Mentioned in 59 AI use cases across 13 industries
This is like a smart mechanic for power-plant valve actuators: it watches sensor data, predicts when parts are likely to fail, and also explains in plain engineering terms why it thinks a failure is coming (e.g., which pressures, temperatures, or vibrations are driving the risk).
Think of this as a very smart data detective for energy and mining companies: it combs through mountains of operational, geological, and financial data to spot hidden patterns that humans miss, then suggests where to dig, how to run equipment, and where money is being wasted.
This is like putting a smart ‘check-engine’ light on every critical asset in an oil & gas operation. Instead of waiting for something to break, software constantly watches sensor data and warns you in advance when a pump, compressor, or pipeline component is likely to fail, so you can fix it during planned downtime.
Think of this as putting a “smart brain” on top of every critical piece of oil & gas equipment. It constantly listens to sensors, learns what ‘normal’ looks like, and warns you before something breaks so you can fix it at the best possible time.
Imagine every time you open your TV, there’s a smart concierge who has watched everything you’ve ever seen, remembers what you liked, what you quit after 5 minutes, what you binged in a weekend, and what people like you enjoy. That concierge quietly rearranges the shelves so the things you’re most likely to love are always right in front of you. That’s what a Netflix-style recommender system does—at software scale for millions of viewers.
Imagine a super-detailed digital twin of an old timber building that can almost build itself: you feed it survey data and drawings, and an AI-driven system assembles a smart 3D model that knows what each beam and joint is, how it fits together, and how the building has changed over time.
This is about using AI as a super-smart control center for factories and supply chains. It watches machines, inventory, orders, and logistics in real time, then predicts problems before they happen and suggests the best way to run production so you waste less time, material, and money.
This is like a super-fast paralegal that specializes in personal injury cases. You tell it the key facts, and it drafts legal documents and letters for you to review and finalize instead of starting from a blank page.
This is about using AI as a smart junior assistant for lawyers — helping read huge piles of documents, draft routine language, and surface relevant cases so the attorney can focus on judgment and strategy.
Think of this as a ‘self-optimizing factory brain’ for mines: it watches every step of crushing, grinding, and separating ore, learns what settings give the best results, and then continuously tweaks the knobs to squeeze out more metal with less waste, energy, and downtime.
This is a strategy and analytics approach that helps large consumer packaged goods (CPG) companies use their data and AI as a new kind of ‘economies of scale’—not just buying more shelf space or running bigger TV campaigns, but spotting profit opportunities and efficiency gains across brands, markets, and channels using advanced analytics and generative AI.
This is like giving your supply chain a smart, always‑on co‑pilot that can read all your plans, emails, contracts and forecasts, then suggest better decisions — from what to buy, where to make it, and how to ship it — in plain language.
This is like putting smart ears and eyes on your machines so they can tell you when something sounds or looks wrong—before it breaks. Small sensor boxes sit on the equipment, watch and listen in real time, and warn you early so you can fix problems during planned downtime instead of after a costly failure.
This is about using AI as a super-fast paralegal and forensic analyst that can read millions of documents, emails, and records, spot patterns, and summarize findings to support disputes, investigations, and regulatory responses—while staying within new legal and compliance rules.
Think of Robin AI as a very fast, tireless junior lawyer that reads contracts, flags issues, and suggests edits so your human lawyers only have to make the final calls instead of doing all the manual line‑by‑line work.
This is like a standardized exam for AI lawyers: a big, rigorous test to see how well AI systems actually understand and analyze contracts in realistic legal scenarios.
This is like a global "traffic control tower" for the oceans that watches ships from space and radio signals, then uses AI to flag suspicious or risky behavior in near real time.
Think of the future transport system as a giant, city-wide brain. Instead of each car, bus, or train acting on its own, AI watches traffic, weather, demand, and incidents in real time and then orchestrates everything—routes, signals, pricing, and even maintenance—so people and goods move faster, safer, and cheaper.
