Gladia, an AI transcription and audio intelligence provider, launched Solaria, a next-gen automatic speech recognition (ASR) model designed to redefine real-time communications for call centers and other voice-first platforms.

Solaria now empowers businesses to enhance and expand their customer service operations with AI-powered voice technology that delivers unmatched language coverage—supporting 40+ languages previously inaccessible with other solutions—without compromising quality or speed.

While outsourcing has long been a cost reduction strategy in the call center industry, businesses now face a new, critical challenge: providing seamless, multilingual support at scale. With 49% of global executives reporting financial losses due to language barriers, the demand for scalable, high-quality multilingual solutions has never been greater.

“We’ve seen in the market a huge surge in voice AI. It’s like voice is part of our life again, and we are introducing a new product called Solaria, which is a model that is real time with advanced capabilities,” said Jean-Louis Queguiner, CEO of Gladia, in an interview with GamesBeat. “And it’s going to be the fastest on the market, and the most accurate in the market, covering 100 languages.”

The product also has features like real time sentiment analysis and real time translation, he said. It handles speech to text translation and transcription. This is important to do in real time for voice agents or call centers, where someone may have to answer a question that comes in with a different language.

Solaria: An enterprise-ready model for global customer experience

Solaria is a speech-to-text (STT) engine built for global scalability. Solaria was designed to meet the demands of today’s contact centers, where both AI automation and human agents need high-accuracy, low-latency, and real-time multilingual support to succeed.

The model achieves industry-leading results in speech recognition, delivering both accuracy and fast processing speed. Recent benchmarks show Solaria has reached an unmatched 94% Word Accuracy Rate (WAR) average in English, Spanish, French and other common languages, while maintaining an ultra-low latency of 270 millisecond, making the conversation feel natural and responsive.

While real-time speech-to-text is often measured by speed alone, accuracy and language coverage are equally crucial for businesses providing seamless services across regions.

Unlike other speech-to-text models that prioritize speed over usability, Solaria balances industry-leading accuracy and speed with unmatched language coverage—100 languages in total, with exclusive support for 42 languages not matched by competitors. For high-population markets and key outsourcing hubs like Bangladesh, India, and The Philippines, native-level accuracy in regional languages is now offered through Solaria.

With native-level transcription, real-time code-switching, and translation across all supported languages, businesses can expand into global markets without constraints.

Designed for enterprise-scale voice automation, Solaria delivers:

Best-in-class accuracy in high-population languages such as Tagalog, Bengali, Punjabi, Tamil, Urdu, Persian, and Marathi.

Ability to adapt the model to industry-specific terminology (like medical or financial jargon) and have it extract critical data, like names, addresses, and numericals.

Adaptive speech processing, ensuring high accuracy in noisy call center environments.

Enterprise-grade data security, in full compliance with GDRP, HIPPA, and SOC 2.

With the addition of Solaria to its product portfolio, Gladia allows businesses to enhance customer service by improving AI-powered voice agents, making IVRs and virtual assistants more reliable across multiple languages, while also optimizing human-assisted workflows with real-time transcriptions and translations to help agents provide more effective assistance.

“Speech is the most natural way to connect with the world—for the first time, automated speech recognition is closing the divide, enabling humans and AI to truly speak the same language,” said Jean-Louis Quéguiner, CEO of Gladia, in a statement. “With Solaria, we have made a breakthrough in AI-powered voice technology that unlocks new opportunities for businesses, driving efficiency and delivering more seamless, impactful customer experiences across diverse languages and markets. Solaria is built for next-generation voice platforms ready to lead this transformation on a global scale.”

Serving more than 700 enterprise customers worldwide, including Attention, Circleback, Method Financial, and VEED.IO, Gladia delivers enterprise-grade service and scalability, backed by dedicated support and infrastructure in the U.S. and Europe, guaranteeing reliable performance for mission-critical applications. Companies looking to scale globally, optimize operational costs, and enhance customer experiences can start building with Gladia’s API today.

As part of the Solaria launch, Gladia has partnered with LiveKit, a leading open-source developer framework for real-time AI voice agents, to power real-time, multilingual translation within AI-driven applications. This gives developers global language capabilities out of the box through seamless integration with Gladia’s API.

