General Electric Company (GE) is a global industrial technology company focused on aerospace, power, and renewable energy. Following a multi‑year restructuring, GE is transitioning into separate public companies, with GE Aerospace and GE Vernova as its primary businesses. The company develops advanced hardware and software solutions that power aircraft, energy infrastructure, and industrial systems worldwide.
RoofIT lets roofing contractors order materials from ABC Supply, see prices, and track deliveries without leaving the CRM they already use to run jobs.
Teams can preview how personalization changes rankings for a specific shopper and query before turning it on for everyone.
Zendesk turns AI labels on tickets into sorting rules, queues, and dashboards so urgent or specialized cases go to the right people faster.
This workflow teaches an AI to understand whether Chinese housing-related social posts are upbeat, neutral, or worried, so analysts can measure market mood instead of reading millions of posts by hand.
Instead of using one AI for everything, investors assign different AIs to the parts they do best—research, financial modeling, and visual review—based on the property type.
As a person clicks around right now, the system updates what it thinks they want and reorders recommendations on the fly.
AI watches heat and power-use data from electrical systems to catch dangerous overloads before they cause outages or fires.
An AI agent reads tenant messages from email, chat, and forms, figures out whether people are happy or upset, spots urgent problems, and gives managers a daily summary of what needs attention.
Comments and markups made in Bluebeam on drawings can be shown inside the submittal record so reviewers can see what was marked up, by whom, and on which page.
Chip factories can use special patterning and stacking methods to build tiny supercapacitors right into the chip during manufacturing.
Software suggests what rent a landlord should charge for each apartment, sometimes updating prices often and letting managers accept recommendations automatically.
The system reads claim-related documents, looks up the right rules and references, and helps review reimbursement requests faster.
AI helps buildings run smarter by predicting repairs, reducing wasted energy, tracking sustainability metrics, and automating tenant interactions.
A landlord uses software to help decide whether a renter looks qualified, but must explain what the software does, test that it works, and make sure it does not unfairly disadvantage protected groups.
The company built a dashboard that connects each lease to its rent changes over time, so leaders can see which tenants renewed, how much rents increased, and which properties or teams are performing well without manually stitching spreadsheets together.
IAS uses contextual signals to steer ad buying toward better-performing pages, and brands then measure stronger click-through, conversion cost, or return on ad spend.
The system looks at rental market data and uses several prediction models together to estimate what rent a property should command.
A university gave students an AI study helper they could message anytime to ask assignment questions and get guidance while preparing assessments.
Use several AI models together to search through many possible nano-material designs and pick ones that make EV supercapacitors store more energy, last longer, and stay stable.
Investors can estimate how much more money a building could make if AI helps more renters renew, then use that estimate when deciding what to pay for the property.
Use software intelligence to decide when solar power should be sold immediately or shifted through batteries later, so the same renewable assets earn more money and operate more flexibly.
A small, telecom-trained AI agent answers common customer support calls, checks live account and network systems, and either fixes the issue or hands it to a human with full context.
The same AI helper can answer residents’ common questions and remind them about renewing their lease, making living at the property feel easier and more responsive.
The system compares where trucks are going with where fuel is bought, then steers drivers to cheaper stations and flags suspicious purchases.
An algorithm decides in real time when a UPS should draw fast burst power from an ultracapacitor versus steadier energy from a battery, so backup power stays stable and the battery is stressed less.
An AI agent checks invoices against contracts and service expectations, spots anomalies, and drafts variance commentary so asset managers can protect NOI.
An AI system is being designed to predict droughts, floods, and other severe weather in Brazil much earlier, helping the country prepare before damage happens.
Instead of different departments working separately, WIN Garment uses one shared digital workspace so designers, buyers, technicians and sales can work together online from anywhere.
Combine crop data from many countries to estimate the world's wheat supply and how much will remain in storage.
The AI predicts which paying players are likely to quit at a certain level, so the game can help them with boosts or tips before they give up.
Instead of sending sensitive transformer data everywhere, the analytics can run on a separate local network so operators get AI-driven insights with lower cyber risk.
