Use cases

Our technology has the potential to revolutionize a multitude of industries, improving efficiency through optimization of existing systems.

Enhancing and optimizing solutions to everyday problems through intelligent data sharing, machine learning and AI.

Delivery Agents

• Return value to local economies.
• Unparalleled level of privacy
• Decentralized - keep control of your data

Our Decentralized Delivery Network (DDN) provides the infrastructure to deliver pizzas, people and packages simultaneously across the globe. This framework is the result of 2 years’ worth of diligent building work, establishment of strong partnerships and experimenting with decentralised multi-agent systems in the mobility space – particularly with supply chains, autonomous vehicles, delivery networks and the UK train infrastructure.

This project is now coming to a fruition with the v.1.0 release of the Fetch.ai Mobility Framework. Further incentivized with FET rewards, this open-source product suite enables anyone to easily build multi-agent-based mobility services. The availability of real time information, and the intelligence to analyse it will make transportation systems more resilient and more efficient.

Autonomous AI Travel Agents

The Autonomous AI Travel Agents reduce the role of centralized aggregators and services, thereby encouraging direct provider-to-consumer interaction and as a result offer significant cost savings for both hotels and consumers.

The FET powered Autonomous AI Travel Agents network delivers an alternative method by which bookings can be taken: one where the customer and a service provider deal with each other directly, and one where a more personalized, better value experience can be delivered. It aims to provide an unparalleled level of privacy for all its users by moving the private, sensitive data away from centralized entities by keeping it safe in each user’s smartphone.

We are now looking for beta testers to test our Autonomous AI Travel Agents application!

Click here for more on Fetch.ai Autonomous AI Travel Agents

Smart Cities Field Trial

The smart city zoning trial in Munich, Germany launched in Connex Buildings and utilizes multi-agent blockchain-based AI digitization services to unlock data and provide smart mobility solutions in its commercial real estate properties in the city centre.

Take parking your car, for example. In a smart city, rather than driving into a parking lot hoping to find a space, an autonomous agent within your car will search and communicate with parking agents to find the nearest available space to your destination and book it for you, before directing you to it. When you come back to your car and drive off, your car agent checks out of the parking lot, calculates the payment and makes it for you, removing the hassle of parking tickets.

Using AI-agents to optimize resource usage and reduce the city’s carbon footprint, we predict that mass implementation of smart-city infrastructure will result in 34,000 tonnes Co2 emission reduction annually.

Commodity exchange & decentralized finance

The decentralized exchange is an innovative platform that will allow increased liquidity in trading of steel, base metals and other commodities.

Fetch.ai is helping the market participants overcome existing barriers to entry through technology. It will enable and simplify digitalized trading of these materials through the use of tokens, allowing market players to gain access to exciting new risk management tools, while maintaining market efficiency and security.

The decentralized platform will unlock new funding models for the supply chain participants by allowing them to use their materials as a collateral for tokens, which will enable full realization of the value of the underlying commodity they are holding.

It will also allow spread hedging between raw materials and finished products in a simplified fashion which will help market players to better hedge the portion of the supply chain which is more relevant to them.

Collective Learning

The Fetch.ai collective learning module is a tool that enables distributed parties to work together to train machine learning models without sharing the underlying data or trusting any of the individual participants. This is patricularly useful in scenarios where personally identifiable information (PII) is involved which cannot compliantly be shared.

This technology has a transformative potential across a range of sectors. In this case we've focused on the benefits it brings to the healthcare industry. Collective Learning via decentralized protocols provides hospitals and doctors with a network in which they can use their own private data, in the form of chest X-rays, that have been labelled according to whether the patients with pneumonia have tested positive for COVID-19 serving as a rapid diagnostic tool. It can also be used to identify the severity of a patient’s condition including recognizing the need for intubation or the need for supplemental oxygen.

Doctors can use collective learning to optimize diagnoses, help patients receive effective care faster - and without giving away access to their private personal data. With wider implementation of our Collective Learning network, we have the ability to rapidly and efficiently combine information from hospitals across the globe to vastly improve prognostic predictions and ensure patients are given the right care.

Signs agents

Traffic signs with the ability to communicate with vehicles will add additional insights for their journey.

Vehicles have one or more software agents that search the local area for information relevant to their journey. And they can see the world in a sort of augmented reality.

What might start as a simple communication between signs and vehicles opens up new economic opportunities as agents become more knowledgeable and signs become value centers in their own right.

Supply Chains

The intelligent supply chain will allow business to analyze future patterns, enabling them to navigate disruptions months in advance and preempt changes in customer buying patterns.

Artificial intelligence and blockchain technology will help companies to make sweeping efficiencies. For example, AI can utilize real-time information to help firms choose the best partner to trade with or to warn manufacturers about the need to conduct maintenance on a component of a delivery truck.

