A new project in Spain shows how digital twins, which are virtual replicas of real environments, are becoming powerful tools for protecting ecosystems. Fujitsu and the BCN Port Innovation Foundation have announced a proof of concept to create an ocean digital twin at the Port of Barcelona. (Will they use Mirai robots at sea?)

The initiative will use underwater drones, artificial intelligence and advanced analytics to generate detailed digital models of the seabed and marine life. The goal is to support “the regeneration of the marine environment, the protection of biodiversity and the promotion of the blue economy.” Using non-destructive sensing, the system will visualize biodiversity, estimate vegetation coverage and calculate blue carbon stored in marine algae.

Digital twins work by collecting real-world data through sensors, drones or satellites and feeding it into a digital model that mirrors the real ecosystem. In Barcelona, autonomous vehicles will map the seabed while machine-learning systems translate the information into measurable indicators. According to the project description, “Machine learning models convert this data into quantitative environmental intelligence, estimating vegetation coverage, assessing habitat extent, and calculating blue carbon absorption.”

One powerful feature of digital twins is the ability to test future scenarios before action is taken. The platform developed by Fujitsu will allow environmental simulations to evaluate policy or infrastructure impacts. The system “enables the simulation of ‘what if’ scenarios, helping pre-verification of environmental measures before they are implemented to prioritize investments based on their real impact.”

Ángeles Delgado, president of Fujitsu Spain and Portugal, says the approach turns complex marine data into practical insight: “This project demonstrates how technology can become a true ally of sustainability. The ocean digital twin allows us to transform complex data from the marine environment into actionable information to protect biodiversity, promote blue carbon initiatives, and make evidence-based decisions.”

Ocean twins are part of a broader trend using digital replicas to manage environmental systems. Cities are building urban digital twins to model climate impacts, researchers are creating forest twins to track carbon storage and wildfire risk, and global projects such as Europe’s Destination Earth climate twin aim to simulate the entire planet to improve climate forecasting and environmental planning.

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Did China sever undersea communications cables yet again? Are ships hauling crude oil leaking their cargo along the way? Are animal transport ships dumping feed bags overboard and causing unseen turtle and wildlife deaths? Are port authorities deliberately destroying underwater archaeology so projects can move ahead?

Getting away with bad business at sea may soon be harder with Mirai Robotics on patrol.

While security is a giant concern, Luciano Belviso, Mirai’s co-founder told Green Prophet: “Mirai’s autonomy can also support environmental monitoring, enabling continuous observation of marine ecosystems, pollution, and offshore infrastructure with persistent, autonomous operations, regardless of weather conditions.”

The company just raised $4.2 million in a seed round to continue development of its AI-driven autonomous marine vehicles. According to the company, the sea is one of the most critical infrastructures on the planet: more than 80% of global trade moves by sea, over 90% of Europe’s foreign trade depends on maritime routes, and roughly 95% of international internet traffic flows through subsea cables.

“The sea is one of the last major physical infrastructures not yet governed by software,” says Luciano Belviso, CEO of Mirai Robotics. “Autonomy is the key to finally making the oceans safe and usable, unlocking enormous resources and addressing critical security challenges. But it must be implemented through systems capable of operating continuously and safely in extreme environments. This is a technological and industrial challenge that requires a true robotics-lab approach.”

Mirai Robotics has already developed two autonomous vehicles designed for different operational needs, targeting ISR (intelligence, surveillance and reconnaissance) and patrolling scenarios in both coastal and offshore environments.

The vehicles integrate advanced perception systems, autonomous navigation, remote control, and safety features. They are designed to operate either as standalone units or as part of distributed monitoring systems.

Alongside its proprietary platforms, Mirai Robotics also develops autonomy, navigation, and control systems that can be integrated into third-party vessels. This allows industrial and institutional operators to adopt autonomous technology without fully redesigning existing fleets.

