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Meet the Six Firms Using Generative AI to Reimagine Customer Engagement in the Future



Meet the Six Firms Using Generative AI to Reimagine Customer Engagement in the Future

The development and application of generative AI-powered products and experiences saw a major advancement in 2023, a breakthrough year for the field.

AI was integrated into client-facing applications in a variety of industries, including healthcare, retail, education, and more, to help companies create innovative experiences that strengthen customer bonds.

Twilio announced its inaugural AI Startup Searchlight, a global search for businesses leveraging generative AI to develop better, more trustworthy customer communications, in an effort to uncover the most creative and promising AI-powered customer experiences. Twilio sought international companies with less than $50 million in venture capital that already had a working product or functional demo and were creatively integrating generative AI into Twilio channels like voice, email, and WhatsApp.

The judges consisted of Twilio CEO Khozema Shipchandler, Twilio Ventures director Brandon Leen, and WAYE creator and futurist Sinead Bovell. The judges sought out nominees who had shown extraordinary inventiveness, made the most of the AI opportunity, and had a significant impact on the direction of AI-powered customer experiences.

Twilio narrowed down the numerous applications to six standout firms that were utilizing useful generative AI applications in the fields of logistics, hospitality, healthcare, and more. Each of these awardees developed novel, creative solutions that made use of data, communications, and AI’s capabilities to address specific business difficulties and produce long-term advantages for their clients.

The recipients of the award showcased remarkable progress in the direction of reliable communication and client interaction, demonstrating the genuine potential of generative artificial intelligence.


The founding principle of Arist was to simplify and make workforce education easily accessible. Arist transforms how teams communicate and meets with employees on their chosen channels, such as Slack, SMS, and WhatsApp, by utilizing AI and Twilio.

With the help of Arist’s content creation assistance, users can create new courses using pre-existing information. Arist is able to motivate learning efforts with their clients and staff and inspire learner confidence by efficiently capturing information and value that has already been developed.

Over a million courses have already been sent to eminent international firms including BMO, DoorDash, the World Health Organization, and others using the text message learning platform Arist has previously developed. Arist intends to use AI to personalize learning for clients and deliver efficient communications throughout the employee education journey. In the future, the company will roll out capabilities such as learner response analysis and adaptive learning.


An estimated 3.5 million workers in the US alone are engaged in repetitive back-office and logistics work. FleetWorks is able to automate the most time-consuming aspect of logistics management—live order issue handling—by adding AI technology on top of traditional systems.

Fleetworks made a copilot for all of their work by utilizing Twilio’s voice API in addition to its IVR and SIP trunking features. This allowed UberFreight and other companies to optimize their operations.

The business uses automation to handle freight movement coordination, doing away with the need for many phone conversations and emails that were previously necessary. Fleetworks relies heavily on artificial intelligence (AI) to deliver excellent customer service and free up their clients’ time to concentrate on efficient transportation.


Milo, which stands for “my important loved ones,” is a startup that offers parents an AI partner to assist in handling the invisible burden of raising and managing a family. According to Milo, parents spend much too much time and energy on low-value but essential chores like organizing, planning, and information management—tasks that are more suited for computers and artificial intelligence (AI) than for human brains.

Using Twilio’s messaging API, busy parents can send voice recordings, SMS reminders, and calendar invites to their loved ones, all of which are combined into Milo, which then summarizes the pandemonium for the family as a whole.

To assist in managing the schedules of young children and their parents, Milo created a virtual copilot by combining the most advanced LLM capabilities with a human in the loop. With funding from OpenAI, Milo’s AI technology also improves with time. It adjusts based on user response to the needs and preferred methods of information delivery, saving parents a great deal of time.

Next Order

Next Order is a restaurant software supplier that provides a direct ordering channel, connections with delivery platforms, and a cloud-based point-of-sale system. Their goal is to improve working conditions for restaurant employees and make business ownership easier.

AI contributes to the expansion of this goal. Next Order automates client interactions and offers restaurants insightful data by utilizing AI in conjunction with Twilio’s Programmable Messaging, Email API, Voice, IVR, and SIP Trunking. This AI can provide more consistent customer service for diners. This technology helps restaurants make better business decisions, save expenses, and enhances the dining experience for patrons during peak hours.

More than 1,000 restaurants who previously battled with limited access to large-chain restaurant technology and were dependent on antiquated service providers are now better positioned to compete and provide outstanding customer experiences thanks to Next Order.

Rely Health

Rely Health strives to keep patients from becoming disoriented in the complicated world of healthcare. Rely Health’s AI-powered companion collaborates with clinical personnel to assist patients in optimizing in-network retention, gaining access to clinical charting, and comprehending the viability and well-being of their healthcare plans.

