Openvibe’s clever app that integrates multiple open social networks including Bluesky, Mastodon, Nostr, and Threads, just got a boost toward its future development. The company on Tuesday announced that it has received outside investment of $800,000 in a round led by Czech Founders VC, which includes backing from WordPress.com and Tumblr parent company, Automattic, as well as Tensor Ventures.
Czech Founders VC and former CTO of Mews Jan Široky also invested separately from his firm.
Launched in 2024, Openvibe initially supported three of the more prominent open social networks, all of which operate using different protocols: Mastodon uses ActivityPub, Bluesky runs on AT Protocol, and Nostr powers a number of third-party apps. Openvibe later added support for Instagram Threads, as that app became further integrated with ActivityPub and opened itself up to the developer community.
As CEO Matej Svancer explained at the time, the idea behind his app was to offer users a more friendly and “easy-to-use gateway” to the open social web. Because of the different protocols these networks utilize, it can be difficult for newcomers who end up having to switch apps or limit their engagement to just their preferred platform.
But Openvibe doesn’t just let people stay connected with friends across all these services in a combined timeline, it also allows cross-posting to multiple networks at once.
With the added capital, Svancer plans to accelerate product development, expand Openvibe’s user base, work on integrations with other social platforms, refine the user interface, and more.
In addition, Automattic’s investment is worth noting, as the company historically backs projects in the open source space, particularly those designed to compete with Big Tech. (Unfortunately, Automattic CEO and WordPress co-creator Matt Mullenweg has created a lot of division and drama within the WordPress community over the past several months, which has some questioning his commitment to open source values.)
Still, Openvibe’s fundraising signals that there is some appetite among investors for backing apps and services that are taking advantage of the new open social protocols. Recently, for example, celeb investor and entrepreneur Mark Cuban put out a call for video apps building on Bluesky’s AT Protocol. Bluesky has also raised funding, most recently its $15 million Series A last fall.
Openvibe is available as a free app on iOS and Android but plans to later introduce a subscription plan to generate revenue.
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Falls are common for older people living semi-independently. According to the CDC, they’re the leading cause of injury for adults aged 65 and up. On average, about 10% of these falls are serious, requiring medical attention. Yet many fall victims don’t get the treatment they need.
George Netscher, a software developer by training, watched his grandmother and aunt, both of whom had Alzheimer’s, struggle to avoid falls. Worried that his mother might also develop the disease, Netscher founded a tech company, SafelyYou, in search of a better care solution.
“The tech originated in 2015 as part of my doctoral research,” Netscher told TechCrunch. “SafelyYou’s mission is to ensure the highest-quality care for seniors in any care setting.”
SafelyYou, which sells its platform to senior living communities, employs a combination of cameras and AI-powered sensors to detect when a person might be falling. Once those sensors spot a fall, they trigger text message and phone alerts to on-call staff so they can attend to the fallen person.
SafelyYou also retains a remote clinical team to document each fall. The team makes recommendations to SafelyUse’s customers so that they can take steps to reduce risk.
“Our expert clinicians have analyzed more than 300,000 on-the-ground events,” Netscher said, “and regularly review fall videos, conduct root cause analyses, and provide suggestions that help to reduce future falls in senior living communities.”
There are other fall detection products on the market aimed at older populations. But Netscher claims that SafelyYou is less susceptible to false alarms.
“Some other fall technologies won’t detect a fall unless someone has been on the ground for at least 12 seconds, which could miss an individual’s fall entirely if they fell and recovered,” Netscher said. “Our technology is completely ambient and does not require wearables or other inputs from residents or caregivers.”
SafelyYou nearly shut down during the COVID-19 pandemic, when assisted living facilities around the country were effectively quarantined. The startup managed to make it through, however, and is now serving nearly 1,000 senior living communities.
To support SafelyYou’s expansion, the company recently closed a $43 million Series C round led by Touring Capital with participation from Foundation Capital, Omega Healthcare Investors, Founders Fund, Cross Creek Advisors, Samsung Next, and Qualcomm Ventures.
Netscher says that the new capital, which brings SafelyYou’s total raised to over $100 million, will be put toward growing the company’s roughly-100-person, San Francisco-based team.
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Atomicwork, a SaaS startup led by Indian founders, has raised $25 million in a fresh investment round backed by Khosla Ventures, as it plans to scale and deploy AI agents to simplify communication and service delivery between employees and their enterprises.
Amid growing digital adoption, enterprises struggle to natively provide quick support and easy access to information for their employees. The IT service management market offers tools to solve this problem to some extent. However, deploying these solutions requires time and specialized resources. The emergence of AI has brought some relief. Yet, enabling a chatbot-like experience often demands an incumbent enterprise system behind the scenes. It could be ServiceNow, BMC Remedy, or Jira Service Management.
Atomicwork replaces the incumbent’s presence with a modern AI-driven experience, enabling enterprises to offer automated service workflows. Employees can use these workflows to find work-related answers or access services from departments including HR, IT, or finance through integrations with apps such as Microsoft Teams, Slack, Intune, Okta, Notion, Salesforce, and GitHub, among others.
Vijay Rayapati, co-founder and CEO, defines Atomicwork as a “full-stack AI ServiceNow,” targeting global companies with around $1 billion in revenue and at least 1,000 people.
“The difference [between ServiceNow and Atomicwork] is architectural, what was built 25-30 years ago, versus how we build today,” Rayapati said in an exclusive interview.
Unlike deploying ServiceNow or any of its competitive IT service management platforms, which involves multi-year implementation cycles, Atomicwork’s platform could be implemented in no more than a couple of weeks, according to him. The startup also provides a universal agent to assist enterprises in setting up automated workflows.
