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Fish Audio raises $50M seed to build AI voice models for creators and enterprises

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The market for AI-generated voice models is massive. Creative use cases require AI voice models to be more expressive, while enterprises looking to automate customer support and sales ops need them to be more steerable.

Palo Alto-based Fish Audio wants to cater to all of those use cases with its library of more than 15,000 natural language controls. Since launching last year, the startup today has more than 8 million people using the open-source or hosted versions of its models, and now generates annual recurring revenue of $21 million.

To continue building on that traction, the startup on Tuesday said it has raised $50 million in a seed round that was led by Coreline Ventures and Capital Today. The funding also saw participation from 359 Capital, Parable, Play Time, Alphalist Partners, Bayhouse Ventures, Carya Venture Partners, and HF0.

Fish Audio started as a small project by former NVIDIA researcher Shijia Liao, who, frustrated by non-expressive synthetic voices available on the market, trained a voice generation model on a single GPU, which he open-sourced. The Fish Speech repository on GitHub now has more than 31,000 stars, and is used by indie developers, video game designers, and creators.

The company has launched five models in the last year: four speech generation models and one speech-to-text model. It has open-sourced three of its speech generation models, but its latest S2.1 Pro model is available only through its paid API.

Fish Audio offers paid monthly plans suited for creators and teams that unlock a set number of minutes of generation, plus voice cloning features. The company also offers an enterprise version of its APIs and platform, and says organizations like HeyGen, Sanas and Plaud are already using it.

“Every enterprise has different use cases and different preferences. For example, companies like HeyGen, which use our voices to power AI avatars, want realism in voices; a gaming studio would want expressive voice for their characters; and voice agent companies like LiveKit want more natural-sounding and low-latency voices that are expressive enough for calls,” Cao said.

One way the startup has built its library of voices is by simply asking users to submit their own voices for training its models, and compensating them if their voices are used. That resulted in some trouble a few months ago, however, as some creators alleged that their voices were uploaded to Fish Audio without their consent. The startup had a DMCA content take-down process in place to address such concerns, but the take-downs themselves took a long time.

Fish Audio’s CEO and co-founder Rissa Cao told TechCrunch that the company has now automated the take-down process. Creators can easily submit a short voice sample or a contract to prove that an uploaded voice belongs to them, and their voice will be taken off the startup’s platform in less than 3 minutes, she said.

Still, that doesn’t prevent anyone from uploading an artist’s voice without their knowledge. And until the artist finds out, their voice will continue to be used on the platform until they file for it to be taken down.

Oskue Honda, a partner at Coreline Ventures, said a community-driven model only works when creators trust the platform.

“A community-centric approach can only become a durable advantage if creators trust the platform. That means consent, transparency, and attribution must be built into the product rather than treated as afterthoughts. I believe the industry needs to move toward verified voice ownership, clear licensing terms, easy reporting and takedown processes, and eventually revenue-sharing models where creators benefit financially when their voices are licensed or used commercially,” he said.

Cao said when the startup was only offering its product as an open-source project with plans for creators, it was running efficiently and didn’t need money. But it wanted to develop more advanced models, and also wanted to accommodate enterprises as investor interest was ramping up, which led it to seek capital.

Looking ahead, Fish Audio plans to release an audio understanding model this year. It’s also building a speech-to-speech model.

The speech generation market is crowded, with companies like ElevenLabs, WellSaid, Cartesia, Speechify, Async (previously Podcastle), and Krisp competing for creators and enterprises’ wallets.

According to Rico Mallozzi, a partner at 359 Capital, fine-grained controls for developers and cost-efficient model training will help Fish Audio compete better with big AI labs.

“I think what they’ve been able to build, state-of-the-art models, with the team they have, compared to some of these other well-funded AI labs or companies, is incredible. It shows their technical acumen in closing the gap between artificial-sounding and human-like voices,” Mallozzi told TechCrunch over a call.

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Cyera agrees to acquire Oasis Security for $1B to safeguard proliferating AI agents

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Data security company Cyera, which recently raised $600 million at a $12 billion valuation, announced Tuesday that it signed a letter of intent to acquire Oasis Security for approximately $1 billion in a deal expected to be paid mostly in cash, with the remainder in Cyera shares.

Oasis focuses on non-human identities, primarily AI agents. As the number of AI agents proliferates, companies must deploy cybersecurity software that monitors these agents’ behavior and grants them permission to access other software.

Founded in 2022, Oasis has raised about $195 million from Accel, Craft Ventures, Cyberstarts and other investors.

The deal highlights a surging market for cybersecurity providers defending enterprises against AI-weaponized threats.

Cyera, which shares investors Accel and Cyberstarts with Oasis, has been on an acquisition spree, recently purchasing Index Ventures-backed Ryft and the less-than-one-year-old Genie Security.

Post-acquisition, Cyera plans to integrate Oasis’s technology into a unified identity and data security platform.

Although Cyera recently surpassed $150 million in annual recurring revenue (ARR), the company is far from profitable, TechCrunch reported last month. The five-year-old company has raised about $2.3 billion in total funding.

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More Than 45,000 Software Flaws Reported as AI Reshapes Cybersecurity

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The number of software vulnerabilities being uncovered in 2026 is on pace to roughly double the total recorded in 2025, as AI tools become more effective at identifying cyber threats.

