Tech
These two founders left Goldman and Meta to build voice AI for markets everyone else overlooked
Customer support and service are among the hottest sectors in voice AI right now. But building a product that sounds human and responds without noticeable delay turns out to be much harder in some markets than others — and most of the major players weren’t built with Africa and the Middle East in mind.
AethexAI, a startup founded last year to close that gap, has raised $3 million in pre-seed funding led by 4DX Ventures, with participation from Enza Capital, Dorm Room Fund, Mojo Ventures, and Stanford GSB 26 Fund. Individual investors include Stanford faculty, telecom executives, and AI researchers from Anthropic.
Rather than using existing orchestration tools like Vapi and LiveKit, the company built its own small model and orchestration layer from scratch to handle the localized dialects of English, French, and Arabic spoken across its target markets — a decision driven, as we’ll get to, by the particular demands of operating in the region.
The company is also launching its platform for enterprises to try out its tech and sign up for its services, along with APIs and SDKs for developers to experiment with its models.
The startup was founded by Mariama Diallo and Ayooluwa Odemuyiwa. CEO Diallo worked at Goldman Sachs and later joined YC-backed ModelML as a product and growth hire. CTO Odemuyiwa graduated from Caltech, worked at Meta, and enrolled at Stanford Business School before co-founding the company. The pair wanted to build something for emerging markets and started looking for opportunities.
Businesses around the world are racing to adopt AI tools to automate parts of their operations. But that doesn’t always work out. In Egypt, a call center automated a significant share of its calls, but rolled the system back because of poor results, the founders found. Several support centers in Africa told them that finding and hiring engineers to automate calls at the right cost was a persistent headache.
“The latency and jitter that we saw on automated calls in this region were outrageous. If we had become orchestrators, we might have had to use large models that were hosted outside the region, resulting in higher latency. We realized that in order for this to work, we have to use very small models and cut latency at every step,” Odemuyiwa told TechCrunch about the decision to build the company’s own models and orchestration layer.
AI labs that deploy their latest models usually spend millions training them and acquiring data. AethexAI found a solution for both. Rather than chasing the largest possible models, it decided that small models are enough to tackle the latency problem while maintaining accuracy and developed its own Kora series, with parameters ranging from 300 million to 1.7 billion. That’s a fraction of the size of the LLMs, which is precisely the point.
To train these models, the startup used anonymized recordings from a call center partner. It also shipped hard drives to radio stations across Africa to collect more audio data. To keep costs down, it built a contributor network of university students to annotate data and pronounce local names. As a result, the startup says, it’s now handling more than 17,000 calls per day.
On the business side, the company is taking care to walk clients who are new to voice AI through the process, offering onsite demos and workshops to help them identify the best use cases for automation.
“We always tell customers that we cannot be everything for everybody right now. We’re small. When we start talking to a company, we ask them to pick one use case that is the most important to them to start [with],” Diallo said.
The startup is open to working across all industries, but at the moment, a big part of its use cases involves calls for debt collection, customer activation, or KYC — Know Your Customer verification, the standard identity-checking process used by banks and telecoms. The company is hiring forward-deployed engineers on a contract basis to serve local markets and building channel partnerships with telecoms providers to handle telephony for voice AI calls. Plug-and-play solutions, it says, simply won’t work here.
Walter Badoo, co-founder and managing partner of 4DX Ventures, argues that the Africa and Middle East market is fundamentally different from the markets most voice AI companies were built to serve.
“Enterprises in Africa and the Middle East process roughly three times the call volume of their Western counterparts, as voice is still the dominant channel for customer interaction,” he said. “Incumbent systems were built for Western markets characterized by high-end GPU infrastructure, standard English and European speech environments, and enterprise workflows common in the US and Europe. That creates real gaps when enterprises need systems that handle dialects, code-switching, and informal speech patterns, and that work within their existing telephony infrastructure and their actual price points.”