The decision to start in Italy is deliberate. The country is historically a global leader in shipbuilding and maritime engineering, with strong expertise in defense, yachting, offshore infrastructure, and marine technology.

The company was founded by Luciano Belviso (CEO), Luca Mascaro, and Davide Dattoli. Belviso previously built and led complex industrial companies including Blackshape, an aircraft design and manufacturing company later acquired by Angel Holding.

Luciano Belviso (left) and Luca Mascaro (right). Supplied by Mirai

Mirai Robotics has closed a $4.2 million pre-seed equity round, one of the largest in Italy in the robotics and deep-tech sector, led by Primo Capital, Techshop and 40Jemz Ventures, with participation from Italian and international angel investors. The capital will accelerate technology development, strengthen the team, and launch new pilot projects with industrial and institutional partners.

We love that the company can catch polluters in real time and take risks to rescue those at sea where other seafarers may not dare or have the expertise.

Mirai (未来) is a Japanese word that means “future.”

They aren’t alone. Mirai Robotics enters a rapidly growing field of autonomous maritime technology that can support defense and environmental missions. Competitors include firms such as Maritime Robotics, Saildrone, whose wind- and solar-powered robotic vessels collect environmental and security data across vast ocean areas. Defense and dual-use companies like L3Harris Technologies and Thales Group are also developing autonomous patrol boats and surveillance platforms for naval and infrastructure protection. In Europe, look to startups such as Ocean Infinity and Sea Machines Robotics.

::Mirai

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I am with Elon Musk and his dream to move to Mars. I have always had a feeling that we’re not alone.

For decades, scientists searching for extraterrestrial intelligence have focused on one specific type of radio signal, extremely narrow spikes in frequency. These “narrowband” signals are considered strong candidates for technological transmissions because natural astrophysical processes rarely produce them. However, new research from the alien-hunting organization, the SETI Institute, suggests alien signals might be harder to detect than previously thought, not because they do not exist, but because they may become distorted before leaving their home star systems.

The study, published in The Astrophysical Journal, explores how stellar “space weather” could blur radio transmissions from distant civilizations. Turbulent plasma near stars, including charged particles carried by stellar winds and eruptions such as coronal mass ejections, can interfere with radio waves as they travel outward from a transmitting planet. Even if a civilization sends a perfectly narrow signal, the plasma surrounding its star could spread the signal’s energy across a wider range of frequencies.

This process weakens the signal’s peak strength and makes it more difficult for traditional SETI detection systems to identify. Many current search pipelines are optimized to detect ultra-sharp signals, meaning broadened transmissions could slip below detection thresholds.

“SETI searches are often optimized for extremely narrow signals,” said Dr. Vishal Gajjar, astronomer at the SETI Institute and lead author of the study. “If a signal gets broadened by its own star’s environment, it can slip below our detection thresholds, even if it’s there, potentially helping explain some of the radio silence we’ve seen in technosignature searches.”

To understand how strong this effect might be, researchers studied radio transmissions from spacecraft within our own solar system. By measuring how solar plasma affects these signals, the team developed models that estimate how stellar turbulence might distort transmissions in other planetary systems.

Their findings suggest the effect could be particularly strong around M-dwarf stars, small and active stars that make up roughly 75% of the Milky Way’s stellar population. Because these stars often produce intense stellar activity, signals from planets orbiting them could become significantly broadened before escaping the system.

The research suggests future SETI searches may need to expand their approach, developing detection systems capable of identifying signals that have been smeared or broadened by stellar environments, not just perfectly narrow ones. By accounting for how stellar activity reshapes radio transmissions, scientists hope to design searches that are better matched to what actually arrives at Earth, potentially revealing signals that have so far remained hidden.

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When I first studied forestry at the University of Toronto with Professor Sandy Smith, I didn’t realize how deeply the school’s ecological roots would shape the way I look at the world. The University of Toronto has always been, at its core, an environmental university. from its forestry program and plant biology labs to courses in sustainable cities.