The National Vulnerability Database recorded 45,207 vulnerabilities between January and late July, a figure already approaching the total logged during all of 2025. At the current rate, this year is on track to record twice as many uncovered flaws.

The number of vulnerabilities being patched by major technology companies each month is also far higher than in comparable updates last year, according to reporting by Bloomberg. Oracle patched 1,449 vulnerabilities in its July update, up from 309 in the comparable update a year earlier. Microsoft, Google, and other major software providers have reported similar increases in the number of vulnerabilities being patched.

Concerns that AI could hand hackers a roadmap for breaking into vulnerable software have also not yet come to fruition, although many of the most advanced cyber tools remain outside public access. As more operators, including Google and Microsoft, launch their own cyber AI models and services, there is a risk that more bad actors will gain access to them.

Tech companies expand access to AI security models

Anthropic kickstarted the cyber AI market with the launch of Mythos to a select group of partners under its Glasswing initiative. OpenAI launched a similar cyber AI model a few weeks later, which experts believe is comparable to Mythos in sophistication.

Others are jumping on the bandwagon. Microsoft is launching its own security product, while Google has made one available to select partners.

These cyber AI services have been deployed by technology companies, large institutions, and governments to identify vulnerabilities in their own software. Mozilla was one of Mythos’ early partners and said in April that it had rapidly increased its vulnerability detection and patching through the tool.

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What security teams should do now

Some organizations, including the National Security Agency, are now using Mythos for offensive cyber planning. This opens the door for US adversaries to conduct similar offensive planning and vulnerability testing, particularly China, which subjected its geopolitical rival Taiwan to 2.6 million cyberattacks in 2025. Security experts warn that AI could increase the scale and speed of future cyber operations.

Cyber agencies linked to the Five Eyes intelligence-sharing alliance, which includes Australia, Canada, New Zealand, the UK, and the US, have said that the proliferation of AI cyber tools could transform the cyber landscape within months rather than years. They have warned that as cyber defense tools become more powerful, offensive cyber capabilities will also grow in sophistication and use, meaning businesses of all sizes will need stronger layers of protection.

Beyond bad actors and adversaries gaining access to offensive cyber tools, rogue AI may also pose a growing threat to businesses. As OpenAI revealed last week, rogue AI systems are becoming increasingly capable of escaping confinement and damaging the open web, with one of its unreleased cyber tools hacking the popular open-source platform Hugging Face. Many industry leaders have called for greater transparency around the cyber tools being developed and the risks they present, leaving businesses with little choice but to strengthen their defenses before these capabilities become more widely available.

For businesses, the rise in vulnerabilities being patched by major tech companies is no reason for complacency. As access to cyber AI models expands, offensive capabilities will grow, and defensive investment will need to keep pace.

Also read: How AI assistants could become the next major cybersecurity risk just by following the wrong instruction.

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Amazon Reportedly Plans to Consolidate Nova AI Models

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Amazon is reportedly looking to revamp its AI strategy, shifting from a wide portfolio of models for text, images, video, and multimodal tasks toward a single frontier model.

The ecommerce giant has been one of the main beneficiaries of the AI boom, with developers investing heavily in compute capacity from AWS. However, it has not seen similar gains in the AI model market, with several of its flagship models trailing the industry leaders in revenue and market share.

Amazon plans to deprecate several models, including Premier and Omni, the Canvas image-generation model, and the Reel video-generation model, according to a report by Business Insider. These could be consolidated into a single multimodal frontier model, potentially still under the Nova brand.

“As with any AI portfolio, we continually evolve our model lineup based on what customers need,” an Amazon spokesperson told Reuters. “We’re continuing to invest in and support the Nova models our customers rely on today. We’re also investing in the next generation of frontier model research.”

Amazon has also reduced headcount within its artificial general intelligence organization, according to. The cuts could support a more concentrated development strategy, although Amazon has not said that it is scaling back its broader ambitions to build frontier models in-house.

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Why AWS infrastructure may remain Amazon’s stronger AI play

Amazon, like Microsoft, has spent billions maintaining close relationships with leading AI developers OpenAI and Anthropic. It has invested $25 billion in Anthropic, alongside agreements that ensure the company uses AWS for some of its compute capacity, and has earmarked a further $20 billion for investment over time.

Amazon also brought GPT and Codex to AWS in April, ending Microsoft’s exclusivity over the models. This came shortly after Amazon finalized a $50 billion investment in OpenAI.

AWS revenue rose 28% year over year in the first quarter of 2026, reflecting continued demand for cloud and AI infrastructure, according to Amazon. Although that growth trailed Google Cloud and Oracle, AWS remains substantially larger by revenue.

However, like Microsoft, Amazon still wants its own portfolio of AI models for internal use and for sale to cloud customers. It recently expanded its Connect platform with four agentic services covering supply chain planning, recruitment, customer engagement, and healthcare administration.

The strategic retreat could also affect hardware products and services still in development. Amazon had reportedly been planning an AI-native smartphone that would allow users to access Alexa directly through the device, while plans for additional Alexa+ smart devices may also be reconsidered.

For AWS customers, the shift could mean Amazon focuses more heavily on supplying the infrastructure and third-party models they already use, rather than competing across every part of the AI market itself.

Also read: Amazon Raises $25 Billion in Bond Sale as AI Spending Accelerates

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