This is like giving every lawyer a super-fast digital assistant that can read huge piles of contracts, flag issues, and summarise key points in minutes instead of hours—while the human lawyer still makes the final calls.
This is like giving airline pilots a smart co-pilot that never gets tired: an onboard AI that continuously watches the flight situation, predicts what might happen next, and suggests or executes helpful actions while keeping the human pilot in charge.
This is about using AI as a smart legal assistant for law firms—helping read and draft documents, search case law faster, and automate routine legal tasks so lawyers can focus on strategy and clients.
Think of this as using a very fast, very smart legal intern that can read huge amounts of text, find relevant information, and draft first versions of documents—but still needs a real lawyer to check, interpret, and sign off.
This is like giving your building’s heating and cooling system a smart autopilot. It watches how your building behaves, learns patterns of occupancy and weather, and then constantly tweaks HVAC settings to keep people comfortable while cutting energy waste and emissions.
This is like using extremely smart microscopes and calculators on a computer to design new medicines before you ever mix chemicals in a lab. The software predicts which molecules are most likely to work, so scientists test 100 promising ideas instead of 10,000 random ones.
Think of a data center as a giant, always‑on factory plugged into the power grid. Gridmatic builds an AI "power manager" that constantly watches electricity prices, grid conditions, and the data center’s workload, then turns dials up or down so the facility uses cheaper, cleaner power without sacrificing reliability.
This is like giving a commercial building’s heating and cooling system a smart autopilot. It watches how energy is used, learns building patterns (people coming and going, outside weather, peak loads), and automatically tunes HVAC settings to keep tenants comfortable while using less electricity.
Think of Cohesion as a digital command center for large office or mixed‑use buildings. It connects elevators, HVAC, security, access control, and occupancy data into one intelligent system so building operators can see what’s happening in real time and let software make many of the small adjustments people used to make manually.
This is like giving your car factory a super-smart assistant that watches everything on the line, spots problems before they happen, and suggests small tweaks that make the whole plant run faster, cheaper, and with fewer defects.
Think of a large office building as a living body. In the past, the heating, cooling and lighting were like organs running on fixed schedules, whether people were there or not. AI turns the building into a “smart body” that can sense where people actually are, how hot or cold it is, what energy costs right now, and then automatically adjusts everything in real time to stay comfortable while using far less energy.
This is like having a super-fast junior architect who can instantly sketch dozens of early design ideas from a short brief, so you can pick the best ones and refine them instead of starting from a blank page.
Think of a bond trader trying to place orders in a busy marketplace. The trader wants to know: “If I shout this price, what are the chances someone actually trades with me soon?” This research is about building smarter calculators that predict how likely a bond order is to get filled, and how fast, so trading algorithms can choose better prices and order types automatically.
Think of this as a smart co-pilot for buildings: it watches how your facilities are used, how equipment behaves, and what work orders come in, then suggests what to fix first, when to schedule maintenance, and how to run the building cheaper and smoother.
This is like having a tireless junior lawyer who can quickly read, draft, and explain legal documents, but works inside your computer instead of at a desk.
Think of a city where every bus, traffic light, and parking space can talk to each other in real time, and an AI ‘traffic conductor’ continuously listens and adjusts things so people and goods move faster and more safely with less waste.
Think of Intellosync AI as a legal assistant that lives inside your Microsoft 365 tools (like Word/Outlook) and helps you read, draft, and summarize legal documents faster and more accurately.
Legora is very likely an AI assistant focused on legal work—think of it as “ChatGPT that’s tailored for lawyers and legal documents,” helping review, search, and draft legal materials faster and with fewer errors.
Like having a junior contract lawyer on call 24/7 who can read your contract, highlight risky clauses, and explain them in plain English before you sign.
This is about teaching factories to "take care of themselves." Machines learn to warn you before they break, adjust their own settings for quality and efficiency, and eventually coordinate with each other so the whole plant runs with less human babysitting and fewer surprises.