Following its $16 million Series A round in 2024 and today’s rollout of Solaria, Gladia has taken another critical step toward establishing itself as a leading end-to-end API audio infrastructure provider—combining speech recognition, generative AI, and voice generation capabilities to help enterprise users and developers tap into the full potential of real-time audio data.

Paris-based Gladia was founded in 2022 by Jean-Louis Queguiner (ex-OVHCloud) and Jonathan Soto (ex-MIT/Sigfox). Gladia’s product has been adopted by over 150,000 users and 700 enterprise clients—including industry leaders like Attention, Circleback, Method Financial, and VEED.IO.

There is a 300 millisecond delay between the moment you start speaking and the moment you receive the first event of voice being activated. It takes 100 milliseconds to do the transcription and so you have near instant results.

To improve the accuracy further, Queguiner said the company needs to train on more data. And it needs to work with the data augmentations to make the data more robust. The company has enterprise pricing in price but has not disclosed it yet. He said it will be among the most affordable solutions in the market.

The company has nearly 40 employees.

A new 3D-printed design could make an integral part of cooling systems like air conditioners or refrigerators smaller and more efficient, according to new research.   Heat exchangers are devices that whisk away heat, and they’re everywhere—used in data centers, ships, factories, and buildings. The aim is to pass as much heat as possible from one side of the device to the other. Most use one of a few standard designs that have historically been easiest and cheapest to make.  “Heat exchangers are at the center of the industrial economy. They’re an essential part of every machine and every system that moves energy,” says William King, a professor at the University of Illinois Urbana-Champaign and one of the authors of the new study. Existing designs tend to favor straight lines, right angles, and round tubes, he adds.   King and his colleagues used 3D printing to design a heat exchanger that includes features to optimize heat movement, like wavy walls and pyramid-shaped bumps, which wouldn’t be possible to make using traditional manufacturing techniques.  
The team had set out to design a system based on a common refrigerant called R-134a, which is commonly used in devices like air conditioners and refrigerators. When cold water lowers the temperature of the refrigerant, it changes from a gas to a liquid on its path through the device. That liquid refrigerant can then go on to other parts of the cooling system, where it’s used to lower the temperature of anything from a room to a rack of servers.  The best way to cool the refrigerant tends to involve building very thin walls between the two sides of the device and maximizing the amount of contact that the water and the refrigerant make with those walls. (Think about how much colder you’d get wearing a thin T-shirt and pants and lying down on ice than simply touching it with your gloved hands.)
To design the best possible heat exchanger, researchers used simulations and developed machine-learning models to help predict the performance of different designs under different conditions. After 36,000 simulations, the researchers landed on the one they decided to develop. Among the key components: small fins that jut out on the side of the device that touches the water, increasing the surface area to maximize heat transfer. The team also designed wavy passageways for the water to pass through—once again helping to maximize surface area. Simulations helped the researchers figure out exactly how curvy the passages should be and where precisely to place the fins. On the side of the devices where the refrigerant passes through, the design includes small pyramid-shaped bumps along the walls. These not only maximize the area for cooling but also help mix the refrigerant as it passes through and prevent liquid from coating the wall (which would slow down the heat transfer). After settling on a design, the researchers used a 3D-printing technique called direct metal laser sintering, in which lasers melt and fuse together a metal powder (in this case, an aluminum alloy), layer by layer. In testing, the researchers found that the heat exchanger created with this technique was able to cool down the refrigerant more efficiently than other designs. The new device was able to achieve a power density of over six megawatts per meter cubed—outperforming one common traditional design, the shell-tube configuration, by between 30% and 50% with the same pumping power. The device’s power density was similar to that of brazed plate heat exchangers, another common design in industry.   Overall, this device doesn’t dramatically outperform the state-of-the-art technology, but the technique of using modeling and 3D printing to produce new heat exchanger designs is promising, says Dennis Nasuta, director of research and development at Optimized Thermal Systems, a consulting firm that works with companies in the HVAC industry on design and research. “It’s worth exploring, and I don’t think that we know yet where we can push it,” Nasuta says. One challenge is that today, additive manufacturing techniques such as laser sintering are slow and expensive compared with traditional manufacturing; they wouldn’t be economical or feasible to rely on for all our consumer cooling devices, he says. For now, this type of approach could be most useful in niche applications like aerospace and high-end automotives, which could more likely bear the cost, he adds.  This particular study was funded by the US Office of Naval Research. Next-generation ships have more electronics aboard than ever, and there’s a growing need for compact and efficient systems to deal with all that extra heat, says Nenad Miljkovic, one of the authors of the study. 