So it’s not surprising that one of Canada’s emerging cleantech companies tackling plastic pollution also began there. Meet erthos, a Toronto-area startup developing plant-based materials designed to replace traditional petroleum plastics and help move the global economy toward a circular model.

The company began as a student project at the University of Toronto, where the founders started exploring alternatives to plastic while studying subjects ranging from environmental economics to plant biology. Their early work focused on whether agricultural byproducts and plant-derived ingredients could replicate the performance of conventional plastics, without leaving behind the same environmental legacy.

What began as a campus sustainability idea has since grown into a cleantech company that uses AI to design bio-based resins that can replace common plastics such as polypropylene or polystyrene, while still working within existing manufacturing systems. One of their recent talks was with Colgate-Palmolive.

That compatibility with industry matters. One of the biggest barriers to replacing plastics is the massive infrastructure already built around them. Factories, molds, and production lines are designed for petroleum-based materials. If a sustainable material requires entirely new manufacturing systems, adoption slows dramatically. We see that working with big brands isn’t enough. The pineapple textiles and leather company Pinatex, which uses pineapple waste, emerged to great fanfare and worked with brands like Stella McCartney, but one-off and non-committal marketing opportunity can’t build a business. We need more commitment and responsibility taken by brands such as Colgate-Palmolive, H&M, and all ranges of food and plastics industries.

Can erthos help? It focuses on designing materials that can fit into the systems companies already use, making it easier for brands to transition away from fossil-fuel plastics without rebuilding their supply chains. Getting a product to fit into existing moulds and machines is the key for change from plastics to bio-plastics.

The company combines biomaterials science with advanced data tools, they say, to design plant-based formulations made from renewable ingredients such as plant fibers, starches, and oils. By using AI to test and refine formulations quickly, the goal is to create materials that match the durability and functionality of traditional plastics while reducing environmental impact. See Tipa, a brand that works.

The stakes are enormous. Hundreds of millions of tonnes of plastic are produced globally each year, and only a small portion is recycled. The rest accumulates in landfills, waterways, and ecosystems where it can persist for centuries. Worse even, bits of plastics called microplastics are getting into our lungs, our waterways, our food, our brains.

Startups like erthos are trying to change that equation by addressing plastic at its source, replacing the material itself rather than simply managing the waste it creates.

Today the company works with brands exploring alternatives for packaging, consumer products, and other plastic-heavy industries, helping design materials that can be recyclable, compostable, or derived from renewable feedstocks.

Erthos is a Canadian cleantech startup developing plant-based materials designed to replace petroleum plastics and support a circular economy. Founded in 2019 by Nuha Siddiqui, Kritika Tyagi, and Chang Dong at the University of Toronto, the company combines biomaterials science with artificial intelligence to create sustainable plastic alternatives.

Its proprietary platform, ZYA, uses AI to design bio-based resins that can perform like traditional plastics while working within existing manufacturing systems.

Erthos has raised $11.2 million in total funding, including a $6.5 million oversubscribed Series A led by Horizons Ventures, with participation from The51 Food & AgTech Fund, Thrive Venture Fund at BDC Capital, Francis Family Fund, TELUS Pollinator Fund for Good, DcarbonVC, Middle Cove Capital, and earlier investors Golden Ventures and Bee Partners.

::erthos

More Bio Plastics News from Green Prophet

• This Plastic Is Made From Corn: A Biodegradable Alternative to Fossil Plastics
• Sustainable Plastics That Emerge From the Sea
• Teen Scientist Creates Bioplastic from Banana Peels
• Eco-Friendly Compostable Food Packaging for Restaurants
• DuPont Turns to Algae to Create Alternative Seafood

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Many of today’s businesses feel like they’re drowning in data but starving for insights. Sound familiar? You collect customer information, sales figures, production logs, marketing metrics – yet still struggle to turn that data into decisions that move the needle. That’s where the data science lifecycle comes into play. It’s not just for big companies with massive analytics teams. When applied thoughtfully, even small and mid-size businesses can use it to create better predictions and drive real outcomes.

