Senra Systems has successfully raised $65 million in a Series B funding round. These funds will be used to scale its software-driven manufacturing platform designed for wire harness production. The investment will allow the company to open a third production facility, which is necessary to meet growing demand from the aerospace and defense industries.
The funding round was co-led by Lowercarbon Capital and Interlagos. General Catalyst, Sequoia Capital, Andreessen Horowitz, Founders Fund, 8VC, CIV, Dylan Field, The Friedkin Group, Jaws Estates Capital, Sozo Ventures, and Alumni Ventures also participated.
CEO and co-founder Jordan Black noted that wire harnesses remain one of the most undervalued bottlenecks in manufacturing for the aerospace and defense industry, despite being critical components in advanced aircraft, satellites, launch vehicles, and defense systems.
Senra produces complex wire harness systems that provide power, communication, and data distribution across all aerospace and defense platforms. Their platform helps reduce manual operations, accelerates adaptation, and increases production stability.
The company's manufacturing operations are based on Amp—Senra's proprietary software platform. This system integrates engineering, calculations, supply chain management, production planning, and manufacturing workflows into a single digital environment.
Earlier this year, Senra opened its second manufacturing site in Cypress, which increased its production base fivefold. This 80,000 square foot facility is expected to help the company increase its monthly production capacity from approximately 1,000 wire harnesses to around 10,000 by next year.
The demand for wire harnesses has significantly increased amid rising government investments in aerospace and defense programs. Nevertheless, the industry continues to face labor shortages and production constraints. Senra aims to solve these issues by combining software automation with structured personnel training programs. The company is creating an integrated manufacturing solution capable of supporting the aerospace, defense, energy, and computing sectors.
Lowercarbon Capital General Partner Kai Lee stated that wire harnesses form the basis of virtually every advanced electronic platform, making manufacturing automation vital for expanding industrial potential.
The company has strengthened its leadership team by appointing Ken Wenner as Chief Technology and Product Officer. Wenner previously served as Director of Information Technology at SpaceX, where he oversaw corporate systems and the development of manufacturing infrastructure. He managed technologies supporting SpaceX's production operations and launch infrastructure across numerous advanced aerospace programs.
At Senra, Wenner will be responsible for the company's manufacturing platform, operating systems, and long-term technology roadmap. He will guide the technological strategy during the company's preparation for the next phase of business expansion. The company believes that software, automation, and workforce development will strengthen domestic manufacturing capabilities in critical industries.
Databento has successfully closed a Series B funding round, raising $97 million. This capital is designated for expanding the company's market data infrastructure platform. The round was oversubscribed by $300 million and led by the investment firm New Enterprise Associates (NEA).
In addition to existing and strategic investors such as DRW Venture Capital, Redpoint Ventures, and Tribe Capital, there was significant institutional interest in Databento. The company provides access to historical and current market data through a unified API.
The traditional process of obtaining financial data often involves lengthy months of legal approvals, technical integration, and high initial costs. Databento solves this problem by offering a developer-friendly solution based on a pay-as-you-go model.
Christina Qi, one of the founders and CEO, started Databento to eliminate these costs. Prior to this, Qi worked at the hedge fund Domeyard LP, which processed billions of dollars daily. Her experience in quantitative trading shaped the platform's architecture, allowing users to receive institutional-grade data within minutes on demand. This usage-based model removes significant capital constraints that typically hinder small firms and independent researchers.
The new capital will be directed towards globally scaling the company's data infrastructure. Databento places its hardware servers in major global exchanges for direct collection of raw data. Following this round, the company plans to increase its presence to over 20 data centers worldwide and add 100 petabytes of disk space.
A significant part of this growth is related to digital assets. Databento currently provides data on cryptocurrency futures from CME and CFE. The platform also offers packet capture level data for crypto derivatives. With the Series B funds, Databento is integrating spot, futures, and options data from Binance, thereby unifying traditional finance and the decentralized crypto ecosystem within a single API.
Despite the saturation of the venture capital market, Databento demonstrates a high level of demand. The fintech startup is profitable with a staff of only 24 employees and has recently significantly increased its number of active API users. The company's annual revenue has grown 6.65 times, and the corporate client retention rate since launch stands at 97%. As a result of this investment, NEA partners Rick Yang and Danielle Lay will join Databento's board of directors.
The company serves over 3,000 firms globally, supporting complex trading desks with volumes measured in trillions of dollars. Databento also transforms automated workflow construction methods by collaborating with open-source tools like NautilusTrader. This allows quantitative researchers to build hybrid systems to monitor both traditional and crypto markets. The platform is developer-centric and owns the entire data stack from end to end without sacrificing speed. Trading desks no longer need to maintain extensive internal data pipelines for testing and deploying complex algorithms.