Founded in 2022 by Rayapati, who previously founded the cloud management platform Minjar, which was acquired by Nutanix in 2018, along with Kiran Darisi and Parsuram Vijayasankar, both part of Freshworks’ founding team, the startup initially started with an AI assistant to automate enterprise workflows.
As the automation demand has grown and AI capabilities have advanced, Atomicwork introduced its agentic service management platform late last year, which brings context-aware AI agents that analyze multiple data sources to perform tasks across enterprise apps, such as resetting their work email password, relaying questions in a prospect sales call, or accessing their design catalog on Figma using Microsoft Teams or Slack.
ServiceNow — and others in this domain — also allows enterprises to develop and deploy AI agents based on their requirements. Nonetheless, Rayapati told TechCrunch that the startup, with a futuristic approach, has built its software for humans and “non-humans” (read AI agents).
“When humans need help within a business, they raise a ticket in ServiceNow, BMC, or Jira Service Management … we are basically enabling an architecture where [agents] can actually ping a message to get help — just like human employees,” he asserted.
Atomicwork utilizes existing LLM models from OpenAI, Anthropic, Cohere, and Meta, along with its in-house small models, which it uses for intent detection, routing, and slot filing, to enable workflow automation.
As AI deployment brings the question of data security and safety, Rayapati said the startup addresses this by offering enterprises the option to own the encryption keys for their data or bring their own model endpoints into Atomicwork. He also stated that the startup has signed agreements with cloud service providers AWS and Azure to restrict data retention and training and has multiple compliance certifications.
The all-equity Series A round, co-led by Khosla Ventures and Z47 (previously called Matrix Partners India), also saw participation from Battery Ventures, Blume Ventures, and Peak XV Partners. It was followed by a $3.3 million round involving over 40 CIOs, CTOs, and industry experts in September last year and a seed round of $11 million in 2023. So far, the startup has raised over $38 million.
Currently, Atomicwork has eight customers, most of whom are in the U.S., including Ammex Corporation, Zuora, and Pepper Money.
It plans to utilize the new investment to attract more customers by “doubling down” its AI R&D to bolster its platform engineering, strengthen its product and technology, and invest in building more strategic partnerships to expand integrations with companies including Oracle and SAP.
Rayapati did not disclose the exact valuation but said it was close to 5x the total capital it raised in the new round.
The startup has a team of more than 60 people, including over 50 in India.
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DeepSeek’s new open source AI reasoning model, R1, sparked a sell-off of Nvidia’s stock and caused its consumer app to soar to the top of the app stores.
Last month DeepSeek said it trained a model using a data center of some 2,000 of Nvidia’s H800 GPUs in just about two months at a cost of around $5.5 million. Last week, it published a paper showing that its latest model’s performance matched the most advanced reasoning models in the world. These models are being trained in data centers that are spending billions on Nvidia’s faster, very pricey AI chips.
The reaction across the tech industry to DeepSeek’s high-performance, lower-cost model has been wild. Pat Gelsinger, for instance, took to X with glee, posting, “Thank you DeepSeek team.”
Gelsinger is, of course, the recently former CEO of Intel, a hardware engineer, and current chairman of his own IPO-bound startup, Gloo, a messaging and engagement platform for churches. He left Intel in December after four years and an attempt at chasing Nvidia with Intel’s alternative AI GPUs, the Gaudi 3 AI.
Gelsinger wrote that DeepSeek should remind the tech industry of its three most important lessons: lower costs mean wider-spread adoption; ingenuity flourishes under constraints; and “open wins. DeepSeek will help reset the increasingly closed world of foundational AI model work,” he wrote. OpenAI and Anthropic are both closed source.
Gelsinger told TechCrunch that R1 is so impressive, Gloo has already decided not to adopt and pay for OpenAI. Gloo is building an AI service called Kallm, which will offer a chatbot and other services.
“My glue engineers are running R1 today,” he said. “They could’ve run o1 — well, they can only access o1, through the APIs.”
Instead, in two weeks, Gloo expects to have rebuilt Kallm from scratch “with our own foundational model that’s all open source,” he said. “That’s exciting.”
He said he thinks DeepSeek will make AI so affordable, AI won’t just be everywhere. Good AI will be everywhere. “I want better AI in my Oura Ring. I want better AI in my hearing aid. I want more AI in my phone. I want better AI in my embedded devices, like the voice recognition in my EV,” he says.
Gelsinger’s happy reaction was perhaps at odds with others who were less thrilled that reasoning foundational models now have a higher-performing and far more affordable challenger. AI has been growing more expensive, not less.
Other reacted by implying DeepSeek must have fudged its numbers somehow and training must have been more costly. Some thought it couldn’t say it used higher-end chips because of U.S. AI chip export restrictions to China. Others were poking holes in its performance, finding spots where other models did better. Still others believe that OpenAI’s next model, o3, will so outpace R1 when it is released that the status quo will be repaired.
Gelsinger shrugs all of that off. “You will never have full transparency, given most of the work was done in China,” he said. “But still, all evidence is that it’s 10-50x cheaper in their training than o1.”
DeepSeek proves that AI can be moved forward “by engineering creativity, not throwing more hardware power and compute resources at the problem. So that’s thrilling,” he said.
As for this being a Chinese developer with all that implies, like concerns over privacy and censorship, Gelsinger metaphorically shakes his head.
“Having the Chinese remind us of the power of open ecosystems is maybe a touch embarrassing for our community, for the Western world,” he said.
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