Here, you’ll walk through how to apply each stage of the data science lifecycle, how to make it practical for your business, and how modern platforms streamline the process so you don’t have to become a data scientist overnight.

• Define the Problem

Data science doesn’t begin with the data, but rather with a problem you want to solve. The first stage of the lifecycle is problem definition. You need to ask: What decision are you trying to improve? What outcome do you want? What business processes need to change?

Maybe you want to reduce customer churn, optimize delivery routes, predict equipment failure, or increase high-value customer purchases. Whatever it is, you must define it clearly. Ambiguous goals lead to vague results.

For example, instead of saying “we want more sales,” define “we want to increase repeat purchases by 20 percent within 12 months from our top 25 percent of customers.” 

• Collect and Clean the Data

Once you have your question, the next stage is data collection and preparation. You’ll need to gather data that’s relevant to your question – customer history, transaction logs, equipment hours, social engagement…whatever applies.

Allocate time and resources to clean the data, if needed. Standardize entries, handle missing values, remove duplicates, and ensure your data is properly labeled and structured. This stage lays the foundation. If your data is unreliable, the models and insights built on top of it will be shaky. So take your time here.

• Explore and Visualize

With clean data in hand, you move into exploratory data analysis (EDA). This is where you interact with the data to discover patterns, trends, anomalies, and relationships. It’s not about making decisions yet – it’s about understanding what the data is telling you.

You might ask:

• Which customers are most likely to churn?
• What repair incidents frequently precede equipment breakdown?
• Are there seasonal patterns in your sales?
• What cohorts of users behave differently?

Visualization tools help a lot in this stage. You might map customer segments, chart equipment failures, or link marketing campaigns to ROI. The insights you uncover here shape the next phase.

• Model and Predict

Now you advance into modeling. Based on the patterns you identified, you build predictive models. These might forecast customer churn probability, equipment failure dates, sales volumes, or other outcomes relevant to your problem.

This is where data science often feels intimidating, but modern platforms are making this far more accessible. Advanced tools now allow you to build and validate models with less manual coding, and focus instead on interpreting results and making decisions.

• Prescribe and Act

Here’s where the magic happens. Predictive insights are valuable, but only when they trigger action. This stage – sometimes called prescriptive analytics – transforms forecasts into decisions, workflows, and changes that move your business forward.

For example, if your model predicts that a fleet vehicle has a 70 percent chance of requiring maintenance in the next 30 days, the prescriptive step is: “Schedule maintenance now before breakdown.” Or if a customer is likely to churn, the action might be: “Offer them a personalized discount or onboarding call.”

• Monitor and Improve

The final stage of the lifecycle is often underappreciated: monitoring and maintenance. Even the best models degrade over time because business conditions change, data evolves, and new patterns emerge. You need to track how your predictions perform and continuously refine your approach. This stage keeps your analytics alive and relevant.

Real-World Example: Fleet Maintenance

Let’s bring this to life with a concrete example. Imagine you manage a delivery fleet. You’re spending a lot on maintenance, facing unplanned breakdowns, and struggling to allocate vehicles efficiently. Here’s how the data science lifecycle helps:

• Problem Definition: Reduce unplanned maintenance costs by 30 percent over the next year.

• Data Collection: Gather data on vehicle hours, miles driven, past repair records, driver logs, fuel usage.

• Exploratory Analysis: Visualize patterns – certain vehicles break down more under specific conditions, locations, or driver behaviors.

• Modeling: Build a model to predict which vehicles are at highest risk of needing repair in the next 30 days.

• Prescriptive Action: Using fleet maintenance software, schedule preventive maintenance for high-risk vehicles, replace tires proactively, and rotate drivers based on risk patterns. By tracking standard repair times and comparing performance against them, you create a culture of accountability and motivate staff to complete repairs more efficiently.

