Haladir, a San Francisco-based artificial intelligence startup developing operational decision-making software for logistics and supply chain organizations, has raised $4.3 million in seed funding to accelerate the development of its “operational superintelligence” platform. The seed round was led by BoxGroup and Susa Ventures, with participation from Sunflower Capital, Valkyrie Ventures, XPRESS Ventures, as well as angel investors. The company also acknowledged prior backing from Y Combinator and SV Angel, while entrepreneur Josh Browder was recognized as the company’s first believer and early supporter through his investment firm, Browder Capital.

Founded in 2025, Haladir is building an AI platform designed to help logistics operators make complex operational decisions using a combination of large language models, operations research, optimization algorithms, forecasting, and formal constraint-solving techniques. Rather than relying solely on generative AI to recommend actions, the company integrates deterministic optimization models with machine learning to produce decisions that satisfy real-world operational constraints across transportation, warehousing, and supply chain networks.

The startup’s technology sits on top of enterprise software commonly used throughout the logistics industry, including warehouse management systems, transportation management systems, order management systems, enterprise resource planning platforms, labor management systems, and electronic data interchange infrastructure. Haladir unifies data from these previously disconnected systems into what it describes as an operational graph, allowing artificial intelligence models and optimization engines to reason over structured operational data rather than isolated datasets.

According to the company, logistics organizations often possess enormous amounts of operational data but struggle to convert that information into reliable decisions because business rules, operational constraints, and optimization objectives are difficult to encode within conventional AI systems. Haladir addresses this challenge by combining formal mathematical optimization with AI models capable of translating human language into machine-readable constraints. The result is intended to automate decisions involving routing, inventory planning, labor scheduling, demand forecasting, warehouse optimization, and other operational workflows.

The newly announced financing will support continued product development as the company expands its work with third-party logistics providers, distributors, and frontier AI laboratories. Haladir also plans to invest in reinforcement learning environments and specialized training data that enable AI systems to better understand constrained decision-making scenarios common in industrial operations. By integrating solver-based optimization with modern AI architectures, the company believes it can improve the reliability of autonomous decision-making across highly regulated and operationally complex industries.

The founding team includes CEO Jibran Hutchins alongside co-founders Quan Huynh, Preston Schmittou, and Joseph Tso. Before launching Haladir, the founders conducted research in operations research and machine learning while studying at institutions including Carnegie Mellon University, Princeton University, and the University of Virginia. The company participated in Y Combinator’s Winter 2026 accelerator program, where it refined its technology and expanded relationships within the startup ecosystem before raising its seed financing.

Haladir describes its long-term vision as building an operational intelligence layer capable of supporting every major decision inside logistics organizations. Instead of replacing existing enterprise software, the platform is designed to integrate with customers’ technology stacks while providing optimization and reasoning capabilities that improve decision quality. The company argues that AI systems become significantly more useful when they operate within mathematically verified constraints rather than generating probabilistic recommendations without operational guarantees.

Investor interest in companies combining artificial intelligence with industrial operations has continued to grow as enterprises seek technologies that deliver measurable productivity gains instead of general-purpose automation. Logistics and supply chain operations represent particularly attractive applications because they involve structured data, repeatable workflows, and optimization problems that directly affect cost, efficiency, and customer service. Haladir’s approach of merging operations research with large language models positions it within a growing category of enterprise AI companies focused on augmenting decision-making rather than simply generating content.

With fresh capital and support from a group of venture firms experienced in backing early-stage enterprise software companies, Haladir plans to expand its engineering team, deepen integrations with logistics platforms, and continue developing AI systems capable of making verifiable operational decisions. As organizations increasingly look beyond traditional analytics toward autonomous optimization, the company aims to establish its technology as a foundational intelligence layer for modern supply chain operations while advancing its broader vision of operational superintelligence.

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