A camera looks at produce on a sorting line and an AI model decides what item it is so machines can route it correctly.
An AI controller learns when a rail system’s supercapacitor should store or release electricity so trains use energy more efficiently.
A digital copy of the aircraft’s battery and power system uses physics plus AI to track wear and predict what will happen next.
An energy company uses customer data to estimate which households are likely to leave, so it can intervene before they switch providers.
Instead of just matching ads to simple keywords, AI reads the meaning of each page so brands can place ads next to more relevant content.
AI reads lease documents and pulls out important details so teams do not have to manually search every page.
Once the utility network is built correctly, teams can ask the system to follow connections and show what equipment belongs to which part of the grid.
The system gathers what customers want and what regulators require, then makes sure the quality system is built to meet those needs.
AI would eventually handle some maintenance-related steps automatically in the background so workers do less repetitive system work.
Connect solar hardware to Home Assistant so it can measure how much power your panels make, show it in dashboards, and use forecasted production to trigger automations.
An AI controller decides when a battery should provide energy and when an ultracapacitor should handle fast power bursts, so the system uses each device for what it does best.
A neural network acts like a fast traffic controller that decides, almost instantly, whether the battery or the supercapacitor should handle incoming or outgoing power in a solar-plus-storage system.
Engineers ask the AI to walk through different quality decision paths so they can see what might happen before choosing an action.
Teams can explore design results for antibodies, peptides, and protein-protein interactions in example notebooks that show structures and model outputs together.
It helps buyers and strategists compare battery technologies, manufacturing capacity, and future costs so they can choose the right storage equipment and timing.
The tax authority uses AI to scan invoice activity and flag companies whose billing behavior looks fake, helping investigators find businesses created mainly to issue fraudulent invoices.
AI turns apartment underwriting into charts and probabilities that help lenders and investors understand risk, making it easier to win approval and funding.
The company uses AI to spot which tenants are likely to not renew their leases, so property teams can step in early and try to keep them.
A drone flies over cocoa and cashew farms at different growth stages, and an AI system combines the images with tabular farm data to estimate crop condition and likely yield.
Energy prices and usage signals can change with real demand, helping providers send power where it is needed most and avoid wasteful overbuilding.
One small AI first decides what kind of help request came in, then sends it to the right expert AI—or to two expert AIs at once if both are useful.
By watching lots of machine health signals in one place, the factory can spot problems sooner and plan maintenance before equipment causes bigger issues.
The system watches trucks in real time and alerts the team if a driver goes off route, stops unexpectedly, or is running late so they can fix problems fast.
Software helps an uncrewed military aircraft fly and carry out missions with less direct human control.
Use AI to predict which aircraft parts or systems may fail soon, but rank and act on those predictions using the FAA’s safety categories so the most dangerous risks get attention first.
After people moved in, the team watched how the building behaved, listened to complaints, found a hidden heating problem, and adjusted controls to fix it.
Use one network model to turn utility asset data into engineering designs, schematics, maps, and views that different teams can use without rebuilding the data each time.
When the sales agent is connected to Salesforce, admins can grant it extra permissions so it can read activities, tasks, events, and custom fields needed to fully research leads and optionally write summaries back.
AI creates a first draft of a trade settlement contract using old templates plus details pulled from emails, presentations, and other documents, then turns the contract review meeting recap into a list of required updates.
The system can use a specialized model to predict protein structure or binding-related outputs faster on GPUs, then show the results inside the same web app.
A store app tells workers which jobs matter most right now, like fixing empty shelves first, so they spend less time figuring out what to do next.
The system looks at customer history and current behavior to spot who may leave soon, explains why, and can automatically trigger actions to keep them.
AI inside Procore helps construction teams read drawings, measure spaces, summarize long documents and draft routine project paperwork.
Instead of just showing raw numbers, the team looks for patterns over time and explains what they learned, what changed, and what they will optimize next.
When an employee asks IT for help, the system reads the request, checks whether the person is allowed to make it, looks up the right knowledge, figures out what the issue is, and sends the ticket to the right team automatically.
Use past buoy measurements and weather-related signals to predict near-future wave height at offshore wind sites, helping crews and operators decide when it is safe and efficient to work at sea.