• Monitor and Improve: Track breakdowns and maintenance costs. Measure whether the model’s predictions align with real outcomes. Tune variables, update thresholds, and adjust scheduling logic.

In this scenario, you move from reactive maintenance – “fix something when it breaks” – to proactive maintenance: “fix it before it breaks.” That shift saves money, improves uptime, and builds accountability across your fleet team.

Your Path Forward

You don’t need to hire a 50-person analytics team to start. Every business can begin with one clear question and one clean data set. Start small and add complexity only when you’re ready. This is your best path forward for sustained results!

The post How to Use the Data Science Lifecycle in Your Business appeared first on Green Prophet.

Neuralink, developed by Elon Musk, promises to help people who are paralyzed operate a computer with their thoughts. While first trials are being sought in humans with mobility issues we can imagine a future, (or not!), where humans are interlinked through our brains. It takes a massive amount of funding to build such a dream and now Neuralink is getting some competition, usually a good thing.

Paradromics, a US neurotechnology company says they have developed the highest data-rate brain-computer interface (BCI) platform, announced the US FDA has granted Investigational Device Exemption (IDE) approval to begin a feasibility study with their implant called Connexus BCI.

As the first company to receive IDE approval for speech restoration with a fully implantable BCI, Paradromics is excited to give participants the opportunity to control a computer and communicate via text or synthesized speech to recover connection.

Related: Womb implant is a success

The Connexus BCI is designed to record and decode brain signals at unprecedented rates of information transfer. “In Q1 next year we are launching a clinical study with the best engineered brain computer interface in the world,” said Paradromics’ CEO and founder, Matt Angle, Ph.D. “This is the device that patients deserve.“

The Connect-One Study will initially enroll two participants—with impaired speech and limited extremity movement (upper and lower) due to severe loss of voluntary motor control—who live within four hours of three clinical sites, UC Davis in Sacramento, Massachusetts General Hospital in Boston, and Harvard Medical School.‍University of Michigan in Ann Arbor, MI – led by Investigator Matthew Willsey, M.D., Ph.D., a neurosurgeon with dual faculty appointments in Neurosurgery and Biomedical Engineering.

This FDA approval builds on key milestones for Paradromics, including three years of stable preclinical recordings, the first successful acute Connexus BCI implantation at the University of Michigan by Dr. Willsey, and the release of a scientific preprint demonstrating that the Connexus BCI delivers an industry-leading 200+ bits per second rate of information transfer in pre-clinical models. Paradromics has a Connect-One Study roadmap to add more sites, include more participants, and explore new BCI applications.

The Connect-One Study is the first in a series of clinical applications planned for the Paradromics BCI platform. Those interested in participating in this or future studies are encouraged to join the Paradromics Community.

The first study will look at restoring speech by Paradromics sees the future in enabling AI-powered treatments for motor impairment now and chronic pain, addiction, depression, and other neurological conditions in the near future.

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Imagine a world where forest wild fires are stopped before the fire trucks even roll. That’s what Israeli startup FireDome just showed in its first real-world demo of an autonomous wildfire resilience system — a machine-vision launcher that spots small fires and catapults eco-friendly flame retardant capsules to snuff them out in seconds.

The system uses AI-powered detection to track smoke, heat, and movement, making split-second decisions on where to aim and release biodegradable capsules filled with water or retardant. The goal: to contain wildfires before they spread. It could save factories and land managers millions on insurance premiums. And save people in California the grief from wildfires. Personal home versions are in the works.

“This is the turning point,” said Gadi Benjamini, CEO and Co-Founder of FireDome. “Wildfires are getting bigger, costlier, and harder to insure against. Our technology acts in seconds to protect lives and landscapes before first responders arrive.”

FireDome’s platform defines what it calls Wildfire Resilience-as-a-Service (RaaS) — a new model that merges detection, decision-making, and suppression into one holistic defense system for communities, utilities, vineyards, and resorts living with wildfire risk.