Put another way, while companies like ElevenLabs, Deepgram, Sierra, and Cognigy are expanding globally at a fast pace, the markets they were built for and the markets they are entering aren’t always the same thing. Startups like AethexAI are betting that the gaps — models specialized in local dialects, on-the-ground partnerships, infrastructure built for the region — represent a market opening that the giants have neither the incentive nor the architecture to close.
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Tech
The world’s largest privately owned laser just turned on
Fusion startup Xcimer Energy on Wednesday flipped the switch on its Phoenix laser system, which the company says is the largest privately owned example in the world.
Xcimer’s approach to fusion power is modeled after the National Ignition Facility (NIF), which proved in December 2022 that a controlled fusion reaction could release more power than required to ignite it.
The NIF trained 192 laser beams on a fuel target smaller than a pencil eraser. The energy from the lasers hit the gold target. As the lasers obliterate the gold target, their energy is converted into X-rays, which are focused on the fuel pellet inside, compressing it until atoms in the fuel fuse and release energy.
The company is betting that more powerful, less complex lasers will help turn NIF’s concept for fusion power into something more profitable.
Xcimer’s plans for a fusion power plant call for two lasers capable of firing in microsecond-long pulses. Light from those pulses will be fed through a compression system, of sorts, which will delivers the lasers’ energy to the fuel target in nanoseconds. The quicker the fuel is compressed, the more likely it is to generate usable fusion reactions.
Phoenix is a step toward an eventual power plant. The system uses excimer amplification, similar to those used in semiconductor manufacturing but significantly more powerful. At full strength, the krypton-fluoride laser generates over 1 kilojoule of energy, Xcimer told TechCrunch, and its core is 38 meters long.
While that may be the most powerful privately owned laser, it’s still a fraction of what the company says it will need for a commercial power plant, which could exceed 12 megajoules.
Xcimer hopes to complete a prototype in 2028 before working on a larger system that it hopes will produce at least as much power as it consumes. Sometime in the mid-2030s, it is planning to build its first commercial scale power plant.
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Tech
Plex adds new social features ahead of a major price hike for its lifetime pass
Plex has come a long way from being just a personal media server. Over the past few years, it has transformed into a streaming hub, today featuring ad-supported content and movie rental options.
Now, the company is setting its sights on competing with social networking platforms like Reddit and Letterboxd: on Wednesday, Plex unveiled several social features aimed at changing how users interact with the platform.
Notable among these is Discussions, a community forum where users can post comments and talk about movies or TV shows. Plex is likely hoping this forum will create a dedicated space that challenges Reddit’s dominance when it comes to community discussions of movies and shows.
The company said it’s worked up a moderation system that uses a blend of AI and human input to moderate both visual and written content.
Another new feature is Lists, which lets users create, manage and share lists of their favorite movies and shows, react with emojis instead of simple star ratings, and share images. Later this year, Plex will add the ability to import existing lists from other platforms, and let users react and comment on their friends’ lists. Letterboxd and IMDb both offer user-generated lists.
Additionally, Plex is adding a new Match Score feature that predicts how much a user might enjoy a particular title based on their viewing habits and preferences.
“It looks at the things you watch and the way you rate them, and turns that into a simple percentage that tells you how closely a title lines up with what you tend to enjoy,” co-founder and chief product officer Scott Olechowski told TechCrunch. “The idea is to take the guesswork out of discovery, so instead of scrolling endlessly, you get a quick, personal read on whether something is likely to be for you.”
The platform is also adding Alerts that will notify users about new activities related to lists, movies, shows and film professionals they follow.
Lists are currently available to all Plex users, and Discussions is set to launch this month. Other features will be rolled out throughout the year.
The new features aim to create a more community-driven content discovery experience, allowing users to share recommendations, compare opinions and connect over their favorite shows and films.
“People are spending more time figuring out what to watch than ever before, and we’re seeing viewers are increasingly turning to friends, creators, and communities they trust for recommendations. Discovery has become a shared experience, and we think the products people use to find entertainment should reflect that,” Olechowski added.
The new features come as Plex is grappling with an increasingly competitive entertainment landscape where streaming companies and social media platforms together vie for people’s attention. Netflix and Disney+ have even launched short-form video content within their apps in a bid to farm daily engagement.
