Artificial Intelligence

Algorized Raises US$13M to Advance Real-Time Safety Intelligence for Human-Robot Collaboration

A new safety layer aims to help robots sense people in real time without slowing production

Updated

February 13, 2026 10:44 AM

An industrial robot in a factory. PHOTO: UNSPLASH

Algorized has raised US$13 million in a Series A round to advance its AI-powered safety and sensing technology for factories and warehouses. The California- and Switzerland-based robotics startup says the funding will help expand a system designed to transform how robots interact with people. The round was led by Run Ventures, with participation from the Amazon Industrial Innovation Fund and Acrobator Ventures, alongside continued backing from existing investors.

At its core, Algorized is building what it calls an intelligence layer for “physical AI” — industrial robots and autonomous machines that function in real-world settings such as factories and warehouses. While generative AI has transformed software and digital workflows, bringing AI into physical environments presents a different challenge. In these settings, machines must not only complete tasks efficiently but also move safely around human workers.

This is where a clear gap exists. Today, most industrial robots rely on camera-based monitoring systems or predefined safety zones. For instance, when a worker steps into a marked area near a robotic arm, the system is programmed to slow down or stop the machine completely. This approach reduces the risk of accidents. However, it also means production lines can pause frequently, even when there is no immediate danger. In high-speed manufacturing environments, those repeated slowdowns can add up to significant productivity losses.

Algorized’s technology is designed to reduce that trade-off between safety and efficiency. Instead of relying solely on cameras, the company utilizes wireless signals — including Ultra-Wideband (UWB), mmWave, and Wi-Fi — to detect movement and human presence. By analysing small changes in these radio signals, the system can detect motion and breathing patterns in a space. This helps machines determine where people are and how they are moving, even in conditions where cameras may struggle, such as poor lighting, dust or visual obstruction.

Importantly, this data is processed locally at the facility itself — not sent to a remote cloud server for analysis. In practical terms, this means decisions are made on-site, within milliseconds. Reducing this delay, or latency, allows robots to adjust their movements immediately instead of defaulting to a full stop. The aim is to create machines that can respond smoothly and continuously, rather than reacting in a binary stop-or-go manner.

With the new funding, Algorized plans to scale commercial deployments of its platform, known as the Predictive Safety Engine. The company will also invest in refining its intent-recognition models, which are designed to anticipate how humans are likely to move within a workspace. In parallel, it intends to expand its engineering and support teams across Europe and the United States. These efforts build on earlier public demonstrations and ongoing collaborations with manufacturing partners, particularly in the automotive and industrial sectors.

For investors, the appeal goes beyond safety compliance. As factories become more automated, even small improvements in uptime and workflow continuity can translate into meaningful financial gains. Because Algorized’s system works with existing wireless infrastructure, manufacturers may be able to upgrade machine awareness without overhauling their entire hardware setup.

More broadly, the company is addressing a structural limitation in industrial automation. Robotics has advanced rapidly in precision and power, yet human-robot collaboration is still governed by rigid safety systems that prioritise stopping over adapting. By combining wireless sensing with edge-based AI models, Algorized is attempting to give machines a more continuous awareness of their surroundings from the start.

Keep Reading

Strategy & Leadership

Why Nostalgia Marketing Works for Your Startup

How startups can use nostalgia marketing to build trust, spark loyalty and stand out with storytelling, vintage design and emotional connections.

Updated

January 8, 2026 6:35 PM

Vintage beer pong posters showcasing colorful, diverse designs from different eras in one collection.

Vintage beer pong posters showcasing colorful, diverse designs from different eras in one collection. PHOTO: FREEPIK

Turning the subtle power of nostalgia into meaningful marketing.

Think of nostalgia as a time machine for brands—it doesn’t just take people back; it brings their emotions forward. And emotions sell. For those who are unfamiliar, nostalgia marketing is a strategy where brands use elements from the past—like familiar sights, sounds, or stories—to evoke warm memories and emotional connections with their audience.

