Gather AI, Maker Of ‘Curious’ Warehouse Drones, Lands $40M Led By Keith Block’s Firm

Gather AI Raises $40M for Curious Warehouse Drones That Think Like Humans

Gather AI has secured $40 million in Series B funding to expand its artificial intelligence platform that deploys autonomous drones and cameras inside warehouses. Unlike traditional monitoring systems that follow preset routes, Gather's technology uses "curiosity-driven" AI to independently identify operational anomalies, inventory discrepancies, and safety hazards—without human direction. The round was led by Smith Point Capital, the venture firm founded by former Salesforce co-CEO Keith Block, signaling strong enterprise confidence in AI's next frontier: physical-world autonomy.

Credit: Gather AI

From Carnegie Mellon Helicopters to Warehouse Intelligence

The journey began not in a warehouse, but on FBI training grounds in Quantico, Virginia. Three PhD students from Carnegie Mellon University—Sankalp Arora and his co-founders—were testing one of the world's first fully autonomous helicopters. Their research focused on a deceptively complex challenge: teaching machines to navigate unpredictable environments while making real-time decisions about where to look and what matters.

That foundational work in spatial reasoning and adaptive perception became the blueprint for Gather AI. Launched in 2017, the startup pivoted from aerial vehicles to industrial logistics, recognizing warehouses as ideal environments for curiosity-driven AI. These spaces are structured yet dynamic—filled with moving inventory, shifting workflows, and constant human activity—making them perfect training grounds for machines that learn by exploring.

What "Curious" AI Actually Means in Practice

Most warehouse automation systems operate on rigid programming. Drones fly predetermined paths. Cameras monitor fixed zones. Alerts trigger only when predefined thresholds are breached. Gather AI flips this model entirely.

Its platform deploys off-the-shelf drones and strategically mounted cameras on equipment like forklifts. But instead of executing scripted routines, the AI continuously asks itself questions: Why did that pallet move unexpectedly? Why is this aisle unusually congested? Why hasn't this high-value item been scanned in 48 hours? This intrinsic motivation to seek novelty and resolve uncertainty—what researchers call "artificial curiosity"—allows the system to detect issues humans might overlook.

When the AI identifies something noteworthy, it logs findings directly into existing warehouse management systems. No manual review required. A mislabeled shipment, a blocked fire exit, or inventory sitting idle beyond optimal turnover windows—all get flagged automatically with contextual evidence.

Why Enterprise Investors See Strategic Value

Keith Block's firm leading this round carries symbolic weight beyond capital. Block, a former co-CEO of one of enterprise software's most successful companies, now chairs a venture fund with deep logistics and supply chain expertise. His rapid buy-in—reportedly understanding Gather's value proposition within five minutes of initial conversation—reflects how clearly the technology solves acute industry pain points.

Modern warehouses face a perfect storm of challenges: labor shortages, rising e-commerce fulfillment demands, and razor-thin margins where small inefficiencies compound into major losses. Traditional monitoring requires expensive custom hardware and teams of analysts reviewing footage. Gather's approach leverages existing infrastructure while delivering proactive insights—a rare combination of affordability and intelligence that resonates with operations leaders.

The Quiet Revolution in Physical AI

While much of the AI conversation centers on language models and digital assistants, a parallel revolution is unfolding in physical spaces. Gather AI represents a maturation point for embodied AI—systems that perceive, reason, and act within the real world. The warehouse becomes a proving ground because its stakes are high enough to justify innovation but structured enough to manage risk.

This "curiosity" isn't random wandering. It's mathematically optimized exploration grounded in reinforcement learning. The AI receives implicit rewards for discovering novel patterns or resolving uncertainties—similar to how humans feel satisfaction from solving puzzles. Over time, it learns which areas of a facility generate the most valuable insights and adjusts its attention accordingly. One distribution center using Gather reported a 37% reduction in misplaced inventory within three months, not because drones flew more routes, but because they learned where to look.

Real-World Impact Beyond Inventory Counts

Early adopters are discovering secondary benefits that extend beyond the platform's core promise. Safety teams receive automatic alerts when drones detect unsecured ladders or pedestrians entering forklift zones. Sustainability officers track energy waste by identifying lights left on in unoccupied sections overnight. Even maintenance departments benefit as cameras spot hydraulic fluid leaks or equipment wear before failures occur.

These emergent use cases highlight a key advantage of curiosity-driven systems: they uncover value humans didn't explicitly program them to find. In an industry where operational excellence often depends on noticing subtle deviations, this adaptive awareness becomes a strategic asset rather than just a monitoring tool.

Scaling Responsibly in a Skeptical Market

Despite the promise, warehouse operators remain rightly cautious about autonomous systems. Safety concerns, integration complexity, and ROI uncertainty have slowed adoption of previous generations of robotics. Gather's founders acknowledge this skepticism shaped their go-to-market strategy.

Rather than selling expensive proprietary hardware, they built their platform to work with commodity drones and existing camera networks. Integration focuses on APIs that feed insights into systems warehouses already use—no rip-and-replace required. And crucially, the AI operates during off-hours initially, building trust by demonstrating value without disrupting live operations. Only after proving reliability do facilities transition to 24/7 autonomous monitoring.

This pragmatic approach has accelerated enterprise adoption. The new funding will expand Gather's deployment team and enhance its computer vision models to recognize increasingly nuanced scenarios—from identifying damaged packaging to detecting subtle shifts in workflow efficiency.

From Warehouses to Broader Industrial Applications

While warehouses provide the ideal initial environment, Gather's underlying technology has broader implications. The same curiosity-driven framework could monitor construction sites for safety compliance, patrol agricultural fields for irrigation issues, or inspect manufacturing plants for quality control deviations.

Arora hints that the company is already exploring adjacent verticals where structured environments meet high operational stakes. But for now, the focus remains on perfecting the warehouse experience—proving that AI's greatest near-term value may not be in generating text or code, but in quietly observing our physical world with intelligent attention.

Why This Funding Moment Matters

The $40 million infusion arrives as supply chain resilience has become a boardroom priority. Companies can no longer treat warehouses as cost centers to be minimized—they're strategic assets where visibility equals competitive advantage. Gather AI's timing aligns with a fundamental shift: logistics leaders now seek technologies that don't just automate tasks, but generate operational intelligence.

This isn't about replacing workers with robots. It's about augmenting human teams with tireless, perceptive partners that notice what we miss. In an era where a single misplaced pallet can delay thousands of customer orders, that perceptual edge transforms from novelty to necessity. As Gather scales its curious machines across global distribution networks, it may well redefine what "smart infrastructure" truly means—not connectivity alone, but contextual awareness that acts before problems escalate.

The future of warehouse intelligence won't be found in more cameras or faster drones. It will emerge from systems that don't just see, but seek to understand—asking the right questions before anyone thinks to ask them. That's the promise Gather AI is now positioned to deliver at scale.