“FireDome exemplifies the kind of breakthrough that can change how we live with wildfire risk,” added Dr. Lori Moore-Merrell, former U.S. Fire Administrator and FireDome advisor.

With climate change turning wildfires into a year-round menace, FireDome’s automated response could help insurers, landowners, and municipalities rethink what resilience looks like — using technology not to fight nature, but to act before disaster strikes.

::Firedome

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Tattoo artists might be wondering if they will be out of jobs, or just able to license their NFT designs to a computer? A new Austin-based startup called Blackdot says it has built an AI-powered tattoo machine that is safer and less painful than getting a human-applied tattoo.

Called Aero for Artist Enabled Robotic Operator, Blackdot’s machine uses computer vision, fine control, and very shallow needle penetration to reduce discomfort. It is now installed at Bang Bang in New York, and already operating in Austin.

In some areas of medicine, robotics and machine learning have changed the name of the game and survival outcome for removing cancers like prostate. Robotics can help a human operator be more precise, but are we ready to hand over the controls?

Do we want a machine that takes the craft out of the hand of the artist? I make pottery out of earth because I believe there is spirit in matter. Is a tattoo applied by a machine giving the same vibes as a potter’s mug made in a factory or a violin made on a machine?

According to the people at Aero, the device tattoos in dot-based grayscale patterns, applying many minute points rather than deep continuous lines — a technique they say limits pain and improves precision.

One upside: fewer tattoos gone wrong?

Tattoos, not just in hipster times, have long carried a dual identity: as personal art but also no small part of getting a tattoo is about the pain and the act of bodily risk. Also, I wonder: does a machine-made tattoos open up the practice of skin art at a time when researchers are calling us to pay attention to the risks of the materials in tattoos and a possible link to auto-immune diseases and cancer. As there is little regulation, there is little known about the long-term health effects of tattooing.

What do the world’s religions say about tattoos?

From a Islamic perspective, tattooing is generally considered prohibited (haram) in many schools of thought. The Prophet Muhammad is narrated in hadith literature to have cursed both the tattooer and the tattooed (for altering the creation of God). Some scholars argue that tattoos break the ritual purity (ablution, or wudu) because they alter the skin surface.

We find some literature to back up the Islamic prohibition: ‘Abd-Allaah ibn Mas’ood said: “May Allah curse the women who do tattoos and those for whom tattoos are done, those who pluck their eyebrows and those who file their teeth for the purpose of beautification and alter the creation of Allah.” (Al-Bukhari, al-Libas, 5587; Muslim, al-Libas, 5538).

In parts of Lebanon, Iraq, and Iran, some Shiite communities have historically tolerated or quietly practiced tattooing, especially small religious motifs (like the names of Imams or sacred symbols). And among younger Shiites, especially in diaspora communities, tattoos are increasingly popular as personal or religious expression — though clerical authorities still discourage them.

In Judaism, tattoos are often discouraged based on Torah injunctions and Levitical prohibitions, and tattoos are not encouraged at all.  It is permitted to remove a tattoo and pierce your ears. That said many Jewish people do get tattoos. Common ones include the Tree of Life symbol, Hebrew and biblical expressions (The Nation of Israel Lives), and some people get tattoos of their grandparent’s numbers printed on them during the Holocaust.

In Christian traditions, the picture is more varied. Some conservative or literalist communities may discourage tattoos, particularly when associated with body modification or vanity, but there is no universally binding doctrine rejecting them. Many churches do not formally forbid tattoos, leaving it to individual conscience, church culture, or pastoral guidance. This blog offers some history of Christian tattoos in Jerusalem. The author points out that some conservative or literalist groups still reject tattoos outright, holding to Leviticus as binding.

Many other Christians see tattoos as a matter of conscience, arguing that Old Testament prohibitions were tied to ritual purity, pagan associations, or covenant identity, and are not binding in the same way after Christ. In some traditions (like the Razzouk family in Jerusalem), tattooing is even a Christian devotional act, marking pilgrimage and identity.

