By Jia Lissa 
In a significant vote of confidence for the future of industrial and physical-world automation, San Francisco-based venture capital firm Base10 Partners has successfully closed two new funds totaling $850 million. The capital injection comprises a seed and Series A vehicle (Fund 4) and a dedicated Series B fund (Fund 2), signaling a robust commitment to a thesis that prioritizes the "real economy" over purely digital-native software plays.
As the venture landscape shifts from the speculative fervor of generalist AI toward specialized, outcome-oriented applications, Base10’s latest raise positions it as a critical bridge between cutting-edge technology and the tangible industries—such as logistics, construction, and manufacturing—that form the backbone of global economic output.
The Core Thesis: Democratizing High-End Capabilities
At the heart of Base10’s investment strategy is a vision articulated by co-founder Adeyemi Ajao: the democratization of sophisticated technical capabilities. Historically, the most advanced automation and operational efficiencies have been the exclusive domain of the top 1% of enterprises—those with the capital and engineering resources to build proprietary systems.
Base10’s mission is to export these capabilities to the remaining 99%. By investing in companies that streamline workflows in sectors like payroll, logistics, and construction, the firm aims to make enterprise-grade efficiency accessible to a broader swathe of the market.
This philosophy is reflected in their current portfolio, which includes high-growth, industry-transforming companies such as:
- Nubank: The Latin American neobank that revolutionized financial inclusion.
- Motive: A leader in fleet safety management and hardware-enabled software.
- WeTravel: An essential tool empowering travel agents with modern digital workflows.
- Happy Robot: A developer of enterprise-grade AI agents.
- Blank Street: A modern, tech-enabled coffee chain that optimizes the physical retail footprint.
Research-First Methodology: A Data-Driven Approach
Base10’s success is not merely a product of capital allocation; it is the result of a "research-first" discipline. Unlike firms that react to inbound deal flow, Base10 operates as an extension of the industries it serves. The team spends months performing deep-dive analyses into specific sectors before deploying a single dollar.
The "Base11" Internal Intelligence
To stay ahead in an increasingly crowded venture market, the firm has developed its own internal AI engine, dubbed "Base11." This system is utilized to classify emerging companies, scrape market data, and automate the initial stages of research. However, Ajao is quick to clarify that while AI assists in the processing of information, it does not replace the human element of venture capital.
"The actual decision-making and winning is more human than ever," Ajao noted. In an era where AI can provide the "what," the firm relies on its partners to discern the "why"—spending extensive time with founders and validating business models with real-world customers.
Strategic Selection
The firm’s rigorous process is best exemplified by their interaction with Y Combinator’s recent cohorts. Rather than meeting with the entire batch of 160 companies, Base10 filters through the noise to focus only on those that align perfectly with their current research themes. This informed approach allows the firm to reach investment conviction rapidly, a necessity in a high-competition environment where speed is often the differentiator.
The Next Frontier: Vision Models and Manufacturing Intelligence
Looking forward, Base10 is betting heavily on the evolution of AI beyond text-based Large Language Models (LLMs). The firm is actively exploring the potential of "world models" and "vision models"—systems capable of understanding and interpreting physical reality with the same fluidity that LLMs process language.
Understanding the Physical World
Ajao posits that if AI can achieve a granular understanding of every pixel and atom on a construction site, it will unlock a new era of robotics. This is the next frontier: moving from "understanding text" to "understanding operations."
The firm is similarly bullish on "manufacturing intelligence." The goal is to develop models that can interpret complex industrial processes—whether in pharmaceuticals, chip fabrication, or high-end chemical production—allowing for real-time optimization of processes that have historically been difficult to automate.
Chronology and Fund Structure
The $850 million capital raise is structured to provide flexible support across the entire lifecycle of a startup:
- Fund 4 (Seed and Series A): This vehicle is designed to maintain the firm’s early-stage roots. Base10 plans to execute 10 to 15 seed-stage investments and two to three Series A investments annually.
- Fund 2 (Series B): This fund is dedicated to scaling proven winners. The firm anticipates making three to four investments per year, focusing on companies that have established product-market fit and are ready for rapid expansion.
This layered structure ensures that Base10 remains involved with its portfolio companies through their most volatile growth phases, providing not just capital, but institutional guidance based on their deep industry research.
Implications for the Venture Ecosystem
The successful close of these funds carries several implications for the broader venture capital market.
Heightened Competition for Quality
As Ajao observed, competition among venture firms has reached an all-time high. Founders now have more choices than ever, which forces firms to articulate their value proposition more clearly. For Base10, this means leaning into their reputation as a research-heavy partner that provides deep industry insights rather than just a check.
The Return of the "Real Economy"
For several years, the venture world was dominated by consumer-facing apps and SaaS platforms. Base10’s shift toward "real economy" sectors like construction, logistics, and payroll signals a broader pivot in the industry. As software eats the world, the next generation of value creation is expected to come from digitizing the sectors that have traditionally been the slowest to adopt new technology.
Philanthropic Integration
A defining feature of Base10’s operation remains the "Advancement Initiative." Recognizing the systemic barriers in the financial industry, the firm donates up to 50% of its carried interest to underfunded colleges and universities. This provides a sustainable model for supporting financial aid and diversifying the next generation of talent in technology and finance.
Official Perspective: Human-Centric Capital
Despite the firm’s reliance on its internal "Base11" system, Ajao maintains a pragmatic view on the limits of technology in finance. He emphasizes that the "winning" of deals—establishing trust with a founder, understanding the nuances of a founder’s leadership style, and verifying a company’s long-term viability—is fundamentally a human pursuit.
"We spend roughly 50% of our time with companies that are not fundraising," Ajao stated. This long-term relationship-building is how the firm maintains its edge, ensuring that when the time comes to deploy capital, they are doing so with a level of insight that competitors—even those using similar AI tools—cannot match.
Conclusion: A Blueprint for the Future
Base10 Partners has carved out a unique niche by blending high-tech internal research with a traditional, hands-on approach to venture capital. By focusing on the "real economy" and maintaining a disciplined, research-led investment strategy, the firm is well-positioned to navigate the complexities of the current economic environment.
As they move forward with their $850 million war chest, the industry will be watching to see how their focus on vision models and manufacturing intelligence shapes the next wave of industrial automation. In an ecosystem often criticized for its focus on the ephemeral, Base10’s commitment to the tangible, physical world provides a compelling blueprint for the future of venture capital.
Ammar Sabilarrohman 
Reynand Wu 
Dwi Wanna