This emotional pull isn’t just anecdotal—research shows its real impact: according to The Team and Forbes via The Drum, 80% of millennials and Gen Z are drawn to brands tapping into nostalgia, while 92% of consumers say nostalgic ads feel more relatable. And for startups competing in noisy markets, this is a goldmine.

In this article, we’ll explore why nostalgia marketing can be a game-changing strategy for your company.

Inside the brain: how nostalgia turns memories into purchases

Out of all the popular marketing methods—like influencer partnerships or attention-grabbing ad campaigns—nostalgia is unique because its impact starts intrinsically, in the brain. By triggering the release of dopamine, a reward-system neurotransmitter, Nostalgia evokes feelings of warmth, happiness and comfort. Consequently, people don’t just remember a moment—they relive it. Take, for instance, your favorite cereal brand bringing back childhood cartoon characters or using retro fonts and colors. You might choose it over a healthier breakfast option simply because it reminds you of the mornings you enjoyed as a kid. Similarly, speaking of stirring fond memories, Coca-Cola has mastered this effect, using classic holiday ads, vintage packaging, and iconic imagery. Those associations make people see Coke as more than a drink—it’s a familiar feeling they’re willing to pay extra for.

Nostalgia builds trust: how familiarity strengthens brand loyalty

New marketing campaigns can spark curiosity but often trigger skepticism—especially when audiences lack prior connection to the brand. Nostalgia marketing breaks down this barrier by tapping into familiarity, using retro jingles, vintage fonts, pastel colors, or familiar packaging that immediately resonate. This recognition builds an emotional connection and trust with the brand. More importantly, it fosters social connectedness by making consumers feel part of a larger community—giving that reassuring “others remember this too” feeling. As a result, this sense of belonging reduces loneliness, strengthens warmth and trust, and encourages word-of-mouth sharing, naturally amplifying the campaign’s reach and impact.

Nostalgia in storytelling: turning memories into marketing wins

While luxury brands can afford massive campaigns, startups and small businesses can tap into nostalgia as a cost-effective storytelling tool. In a world where marketing often chases the “next big thing”—from AI to futuristic tech—nostalgia offers the opposite: a chance to revisit the past. More importantly, nostalgia allows brands to stand out in a crowded, fast-scrolling feed by delivering something comfortingly familiar with a fresh twist. Think of Polaroid: in an age where smartphones boast crystal-clear cameras, it wins hearts with pastel hues, a vintage lens, and the tactile charm of instant prints—selling not just images, but a moment that feels straight out of the past.

The same principle worked brilliantly for Tiffany & Co., whose 185-year-old brand refresh featured Jay-Z and Beyoncé in a Breakfast at Tiffany’s-inspired campaign, blending timeless charm with contemporary star power and racking up millions of views. In essence, when done right, nostalgia doesn’t just market a product—it invites people to relive a story they already love.

Nostalgia’s cross-generational appeal: connecting generations

Nostalgia resonates across generations speaking to diverse audiences.  For Millennials, it’s a chance to relive the cultural touchpoints of their youth, while Gen Z approaches it with curiosity, eager to explore eras they never experienced firsthand. This crossover creates a unique marketing sweet spot: one group is driven by memory, the other by discovery. Pokémon proves this power by keeping lifelong fans engaged through retro trading cards while introducing younger audiences to its history. Similarly, Nike used nostalgia to bridge two different generations by reissuing retro classics, keeping both longtime fans and new sneakerheads excited. By appealing to both memory and curiosity, brands can create lasting connections that keep different generations engaged at once.

Final thoughts: making nostalgia work for your startup

Nostalgia can be your startup’s non-cliché marketing mantra. Imagine a small bookstore that offers handwritten recommendation cards designed like vintage library checkout slips. This simple touch invites customers to slow down and rediscover the joy of reading. Or picture a local coffee shop serving drinks in mugs inspired by classic diner ware, evoking comforting memories of simpler times. Overall, the lesson is clear: combining nostalgic design with stories that connect people to shared moments creates emotional warmth and trust. Thoughtful nostalgia turns everyday products into meaningful experiences—building loyal communities eager to return.