Unlike in Abrahamic religions, tattoos (godna in Hindi) have been widely practiced in Hindu culture for centuries. Tribal and rural communities across India have used tattoos for spiritual protection, identity, and beauty. Some designs are linked to deities, mantras, or cosmic symbols.

What about the art of it?

Almost painless tattoos may worry tattoo artists who will be out of jobs unless they figure out how to sell designs as NFTs, and also people who may more liberally get tattoos without possible health or spiritual implications.

In Sci-Fi dystopia, we’ve reported on how tattoos can be used for nefarious purposes, such as IDing and tracking people. Such as the tattoo below, from MIT Media Lab.

Tattoos could be used as a trackpad to remotely control your mobile phone or adjust the volume of the music you tune into. They can track user data and report back to you, like a body-integral Fitbit, with embedded thermochromic displays that change color in reaction to heat, reporting on body temperature, blood pressure, breathing patterns. It might also report on your immediate environment, checking air quality, weather conditions, and alert you to the presence of harmful substances.

After hearing all sides — from health warnings and religious prohibitions to the futuristic promises of AI-driven tattoo machines — I’ve made my choice. I’ll keep my skin tattoo-free, au naturel. For me, my body already carries its own stories.

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SpotitEarly and Snoopy helps labs detect small lung, breast, prostate, and colorectal cancers

They say dogs are a man’s best friend and now a new startup is hoping dogs will help sniff out cancer at early stages when it’s treatable. SpotitEarly has created a unique, patented method capable of detecting four types of cancer—lung, breast, prostate, and colorectal—which together represent approximately 50% of all new cancer cases.

In the future, the company intends to expand its capabilities to include additional types of cancer. To date, over $8 million has been invested in the company, including funds from the Menomadin Foundation and Hanko Ventures.

The technology of using dogs to sniff out cancer which we reported on in 2013 is being tested out in a hospital and combines advanced artificial intelligence (AI) technology with the highly developed olfactory capabilities of specially trained dogs, achieving remarkable accuracy.

The test demonstrated high early-stage sensitivity across all tested cancer types:

• Breast cancer: 94%
• Lung cancer: 97%
• Prostate cancer: 97%
• Colorectal cancer: 86%

The test has also shown efficacy in identifying other cancers as well.

How it works: Patients breathe into a specially designed face mask for three minutes. The mask is then sent to the company’s laboratory, where trained beagles “analyze” the sample under the supervision of an AI system. Each sample undergoes 3 to 5 examinations to ensure high accuracy.

To date, more than 1,400 participants—primarily aged 40 to 70—have taken the test, which has demonstrated an impressive accuracy rate of 94%.

Human breath contains over 1,000 Volatile Organic Compounds or VOCs. Science has shown that VOCs represent rich sources of biomarkers associated with metabolic processes and diseases in the body, each identified
by a significant odor signature, including cancer. SpotitEarly harnesses the science of scent to detect cancerous VOCs in exhaled breath samples.

Partners include the University of Pennsylvania.

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Customer service reigns supreme in today’s crowded digital marketplace. Brands can stand out from competitors by providing reliable, real-time customer service and prioritizing customer needs. Regardless of the company’s size, customers expect — and in many cases demand — their specific requests be handled seamlessly. One way that brands are meeting the needs of these requirements is by leveraging the power of artificial intelligence (AI). 

AI is transforming customer service, and therefore a brand’s interactions with customers daily. From replying to on-site queries to following up on questions on Instagram DM to sending customized SMS text messages, AI is reshaping the customer experience altogether. Below are a few common use cases in different industries, as well as tips for using AI in your customer interactions.  

AI Use Cases in Customer Service 

There are various use cases for AI in customer service. As an example, AI in automotive industries is revolutionizing how customers make showroom appointments and book test-drives. Instead of calling a dealership and waiting on hold until a sales member is available, AI-powered chatbots can make the appointment within seconds. Through generative conversational AI, customers may think that they are in fact speaking with a live agent as opposed to a software program!  