Transport & mobility

Today’s transport systems are largely self-service where individuals have to do a lot of work just to get from A to B. Whilst we all have an expanding selection of tools in our pockets, they are requiring more and more of our time to use them.

In the Fetch.ai world, Autonomous Economic Agents do the work on your behalf, operating on your preferences and learning as they go, adjusting in real-time to any unforeseen consequences.

An openly accessible, real-time infrastructure for sharing insights about the state of the transportation would create wealth, increase productivity and drive economic growth by allowing the sale and use of knowledge about the demand for, and supply of, mobility.

Rail

Fetch.ai's decentralized network of autonomous agents can represent all of the trains and stations in the UK, enabling it to indicate the live position of all the trains in real time.

Agents can find, negotiate and transact with one another to autonomously provide you with instant, personalized updates, ensuring that your journey is seamless - even when unforeseen circumstances occur.

Smart parking & congestion solution

In a smart city, rather than driving into a parking lot hoping to find a space, an autonomous agent within your car will search and communicate with parking agents to find the nearest available space to your destination, book it for you before directing you to it. When you come back to your car and drive off, your car agent checks out of the parking lot, calculates the payment and makes it for you, removing the hassle of parking tickets.

This simple act of finding you a parking space not only ensures you make your appointment on time, it also will transform congestion within cities. In 2018 in the US, $87 billion was lost to the economy due to traffic jams with 30% of cars in the most congested cities looking for parking spaces.

Smart eMobility & Electric Vehicle Infrastructure

The next generation of cars are going to be electric. In order to have sufficient supply to meet this surge in demand for electricity, there will need to be huge changes to the existing infrastructure.

Fetch.ai’s intelligent ecosystem will allow the agent within your car can seek out the nearest charging station, book your space and direct you there, saving the hassle of having to wait your turn at a filling station.

As the switch to electric vehicles (EVs) gains pace, more and more users will be seeking out places to recharge and the smart optimization technology will ensure that increased demand is met by the nearest available supply.

In addition, the ecosystem will allow you to choose not only an available charging point but direct you to one that has say a coffee shop or a playground nearby, making your stop more enjoyable and productive while you top up your car.

Thermometer Agents

The global supply chain analytics market is estimated to be worth $9.2 billion by 2024. Autonomous agents equipped with thermometer skills can enhance the sector.

The creation of an unmodifiable audit trail of the recorded temperature history has numerous benefits. For example, wholesalers can use agents to check the temperature on their distribution trucks remains constant. If it doesn’t, they can implement additional measures to make sure their food arrives in the best condition. There is, after all, a strong economic incentive to do so. If the food they provide arrives in better condition than that supplied by their competitors, their profits will rise when retailers subsequently request larger orders.

Energy

The way we consume energy today is suboptimal. We have very static pricing which doesn’t reflect reality at all. Consumers have dozens of electronic devices in their home, but no way to optimize and manage their usage and pricing.

And it’s not just a consumer problem, energy companies have networks of massive peaks and troughs which if flattened would benefit them immensely.

Fetch.ai enables connectivity of all these devices through the use of digital representatives called Autonomous Economic Agents. Energy companies could offer discount incentives for energy consumed in troughs, creating a new dynamic marketplace. Whilst the consumer will automatically receive the best deal for them as their agents manage their consumption based on their own preferences.

Smart Homes

A study by Fetch.ai and Imperial College London has demonstrated how Fetch.ai’s autonomous agents can use a new deep reinforcement learning technique to lower daily domestic energy costs by nearly 20%.

At present, autonomous energy systems rely on generation and consumption models that forecast the amount of energy that will be required by the user the following day. Such an approach is hindered by its lack of flexibility when circumstances inevitably change. The innovative approach adopted by Fetch.ai is model-free and utilizes smart meter data to achieve real-time autonomous energy control and reduce costs.

It will enable smart energy grids efficiently utilize renewable energy sources and help customers reduce their energy bills.

Decentralized Train Network

Fetch.ai's decentralized network uses autonomous agents to deliver tailored travel experiences. By using our world leading technology, passengers will be updated with optimized routes in real time to ensure their journeys are as fast, comfortable and seamless as possible.

This is made possible by Fetch.ai's unique autonomous economic agent technology supported by AI and machine learning and a high performance underlying ledger that supports advanced smart contracts.

Publications

We have a range of Peer-reviewed papers and Publications that display practical utility of the Fetch.ai technology.

One example is this pricing mechanism that aligns incentives of agents who exchange resources on a decentralized ledger with the goal of maximizing transaction throughput. Subdividing a blockchain ledger into shards promises to greatly increase transaction throughput with minimal loss of security.

See more examples of our full range of publications and peer-reviewed papers here here