Rely Health uses artificial intelligence (AI) to improve virtual chatbots, give personalized solutions, and improve predictive analytics for improved patient outcomes. It is driven by real-time data and a strong dedication to patient care. Rely reaches patients on their preferred channel by utilizing APIs (including email and voice) and Twilio’s SIP trunking and IVR solutions.

AI has a big future in patient care, and Rely Health is confident in it. Their technology, which is now present in several states and is still expanding, has the potential to bridge the gap in manual treatment and enhance patient communications for thousands of patients.

The goal of, a customer interaction platform that offers small to mid-sized enterprises virtual receptionists and sales outreach solutions, is to address the difficulties that small businesses encounter. uses automation and technology to assist small and medium-sized enterprises increase efficiency. Since AI makes their agents feel more like an organic extension of a company than an external vendor, views AI as the “secret sauce” of their operation. To reach clients on their preferred channel, they leverage SIP trunking, IVR solutions, and Twilio APIs for voice and messaging.

Agents for frequently handle complex consumer transactions. These AI-guided agents are most suited to handle these exchanges because’s technology is inherently compassionate and emotionally intelligent. AI supports their agents in managing calls, chats, and text messages by giving them the crucial context they need to give excellent customer care on behalf of their clients.


Timescale Introduces Advanced AI Vector Database Extensions for PostgreSQL



A PostgreSQL cloud database provider recently declared the availability of two brand-new, open-source extensions that greatly improve the scalability and usability of its data retrieval from vector databases for artificial intelligence applications.

Using PostgreSQL, an open-source relational database, for vector data retrieval is made possible by the new extensions, pgvectorscale and pgai. This is essential for developing AI applications and specialized contextual search.

AI programmers can add data to high-dimensional arrays using vector databases, connecting them based on their contextual relationships with each other. Vector databases store data using contextualized meanings, where the “nearest neighbor” can be used to connect them, in contrast to typical relational databases. For example, a cat and a dog have a closer meaning as family pets than does an apple. When an AI searches for semantic data, including keywords, documents, photos, and other media, this speeds up the information-finding process.

Timescale’s AI product lead, Avthar Sewrathan, told SiliconANGLE in an interview that while most of this data is kept in very popular, high-performance vector databases, not all of the data used by services is kept in vector databases. Thus, in the same context, there are occasionally several data sources.

“AI is being incorporated into every organization in the world, in some form or another, whether through the development of new apps that capitalize on the power of large language models or through the redesign of current ones,” stated Sewrathan. Therefore, CTOs and technical teams must decide whether to employ a distinct vector database or a database they are already familiar with while figuring out how to use AI. Encouraging Postgres to be a better database for AI is the driving force behind these enhancements.

Building on the open-source foundation of the original expansion, pgvectorscale, enables developers to create more scalable artificial intelligence (AI) applications with improved search performance at a reduced cost.

According to Sewrathan, it incorporates two innovations: Statistical Binary Quantization, which is an enhancement of standard binary quantization that helps reduce memory use, and DiskANN, which can offload half of its search indexes to disk with very little impact on performance. DiskANN is capable of saving a significant amount of money.

In comparison to the widely used Pinecone vector database, PostgreSQL was able to attain 28x lower latency for 95% and 16x greater query throughput for approximate nearest neighbor queries at 99% recall, according to Timescale’s benchmarks of pgvectorscale. Since pgvectorscale is written in Rust instead of C, PostgreSQL developers will have more options when developing for vector support.

The next addition, pgai, is intended to facilitate the development of retrieval-augmented generation, or RAG, solutions for search and retrieval in applications using artificial intelligence. In order to lessen the frequency of hallucinations—which occur when an AI boldly makes erroneous statements—RAG blends the advantages of vector databases with the skills of LLMs by giving them access to current, reliable information in real-time.

Building precise and dependable AI systems requires an understanding of this technique. OpenAI conversation completions from models like GPT-4o are built directly within PostgreSQL with the first release of pgai, which facilitates the creation of OpenAI embeddings rapidly.

The most recent flagship model from OpenAI, the GPT-4o, offers strong multimodal capabilities like video comprehension and real-time speech communication.

According to Sewrathan, PostgreSQL’s vector functionality builds a strong “ease of use” bridge for developers. This is significant because many firms currently use PostgreSQL or other relational databases.

Because it streamlines your data architecture, adding vector storage and other features via an extension is much easier, according to Sewrathan. “One database is all you have.” It has the ability to store several data kinds simultaneously. That has been extremely beneficial because without it, there would be a great deal of complexity, data synchronization, and data deduplication.

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Apple is Updating Siri and Giving it new Generative AI Capabilities



The release of iOS 18, macOS updates, and other significant announcements marked the beginning of Apple’s yearly Worldwide Developers Conference (WWDC) 2024 yesterday. The launch of the eagerly awaited new iteration of Apple’s voice assistant, Siri, was the most notable of these. By means of a brand-new system dubbed “Apple Intelligence,” the revised Siri is equipped with stronger generative AI capabilities.