This is like a very smart mechanic for jet engines that continuously listens to many different sensors and, using patterns learned from past engines, estimates how much life is left before something needs repair or replacement.
This is Netflix’s R&D lab for making sure every member quickly finds something they’ll love to watch. Think of it as a constantly learning concierge that rearranges the entire Netflix store for each viewer, in real time.
This is about how rich investors are using smarter trading technology and AI tools—like ultra-fast, data‑driven autopilots—to manage and grow their money instead of relying only on human advisers and manual trades.
This is Netflix’s “smart brain” that watches what every viewer clicks, skips, and binges, then uses a giant AI model to decide which shows and movies to put in front of each person so they’re more likely to hit play.
This is like a weather forecast, but for how much energy a building will use. It learns from past data about the building (design, materials, historical meter readings, weather) and then predicts future consumption so you can plan and optimize better.
This is a study that asks: "How much value do Netflix-style ‘Because you watched…’ recommendations really create?" It measures what happens to user behavior and business outcomes when you turn personalized recommendations on vs. off.
This is like giving Netflix a smart brain that quietly watches what you watch, when you stop, what you search for, and then rearranges the entire app, recommendations, images, and streaming quality just for you—millions of people at once, all differently.
Think of this as Netflix building its own very smart "taste brain" that understands movies, shows, images, and text, then wiring that brain into all the ways it personalizes what you see — rows, artwork, search, and more — instead of relying on a bunch of separate smaller brains.
This is like a smart air-traffic controller for a factory: it looks at all your orders, raw materials, machines, and people, then constantly rearranges the schedule so everything runs smoothly, on time, and at the lowest cost.
This is like giving every lawyer a super-fast, ultra-careful digital paralegal that reads contracts, finds definitions and references, and checks for problems in seconds instead of hours.
Imagine your entire oil and gas operation—wells, pipelines, refineries—covered in smart sensors and watched by an always‑awake digital control room. That digital brain constantly learns from data, spots problems before they happen, and quietly adjusts valves, pumps, and schedules so you produce more oil and gas with less downtime, waste, and risk.
Think of Draftwise as a “supercharged legal autocomplete” that lets lawyers draft contracts and documents using the firm’s best past work and clauses, suggested instantly as they type.
This is like giving lawyers a super-fast, very careful junior associate who can read long contracts in seconds, suggest edits, draft new clauses, and flag risks, but always under the lawyer’s supervision.
This is like having a smart assistant read through thousands of customer comments, group them by topic, summarize what people love or hate, and flag big issues for you—while human experts still check the most important insights before decisions are made.
Think of this as giving every lawyer a super-smart digital paralegal that can read huge volumes of cases, laws, and documents in seconds, suggest arguments, and draft materials—while the human lawyer still makes the final calls and ensures ethics and accuracy.
This is like a highly specialized “health meter” for jet engines. It watches many engine sensors over time, understands how they influence each other, and predicts how much life the engine has left before it needs major maintenance or replacement.
This is about how Netflix-style “Because you watched…” lists are created. The system watches what you watch, when you stop, what you rewatch, and then predicts what you’re most likely to enjoy next—like a super‑attentive video store clerk who’s seen your entire viewing history.
Think of Luminance as a super-fast junior lawyer that can read huge piles of contracts, highlight key clauses, and answer questions about them in plain English, but always within law-firm standards for accuracy and control.
This is like a smart mood board generator for interiors: you describe the room and style you want, and the AI instantly shows you many different design ideas and looks you can explore or refine.
Think of this as a building’s "autopilot for energy": it constantly watches how the building is being used, how hot or cold it is, what the weather and prices look like, and then automatically adjusts heating, cooling, lighting and other systems to keep people comfortable while using as little energy (and money) as possible.
Think of a smart building as a self-driving car for energy and operations: sensors constantly watch what’s happening (people, temperature, light, equipment), and AI decides when to heat, cool, light, or ventilate each space so you use the least energy without sacrificing comfort.