Energy demand for cooling buildings alone is set to double between now and 2050, and new designs could help efficiently meet the massive demand forecast for the coming decades. But challenges including manufacturing costs would need to be overcome to help innovations like the one designed by King and his team make a dent in real devices. Another barrier to adopting these new techniques, Nasuta says, is that current standards don’t demand more efficiency. Other technologies already exist that could help make our devices more efficient, but they’re not used for the same reason.  It will take time for new manufacturing techniques, including 3D printing, to trickle into our devices, Natsua adds: “This isn’t going to be in your AC next year.”

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Imagine if a large team of 200 people could hold a thoughtful real-time conversation in which they efficiently brainstorm ideas, share knowledge, debate alternatives and quickly converge on AI-optimized solutions. Is this possible — and if so, would it amplify their collective intelligence? There is a new generative AI technology, conversational swarm intelligence (or simply hyperchat), that enables teams of potentially any size to engage in real-time conversations and quickly converge on AI-optimized solutions. To put this to the test, I asked the research team at Unanimous AI to bring together 50 random sports fans and task that large group with quickly creating a March Madness bracket through real-time conversational deliberation. Before I tell you how the experiment is going, I need to explain why we can’t just bring 50 people into a Zoom meeting and have them quickly create a bracket together. Research shows that the ideal size for a productive real-time conversation is only 4 to 7 people. In small groups, each individual gets a good amount of airtime to express their views and has low wait time to respond to others. But as group size grows, airtime drops, wait-time rises — and by a dozen people it devolves into a series of monologues. Above 20 people, it’s chaos.  So how can 50 people hold a conversation, or 250, or even 2,500?  Hyperchat works by breaking any large group into a set of parallel subgroups. It then adds an AI agent into each subgroup called a “conversational surrogate” tasked with distilling the human insights within its local group and quickly sharing those insights as natural dialog with other groups. These surrogate agents enable all the subgroups to overlap, weaving

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Another day, another announcement about AI agents. Hailed by various market research reports as the big tech trend in 2025 — especially in the enterprise — it seems we can’t go more than 12 hours or so without the debut of another way to make, orchestrate (link together), or otherwise optimize purpose-built AI tools and workflows designed to handle routine white collar work. Yet Emergence AI, a startup founded by former IBM Research veterans and which late last year debuted its own, cross-platform AI agent orchestration framework, is out with something novel from all the rest: an AI agent creation platform that lets the human user specify what work they are trying to accomplish via text prompts, and then turns it over to AI models to create the agents they believe are necessary to accomplish said work. This new system is literally a no code, natural language, AI-powered multi-agent builder, and it works in real time. Emergence AI describes it as a milestone in recursive intelligence, aims to simplify and accelerate complex data workflows for enterprise users. “Recursive intelligence paves the path for agents to create agents,” said Satya Nitta, co-founder and CEO of Emergence AI. “Our systems allow creativity and intelligence to scale fluidly, without human bottlenecks, but always within human-defined boundaries.” Image of Dr. Satya Nitta, Co-founder and CEO of Emergence AI, during his keynote at the AI Engineer World’s Fair 2024, where he unveiled Emergence’s Orchestrator meta-agent and introduced the open-source web agent, Agent-E. (photo courtesy AI Engineer World’s Fair) The platform is designed to evaluate incoming tasks, check its existing agent registry, and, if necessary, autonomously generate new agents tailored to fulfill specific enterprise needs. It can