This isn’t Plex’s first foray into social networking. In 2023, the company launched “Discover Together,” which allowed users to create profiles and follow friends’ viewing activities. Last year, Plex rolled out public profiles and reviews for users.
However, it’s important to note that this update also coincides with a significant price hike for Plex’s Lifetime Plex Pass, which will cost $749.99 from July 1. The staggering increase certainly caught the attention of users, especially since Plex just last year increased the Pass’ price from $119.99 to $249.99.
Currently, Plex boasts over 42 million active users monthly across more than 180 countries and territories.
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Tech
Coralogix raises $200M on bet that someone needs to watch the AI agents
Coralogix, a Boston-headquartered software monitoring startup founded in Israel, has raised $200 million in a new funding round, betting that the rise of AI agents will drive demand for a new generation of tools to monitor, troubleshoot, and manage increasingly autonomous software systems.
The Series F financing comes just 11 months after Coralogix raised $115 million in a Series E round, a pace that reflects just how quickly investor appetite for AI infrastructure companies has accelerated. The new round values the startup at $1.6 billion post-money and was led by Advent and the Canada Pension Plan Investment Board (CPPIB), with participation from Greenfield Partners and Brighton Park Capital. The company has now raised a total of $550 million to date.
The investment comes as software companies race to adapt to the rise of AI agents, software systems that can autonomously write code, investigate problems, and complete tasks that would previously have required a human engineer. Coralogix is among a growing number of infrastructure firms betting that as AI systems move into production, demand will rise for tools that can monitor their behavior, troubleshoot failures, and provide the operational data needed to keep them running reliably. (The more autonomous software you deploy, the more you need to know when something goes wrong and why.)
Founded in 2014, Coralogix helps companies monitor the health and performance of software systems by collecting and analyzing operational data such as logs, metrics, and traces — essentially a continuous record of what a software system is doing and how it’s behaving. The platform is used by more than 5,000 customers worldwide, including IBM, Tradeweb, and JFrog, to detect outages, investigate incidents, and optimize applications.
The observability industry, where Coralogix competes with the likes of Datadog, New Relic, and Splunk, is being reshaped by the rise of AI. Vendors are increasingly embedding AI into monitoring and incident-response workflows as enterprises deploy more AI-powered applications and agents.
The shift is already changing how customers interact with Coralogix’s platform, co-founder and CEO Ariel Assaraf (pictured above, right) said in an interview. More than half of the startup’s enterprise customers now use either its AI agent, Olly, or their own AI models through command-line and agentic interfaces to investigate incidents and query operational data, he said.
“The interface layer is slowly getting eroded,” Assaraf told TechCrunch, observing that engineers are increasingly interacting with software through AI assistants and command-line tools rather than traditional dashboards. “Most of the usage is going to be around, ‘How do I connect my LLM to this? How do I operate this through my CLI?’” In plain terms, his customers are less interested in logging into a dashboard and more interested in asking an AI assistant what’s wrong.
The shift has coincided with strong growth for Coralogix. The startup grew revenue by more than 60% over the past year and now counts about 30 customers spending more than $1 million annually, Assaraf said, as it expands further into the enterprise market. The company surpassed $100 million in annualized revenue more than a year ago, Assaraf added, though he declined to disclose current figures
The startup employs more than 600 people globally, with about 100 based in India, home to its third-largest office after the U.S. and Israel. The India operation, Assaraf said, has evolved into a regional hub supporting customers across Asia while helping Coralogix expand into large domestic enterprises, including financial institutions.
Coralogix did not raise because it needed additional runway, Assaraf said, adding that the funding would be used to accelerate investment in AI-focused products, security offerings and global expansion.
“In the AI era, execution and speed matter more than any point-in-time valuation,” he said. “We wanted to accelerate, expand, and take a further step into this AI game that we believe we’re leading in our space.”
Coralogix does not currently expect to raise additional capital and is working toward profitability over the next few years, Assaraf said. The company is also preparing to operate with the financial discipline of a public company, he said, though he stopped short of committing to a timeline for an initial public offering.
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