With these enhanced artificial intelligence capabilities, Apple has enabled Siri to perform better, becoming more contextually aware, natural, and deeply ingrained in the Apple environment. The incorporation of ChatGPT into this change promises more intelligent responses and new AI-powered functionality. The updated Siri, according to Apple, is “more natural, more contextually relevant, and more personal,” and it may speed and streamline routine activities. Let’s examine each of the recently added features of Apple’s sophisticated voice assistant in depth.

New style

Activating a bright light that encircles the screen edges is just one of the many features of the redesigned Siri. Increased user engagement is the goal of this graphic makeover. Apple has added onscreen awareness to Siri, which goes beyond aesthetics and allows the virtual assistant to take actions based on what’s on the screen. Customers may now ask Siri to locate and act upon book recommendations received via Messages or Mail, or to add a new address straight from a text message to a contact card.

An enhanced capacity for linguistic comprehension

Apple’s Siri now features richer language-understanding capabilities, allowing it to process and respond to user commands more naturally. This improvement ensures Siri can maintain context across multiple interactions, even if users stumble over their words. Additionally, users can now type to Siri and switch seamlessly between text and voice inputs, offering more flexible ways to interact with the assistant.

Siri’s compatibility with outside applications

Because of the new App Intents API, one of the most notable aspects of the new Siri is its ability to perform actions in a variety of apps—both those developed by Apple and those by outside developers. This means that programmers can give Siri specific commands to execute within their apps. For example, users may ask Siri to “send the photos from the barbecue on Saturday to Malia” using a message app, or “make this photo pop” in a photo editing software. Interactions between various apps and services can now be done more easily thanks to this added capabilities.

Apple and openAI collaborate to power Siri

Notably, Apple and OpenAI have teamed to enhance Siri’s generative AI capabilities by integrating ChatGPT technology. With this integration, Siri can respond with greater sophistication and manage jobs that are more complicated. Users of Apple’s Mac and iPhone operating systems will be able to access ChatGPT through updates, which will improve features like text and content production. Apple’s plan to integrate cutting-edge AI technologies and maintain its competitiveness in the IT industry includes this relationship.

Apple uses sophisticated Siri to protect user privacy

Users can be reassured by Apple that Siri and the new AI capabilities in its devices will respect its strict privacy policies. While the company will rely on the cloud without storing user data there for more power-intensive operations, certain AI functions will process data directly on the device. This strategy aligns with Apple’s goal of striking a balance between improved usefulness and consumer privacy.

The new Siri will only be available on a few chosen Apple devices

The newest iPads, Macs, and iPhones will be the only devices that can utilize this sophisticated Siri experience. Most of Siri’s new features, which are powered by Apple Intelligence, will only be available on the iPhone 15 Pro, iPhone 15 Pro Max, iPads, and Macs with M1 CPUs or later.

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EU Introduces an AI-Driven “Digital Twin” of the Planet



Today, the European Commission unveiled the initial iteration of Destination Earth (DestinE), an AI-driven simulator designed to increase the precision of climate projections.

Two models—one for extreme weather events and another for adapting to climate change—are included in the initial edition of DestinE. With the use of these models, the Earth’s climate will be closely observed, predicted, and simulated.

According to EU antitrust chief Margrethe Vestager, “DestinE means that we can observe environmental challenges which can help us predict future scenarios – like we have never done before.”

The LUMI supercomputer located in Finland is one of the high-performance computers (EuroHPC) that power DestinE. To accelerate data processing, the developers have integrated this with AI.

Vestager stated, “This first phase shows how much we can achieve when Europe puts together its massive supercomputing power and its scientific excellence.”

The main model will, however, probably change over time, and by the end of this decade, a digital duplicate of the Earth should be finished.

Digital Twin of the Earth

Want to test how a heatwave will impact food security? Or if a storm will flood a certain city? Or the best places to position your wind farm? All of that could be possible using the digital twin of the Earth.

The digital twin uses a sizable data lake to fuel its simulations and forecasts. Satellites like those used in the EU’s Copernicus program are the source of this data. It will also originate from vast amounts of public data as well as IoT devices situated on the ground.

Future iterations of the digital twin of Earth will incorporate data from forests, cities, and oceans, pretty much anyplace on Earth that scientists can analyze data.

In 2022, the EU launched DestinE for the first time. The digital twin will be constructed with funding exceeding €300 million.

With today’s launch, the first phase comes to a conclusion and the second phase begins, with a combined funding commitment of over €150 million for both.

As the final Digital Europe program 2025–2027 is presently being prepared, its approval will determine the funding for the third stage.

Organizations working on this kind of technology are not limited to the EU. The Earth-2 digital replica was introduced by Nvidia in March. As stated by the powerhouse in chip manufacturing, the model is currently being used by the Taiwanese government to more accurately forecast when typhoons will hit land.

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