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Brain-computer interfaces face a critical test Brain computer interfaces (BCIs) are electrodes put in paralyzed people’s brains so they can use imagined movements to send commands from their neurons through a wire, or via radio, to a computer. In this way, they can control a computer cursor or, in few cases, produce speech.   Recently, this field has taken some strides toward real practical applications. About 25 clinical trials of BCI implants are currently underway. And this year MIT Technology Review readers have selected these brain-computer interfaces as their addition to our annual list of 10 Breakthrough Technologies. Read the full story.
—Antonio Regalado
How do you teach an AI model to give therapy? —James O’DonnellOn March 27, the results of the first clinical trial for a generative AI therapy bot were published, and they showed that people in the trial who had depression or anxiety or were at risk for eating disorders benefited from chatting with a bot.I was surprised by those results. There are lots of reasons to be skeptical that an AI model trained to provide therapy is the solution for millions of people experiencing a mental health crisis. But their findings suggest that the right selection of training data is vital. Read the full story. This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Tech companies are warning their immigrant workers not to leave the USEmployees on high-skilled visas could be denied entry back into the States. (WP $)+ Officials are considering collecting citizenship applicants’ social media data. (Associated Press)2 OpenAI has closed one of the largest private funding rounds in historyIt plans to put the $40 billion cash injection towards building AGI. (The Guardian)+ The deal values OpenAI at a whopping $300 billion. (CNBC)+ The company also teased its first open-weight model in years. (Insider $) 3 SpaceX has launched a mission that’s never been attempted beforeIt’s taking private customers on an orbit between Earth’s North and South poles. (CNN)+ Crypto billionaire Chun Wang is footing the bill for the mission. (Reuters)+ Europe is finally getting serious about commercial rockets. (MIT Technology Review)

4 Some DOGE workers are returning to their old jobsThey’re quietly heading back to their roles at X and SpaceX. (The Information $)+ Top staff were placed on leave after denying DOGE access to their systems. (Wired $)+ Can AI help DOGE slash government budgets? It’s complex. (MIT Technology Review) 5 Amazon is going all-in on AI agentsIts new AI model Nova Act is designed to complete tasks such as online shopping. (The Verge)+ Why handing over total control to AI agents would be a huge mistake. (MIT Technology Review) 6 DeepMind is making it harder for its researchers to publish studies It’s reluctant to share innovations that rivals could capitalize on. (FT $) 7 Meet the protestors staking out Tesla dealershipsProfessors and attorneys have taken to the streets to fight back. (New Yorker $)+ Far-right extremists are turning up to defend the company. (Wired $) 8 TikTok’s hottest topic? Tariffs Content creators are eager to explain what tariffs are to confused audiences. (WSJ $)+ Donald Trump is threatening to instigate a new range of tariffs this week. (NY Mag $)+ How Trump’s tariffs could drive up the cost of batteries, EVs, and more. (MIT Technology Review) 9 Not everyone can look as cool as Nvidia’s Jensen HuangHis image has been co-opted to promote knockoff leather jackets. (404 Media) 10 Microsoft has killed off its Blue Screen of DeathGoodnight, sweet prince. (Vice)
Quote of the day “I think that it is one of the most beautiful spaces on the internet for someone to figure out who they are.”
—Amanda Brennan, an internet librarian who worked at Tumblr for seven years, is not surprised by the influx of younger users flocking to her former workplace, Insider reports. The big story The quest to protect farmworkers from extreme heat October 2024On July 21, 2024, temperatures soared in many parts of the world, breaking the record for the hottest day ever recorded on the planet.The following day—July 22—the record was broken again.But even as the heat index rises each summer, the people working outdoors to pick fruits, vegetables, and flowers have to keep laboring.The consequences can be severe, leading to illnesses such as heat exhaustion, heatstroke and even acute kidney injury.Now, researchers are developing an innovative sensor that tracks multiple vital signs with a goal of anticipating when a worker is at risk of developing heat illness and issuing an alert. If widely adopted and consistently used, it could represent a way to make workers safer on farms even without significant heat protections. Read the full story. —Kalena Thomhave
We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.) + Mescal! Dickinson! Quinn! Keoghan! I’m very excited for the forthcoming Beatles biopics, even if we have to wait three years.+ How to cook a delicious-looking basque cheesecake.+ TikTokers have taken to rubbing banana peel on their faces: but does it actually do anything?+ Spring has barely sprung, but fashion is already looking towards fall.

