.
That means starting with what the customer is trying to accomplish, not with how many GPUs they think they need. Whether we are supporting multi-agent systems or designing around specific enterprise requirements, understanding the workload allows us to build the right infrastructure around it. The more customers we serve, the more expertise we build. The more clusters we deploy, the more opportunities we have to improve our performance and economics. Those improvements, in turn, allow us to better serve existing customers and attract new ones. That is the flywheel we are building.
We are not tied to a single technology or provider, and we intend to adopt new, specialized technologies as they emerge. Over time, our durable advantage will come from the expertise we build as we deploy and operate that hardware against the real requirements of enterprise AI.
Building Smartbird with Discipline
The combination of cash and cash equivalents, a convertible financing facility and an ATM program, equip Smartbird with access to over
As Smartbird grows, we will share updates on key benchmarks to measure our progress. Early on, those will include the quality of customer demand, contracted and deployed capacity, and speed of deployment. We will prioritize creating value, not simply getting bigger.
Being right about the growth of AI will not make every infrastructure investment a good one. Technology will change, customer requirements will evolve, and we will face sophisticated competitors. We do not need to predict every change. We need to build Smartbird to adapt quickly, make disciplined investment decisions, and allocate capital accordingly.
Doing that requires exceptional people. We are building a small, technically deep and experienced team in AI infrastructure. We intend to preserve that talent density as we grow. We also recently announced the nomination of two industry experts for election to our board of directors at our next annual meeting of stockholders, adding experience that will help guide Smartbird as we build and scale.
Smartbird Principles
I believe how we build will matter as much as what we build. These principles reflect the company I want us to build and will guide how we operate:
- Customers before capacity. We build infrastructure to solve customer problems, not to make Smartbird look bigger.
- Technical depth over hype. Infrastructure does not care about a good story. It either works or it does not.
- Fundamentals over scale. Growth and scale matter, but neither matters if the underlying economics do not work.
- Complexity, where it creates value. Some of the most valuable enterprise challenges are complex. We embrace complexity when it solves problems that matter.
- Move fast, but don't break things. AI moves too fast for the pace of a traditional infrastructure company, but agility does not require sacrificing operational rigor.
- Build with the best. Exceptional builders, operators, and partners create enormous leverage when they work as one team.
- Build trust. We are candid about what works and what does not, and disciplined in how we deploy resources and build Smartbird.
The Work Ahead
The market opportunity is enormous. Smartbird is still at the beginning of its journey, but we have a clear playbook for how we intend to build. We serve enterprises for whom dedicated infrastructure solves a real, ongoing problem, execute their first deployments with rigor and precision, and cultivate those engagements into long-term relationships.
I am building Smartbird around a simple conviction: as AI moves from the companies building it to the much broader universe of companies putting it to work, infrastructure needs will change with it. We know who we want to serve and how we intend to serve them. Now we build, one customer, one deployment, and one investment decision at a time.
Sincerely,
Nadia Carlsten
CEO
Smartbird
Access the CEO letter on our website or as a PDF
Investor Contact:
Media Contact:
Press@smartbird.ai