In the food delivery space, AI is improving the logistics of creating delivery routes for takeout drivers. More accurate prediction times are calculated so customers know precisely when their stuffed crust pepperoni pizza will be delivered. Not only does this improve customer satisfaction, but it also streamlines processes to boost the efficiency of local drivers.  

Airlines are also utilizing AI to assist customers with urgent requests and provide personalized recommendations during their flights. AI-powered chatbots on KLM Royal Dutch Airlines are assisting with rebooking and providing real-time flight information via Facebook Messenger. 

Delta Air Lines is using AI to store frequent travelers’ in-flight entertainment preferences and suggesting relevant content during their travels. 

Health and wellness-based brands are using AI to manage appointments and schedules. AI can help coordinate different bookings based on staff availability. This can help maximize a staff person’s productivity while also making the customer’s booking experience as easy as possible. AI can remind clients of an upcoming appointment to help avoid any last-minute cancellations. 

Tips for Using AI in Your Customer Interactions 

Now that you have a sense of the types of use cases for AI in customer service, here are some practical tips to keep in mind as you begin to leverage this technology for your specific industry needs. 

Tip #1: Be Personal 

Whether you are leveraging AI or not, customers want their needs to be heard. They don’t want to feel like they’re speaking with a bot. Instead, they want to feel like they’re being taken care of uniquely and treated as a human being. For this reason, personalization is key. 

Through data analysis, AI can assist in personalizing experiences by looking at past customer behaviors such as purchase history and site interactions. Any former conversations can also be tracked to ensure that conversations are picked back up and customers don’t need to repeat themselves. 

In addition to real-time personalized conversations, AI can also provide applicable product recommendations and tailored content. Amazon, for instance, creates a dynamic homepage experience for each Amazon Prime customer based on recent shopping purchases. These recommendations can lead to new purchases and keep customers loyal to specific brands. 

Tip #2: Provide 24/7 Support

Long gone are the days of picking up the phone and calling customer service when a problem arises. Customers today are looking for their issues to be resolved ASAP, meaning brands need to be able to provide 24/7 support. No matter the time of day, AI-powered chatbots can augment your customer service team and respond to inquiries immediately. 

AI can handle frequently asked questions and point users to specific content to help answer their questions. These chatbots can track packages and provide real-time shipping updates. For any delays, they can let customers know of the problem before it becomes a major issue. 

By answering these questions, your customer service department can focus on more complex issues, such as handling broken items during delivery. By passing these queries to human support agents, your customers’ needs are taken care of seamlessly. 

This around-the-clock support can be handled via on-site chatbots as well as SMS text messages. SMS is becoming an increasingly popular solution for brands to automate customer conversations and even remind users when a sale is occurring or to reorder a recently purchased product. 

Tip #3: Integrate Platforms 

On the backend, one way to ensure an easy transition is to integrate any AI-driven tools into existing platforms. Your team has enough to manage besides learning a new system entirely. After all, the purpose of AI is to ease the burden of your employees, not create new hurdles or challenges for them to overcome! 

Fortunately, many of today’s AI tools and systems can be easily integrated. CRM (customer relationship management) platforms and customer service portals can likely adapt to new AI technology. This way, all of your prior customer information is saved, and there are no gaps in customer experience or service. 

Of course, in addition to integrating platforms, be sure that your team is up to speed on these new advancements. Employees should be well-trained in understanding what AI can handle and what is best kept with the team. As an example, AI can quickly answer FAQs and point leads in the right direction in terms of recommending certain products; however, a loyal customer who has yet to receive an expected package after due time should likely be handled by a human customer service agent. 

Support Your Service Team With AI 

While AI cannot do the work of your customer service team altogether, it can ease common pain points for both your employees and your customers. Regardless of your industry, AI can create personalized communications that are handled 24/7 across your already executed platforms. Leaning into AI today can help power your team and the future of your business. 

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