Tech companies are always trying out new ways for people to interact with computers—consider efforts like Google Glass, the Apple Watch, and Amazon’s Alexa. You’ve probably used at least one. But the most radical option has been tried by fewer than 100 people on Earth—those who have lived for months or years with implanted brain-computer interfaces, or BCIs. Implanted BCIs are electrodes put in paralyzed people’s brains so they can use imagined movements to send commands from their neurons through a wire, or via radio, to a computer. In this way, they can control a computer cursor or, in few cases, produce speech.   Recently, this field has taken some strides toward real practical applications. About 25 clinical trials of BCI implants are currently underway. And this year MIT Technology Review readers have selected these brain-computer interfaces as their addition to our annual list of 10 Breakthrough Technologies, published in January.
BCIs won by a landslide to become the “11th Breakthrough,” as we call it. It beat out three runners-up: continuous glucose monitors, hyperrealistic deepfakes, and methane-detecting satellites. The impression of progress comes thanks to a small group of companies that are actively recruiting volunteers to try BCIs in clinical trials. They are: Neuralink, backed by the world’s richest person, Elon Musk; New York–based Synchron; and China’s Neuracle Neuroscience. 
Each is trialing interfaces with the eventual goal of getting the field’s first implanted BCI approved for sale.  “I call it the translation era,” says Michelle Patrick-Krueger, a research scientist who carried out a detailed survey of BCI trials with neuroengineer Jose Luis Contreras-Vidal at the University of Houston. “In the past couple of years there has been considerable private investment. That creates excitement and allows companies to accelerate.” That’s a big change, since for years BCIs have been more like a neuroscience parlor trick, generating lots of headlines but little actual help to patients.  Patrick-Krueger says the first time a person controlled a computer cursor from a brain implant was in 1998. That was followed by a slow drip-drip of tests in which university researchers would find a single volunteer, install an implant, and carry out studies for months or years. Over 26 years, Patrick-Krueger says, she was able to document a grand total of 71 patients who’ve ever controlled a computer directly with their neurons.  That means you are more likely to be friends with a Mega Millions jackpot winner than know someone with a BCI. These studies did prove that people could use their neurons to play Pong, move a robot arm, and even speak through a computer. But such demonstrations are of no practical help to people with paralysis severe enough to benefit from a brain-controlled computer, because these implants are not yet widely available.  “One thing is to have them work, and another is how to actually deploy them,” says Contreras-Vidal. “Also, behind any great news are probably technical issues that need to be addressed.” These include how long an implant will last and how much control it offers patients.

Larger trials from three companies are now trying to resolve these questions and set the groundwork for a real product. One company, Synchron, uses a stent with electrodes on it that’s inserted into a brain vessel via a vein in the neck. Synchron has implanted its “stentrode” in 10 volunteers, six in the US and four in Australia—the most simultaneous volunteers reported by any BCI group.  The stentrode collects limited brain signals, so it gives users only a basic on/off type of control signal, or what Synchron calls a “switch.” That isn’t going to let a paralyzed person use Photoshop. But it’s enough to toggle through software menus or select among prewritten messages. Tom Oxley, Synchron’s CEO, says the advantage of the stentrode is that it is “as simple as possible.” That, he believes, will make his brain-computer interface “scalable” to more people, especially since installing it doesn’t involve brain surgery.  Synchron might be ahead, but it’s still in an exploratory phase. A “pivotal” study, the kind used to persuade regulators to allow sales of a specific version of the device, has yet to be scheduled. So there’s no timeline for a product.   Neuralink, meanwhile, has disclosed that three volunteers have received its implant, the N1, which consists of multiple fine electrode threads inserted directly into the brain through a hole drilled in the skull.  More electrodes mean more neural activity is captured. Neuralink’s first volunteer, Noland Arbaugh, has shown off how he can guide a cursor around a screen in two dimensions and click, letting him play video games like Civilization or online chess. Finally, Neuracle says it is running two trials in China and one in the US. Its implant consists of a patch of electrodes placed on top of the brain. In a report, the company said a paralyzed volunteer is using the system to stimulate electrodes in his arm, causing his hand to close in a grasp. 
But details remain sparse. A Neuracle executive would only say that “several” people had received its implant. Because Neuracle’s patient count isn’t public, it wasn’t included in Patrick-Krueger’s tally. In fact, there’s no information at all in the medical literature on about a quarter of brain-implant volunteers so far, so she counted them using press releases or by e-mailing research teams.
Her BCI survey yielded other insights. According to her data, implants have lasted as long as 15 years, more than half of patients are in the US, and roughly 75% of BCI recipients have been male.  The data can’t answer the big question, though. And that is whether implanted BCIs will progress from breakthrough demonstrations into breakout products, the kind that help many people. “In the next five to 10 years, it’s either going to translate into a product or it’ll still stay in research,” Patrick-Krueger says. “I do feel very confident there will be a breakout.”