One AI predicts which properties are good opportunities, and another predicts which buyers are ready to act, so the business can match the best buyer to the best property at the right price.
A utility can make the grid run at slightly lower voltage to save electricity, but too much rooftop solar makes voltage harder to manage. This workflow coordinates solar smart inverters with existing tap changers and capacitor banks so the utility can keep voltage in range and squeeze out more energy savings.
Give every ad creative a standard label so different TV and streaming systems can recognize the same ad and count how often people saw it.
The tax authority uses AI to scan invoice behavior and flag companies that look fake or exist mainly to issue fraudulent invoices.
Use AI to decide when a supercapacitor should quickly absorb or release electricity so wind or solar power looks steadier to the grid.
An AI-like data-driven controller learns from sensor inputs and outputs to decide how a battery and supercapacitor should share work, so solar power stays smooth and the DC bus voltage stays stable even when sunlight or load changes suddenly.
Take a trial-design AI built by regulators and adapt it with local cost and real-world healthcare data so health assessment agencies can judge how useful and cost-effective a treatment is in their own system.
Instead of clicking around a map, analysts can pull wave data directly into code and automate studies of how devices might perform at many sites.
For storage chips, the safety system can only hold one error at a time, so if several problems happen together some may be lost and software should assume the worst.
AI spots tenants who may leave because of unresolved maintenance issues and helps teams fix problems fast before the tenant decides to move.
The tool not only looks for a cheaper route, it also makes sure the ship avoids dangerous or forbidden places and can follow required lanes or checkpoints.
It helps ships choose the best path by looking at weather, waves, and water depth so they burn less fuel.
A camera takes pictures of harvested crops, and an AI system sorts them into quality grades the way an experienced inspector would, but faster and more consistently.
Before AI can help, the Air Force needs a clean machine that gathers and organizes old maintenance records so analysts can test what works.
This is like a flight recorder for medical AI: it saves what went in, what evidence was found, and how the AI answered so hospitals can inspect decisions later.
A turbine’s built-in controller watches generator signals to spot early signs of faults, so operators can fix problems before the machine fails underwater.
An online prescription eyewear retailer uses an AI system that learns from shopper behavior to suggest products each person is more likely to want.
Sportradar uses market knowledge, betting-industry relationships, and data to help the NHL find and launch betting sponsors in different countries.
Software now helps Pluxee automatically review interactions, forecast staffing needs, and track coaching, instead of relying on spreadsheets and manual checks.
Certara worked with Brazil’s regulator so drug companies can send newer eCTD 4.0 application packages through GlobalSubmit instead of older, more manual methods.
Instead of one AI per task, a larger model combines images, sensor readings, weather, and farm notes to help with many farm decisions.
The system uses location data and unified records to show where unelectrified communities are, helping the government and utilities plan power-line and connection works better.
This AI system uses strain data from composite airplane parts to find hidden cracks and damages that are invisible on the surface by combining smart optimization and machine learning.
Give the system a text recipe for a molecule, and it turns it into a machine-readable graph with useful chemistry features.
Use software to decide when water treatment equipment should run so the grid stays balanced while water service is still delivered.
The system looks at a help ticket and suggests which team should handle it next.
A utility takes its old network data, matches each asset to the right standard bucket in Esri’s Utility Network Foundation, and loads it into ArcGIS in several passes so the new system works correctly.
Developers can build apps that plug deeply into Seismic so teams can add custom features or connect Seismic to internal systems.
Instead of relying on one AI app, Linklaters is combining several AI tools so lawyers can chat, review deals, manage contracts, and use Legora together on client matters.
A software system helps utilities keep track of important equipment and infrastructure, like a smart filing cabinet and workflow hub for physical assets.
An AI system reads a patient description and clinical trial criteria, then finds and ranks the trials that best fit that patient.
A trucking company uses one smart in-cab device to watch the road, track the truck, handle driver logs, and show everything in one dashboard.
Instead of just using valves to lower water pressure, a utility can use smart selection software to find where replacing those valves with power-generating devices makes financial sense.