Investors Shift Focus to AI Efficiency and Economics

Building the AI Backbone

Several of the largest raises centered on the technical foundations required to make AI systems faster, cheaper and more trustworthy at scale.

Positron AI announced it raised $230 million in a Series B round at a valuation of more than $1 billion to scale energy-efficient AI inference. The company is positioning itself as an alternative to power-hungry data center accelerators, with its Atlas inference system already shipping and a next-generation chip, Asimov, planned for a late-2026 final design. Investors include Jump Trading, Arena Private Wealth and Qatar Investment Authority, highlighting demand for hardware that prioritizes memory bandwidth and lower operating costs as inference workloads surge.

Research firm Goodfire has secured $150 million in Series B funding at a $1.25 billion valuation to advance interpretability-first AI development. The company focuses on tools that allow researchers and developers to understand, debug and steer model behavior rather than treating AI systems as opaque black boxes. Backers, including B Capital, Lightspeed, Salesforce Ventures and Eric Schmidt, are betting that transparency and controllability will become competitive necessities as AI expands into regulated and high-stakes environments.

On the data infrastructure side, Tomorrow.io announced $175 million in financing to deploy DeepSky, which it describes as the world’s first AI-native weather satellite constellation. The funding will accelerate the launch of additional low Earth orbit satellites designed specifically to feed artificial intelligence forecasting models with higher-frequency atmospheric data. Tomorrow.io says it serves enterprise customers in aviation, logistics and energy, and is positioning weather intelligence as mission-critical infrastructure rather than a standalone forecasting service.

AI Moves Into Core Business Operations

Another cluster of deals highlights how AI is being embedded directly into enterprise workflows, particularly in finance, accounting and day-to-day knowledge work.

Accrual launched with $75 million in funding to build AI-native automation for accounting teams. The platform aims to automate reconciliation, transaction categorization and reporting using large language models trained on financial workflows. The company is targeting mid-sized enterprises facing talent shortages and growing compliance demands, positioning automation to maintain accuracy while reducing manual workload.

Daytona has raised $24 million in Series A financing to give “every agent a computer.” The startup focuses on augmenting customer support and sales agents with AI-powered digital workspaces that can execute tasks, retrieve information and coordinate across systems. The pitch reflects a broader shift away from static dashboards toward agent-centric interfaces where AI acts as an operational co-pilot rather than a separate tool.

Vertical Intelligence Tackles Cost and Complexity

AI funding is also flowing toward companies applying machine intelligence to complex, data-heavy industries where inefficiency is expensive and persistent.

Alaffia Health announced it raised $55 million to reduce waste in the U.S. healthcare industry, saying such waste amounts to as much as $570 billion annually. Its platform uses artificial intelligence to surface real-time insights into unnecessary procedures, billing inefficiencies and administrative friction. The company plans to expand product development and sales as payers and providers face mounting pressure to control costs without degrading care quality.

In logistics, GenLogs closed a $60 million Series B round to scale its AI-powered trucking intelligence platform. GenLogs combines live fleet telematics with predictive analytics to optimize routing, compliance and performance across trucking operations. The fundraise reflects interest in applying AI to freight and supply chain management as carriers navigate fuel costs, labor constraints and tighter margins.