
Smart Ring Maker's Blood Test Service Tracks 100+ Health Stats
Ultrahuman has launched its blood test-based health tracking service for people in the U.S., following an India launch more than a year ago.
It's called Blood Vision, and includes two blood tests, spread out over time in order to capture the trajectory of your biomarkers, rather than just a snapshot.
The real selling point of the service, though, is what Ultrahuman calls UltraTrace. All the stats from your bloodwork report end up in Ultrahuman's app, and are then linked to metrics collected by one of Ultrahuman's smart rings.
The concept is not too hard to grasp. By linking your biomarkers to stats that relate to your daily behaviours, the whole blood testing process can come across more useful, more actionable.
'Tracking lifestyle biomarkers between two tests allows us establish the relationship between the biomarkers and lifestyle changes. Most people lose track of what to change between two tests, Blood Vision bridges this gap,' says Ultrahuman CEO Mohit Kumar.
Like an ever-increasing number of health and fitness platforms, Ultrahuman also uses AI-generated summaries to translate some of these insights into more digestible nuggets of info.
'By combining these markers with Ultrahuman Ring data—tracking sleep, HRV, and movement—athletes gain real-time insights into how lifestyle choices impact their performance,' reads Ultrahuman's blog on Blood Vision.
What is Ultrahuman Blood Vision?
Absolutely loads of biomarkers are included in the blood test info. They include data points related to kidney and liver function, Thyroid profile, Stress & Ageing Markers and no fewer than 15 stats that relate to heart health.
You can check out the lot before you sign up for Blood Vision. More than 100 biomarkers are in the initial test — the exact number varies by gender a little. And the second test features fewer of them, in the ballpark of 60.
The price might sting as much as the blood test jab for some, though. Annual prices for the program start at $499, although blood tests booked alone are not cheap to start with. Those in New York will also have to pay significantly more, $799.
Blood Vision's required blood tests can either be done at home, then sending the vial off to a phlebotomist for analysis. Or the test can be done at a Quest or Bioreference location. Perhaps surprising, at-home tests come at a slight subscription premium.
Ultrahuman suggests the second blood test is performed 3-6 months after the first. And, judging by how Ultrahuman describes this as an annual plan, the idea is you may decide to carry on for multiple years.
Ultrahuman is best known for its smart rings, the latest of which is the Ring Air, which costs $349.
Hashtags

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
22 minutes ago
- Yahoo
Is Lucid Motors Stock a Buy, Sell, or Hold for July 2025?
The recent discussion about electric vehicles (EVs) centers on industry leader Tesla (TSLA) and how new policies might slow down demand for EVs. President Donald Trump's bill would cut the $7,500 EV tax credit for the purchase of a new EV as well as the $4,000 credit for buying a used EV after September. Against this backdrop, can luxury EV maker Lucid Group (LCID) take the spotlight away from some of the big names? More News from Barchart Warren Buffett Warns Inflation Turns Business Into 'The Upside-Down World of Alice in Wonderland' But Weeds Out 'Bad Businesses' Why GOOGL Stock May Be the Market's Next Big Winner Alphabet Posts Lower Free Cash Flow and FCF Margins - Is GOOGL Stock Overvalued? Our exclusive Barchart Brief newsletter is your FREE midday guide to what's moving stocks, sectors, and investor sentiment - delivered right when you need the info most. Subscribe today! About Lucid Stock Founded in 2007, Lucid Motors, officially known as Lucid Group, operates as a U.S. luxury EV and technology company. It began its operations by supplying high-performance batteries and powertrain systems but changed its position in 2016 to produce its own EVs. Lucid has a market capitalization of $8.9 billion. The company's flagship product, the Lucid Air, was launched in 2021. The EV is popular among consumers for its rapid charging capabilities, long range, and upscale interior design. In late 2024, Lucid started producing its second model, the Gravity SUV. The model combines luxury with long mileage. Lucid is backed by Saudi Arabia's Public Investment Fund (PIF), which remains its majority investor. Lucid is also looking at a potential reverse stock split. The company has filed a preliminary proxy statement for a 1-for-10 reverse stock split. While the strategy is popular among firms trying to avoid a delisting by preventing the stock price from falling below the $1 mark, Lucid does not seem to be in danger of delisting. Lucid recently secured a partnership with ride-hailing giant Uber Technologies (UBER), whereby Uber is set to invest $300 million in Lucid. Uber will also invest in autonomous technology startup Nuro, which is set to equip Lucid vehicles with self-driving capabilities. Uber aims to deploy approximately 20,000 Lucid vehicles equipped with Nuro Driver over a six-year period. Lucid investors celebrated this multi-year deal, which led to LCID stock surging. Over the past month alone, Lucid shares have gained 36%. However, over the past 52 weeks, the stock is still down by nearly 16%. LCID currently trades 34% lower than its 52-week high of $4.43. Currently, Lucid trades at an eye-watering valuation. Its price-to-sales ratio sits at 11 times, which is significantly higher compared to the industry average. Lucid's Q1 Results Were Lower Than Expected On May 6, Lucid reported its first-quarter results for 2025. During the quarter, revenue climbed 36% from the prior-year period to $235.05 million. At the heart of this growth was Lucid delivering 3,109 vehicles in Q1, representing a 58.1% year-over-year (YOY) increase. The company produced 2,212 vehicles during the quarter, which excludes over 600 vehicles in transit to Saudi Arabia for factory gating. While production and deliveries are growing, so are costs. The company continues to post significant losses. In Q1, its net loss per share stood at $0.24. While this was lower than the $0.30 per share net loss in Q1 2024, it was wider than the $0.23 per share net loss that analysts had expected. Lucid ended the quarter with about $5.76 billion in total liquidity. Lucid is still aiming for a huge expansion in deliveries. At the current rate, it's on track to deliver 12,500 vehicles, which is robustly higher than the number it delivered last year. Even with the fear of tariffs looming large, the company aims to produce approximately 20,000 vehicles this year, which is roughly double what it produced in 2024. While analysts expect Lucid to continue posting losses, they anticipate that these losses will narrow. In Q2, Lucid is projected to post a loss per share of $0.22, narrowing by 24% YOY. For the current year, the company's loss per share is expected to be $0.89, reflecting an improvement of 29% YOY. What Do Analysts Think About Lucid Stock? Wall Street analysts are tepid on LCID stock at the moment. Analysts at Cantor Fitzgerald reiterated their 'Neutral' rating on LCID with a $3 price target. This was predicated upon Lucid's Q2 production and delivery numbers falling short of Cantor Fitzgerald's estimates while showing improvements YOY. On the other hand, Baird analyst Ben Kallo raised the price target on Lucid Group from $2 to $3 while maintaining a 'Neutral' rating. The price target was upgraded after Lucid reaffirmed its intention to launch its midsize platform next year, indicating potential models. Morgan Stanley also sees opportunity in Lucid's partnership with Uber. Analysts at the firm reiterated their 'Equal Weight' rating and $3 price target on the stock. Wall Street analysts have a mixed view about Lucid, giving it a consensus 'Hold' rating overall. Of the 13 analysts rating the stock, two analysts rate it a 'Strong Buy,' a majority of nine analysts play it safe with a 'Hold' rating, one analyst provides a 'Moderate Sell' rating, and one analyst recommends 'Strong Sell.' The consensus price target of $2.86 represents 2% downside potential from current levels. Key Takeaways While the multi-year partnership with Uber creates a chance of generating a revenue stream for the foreseeable future, the effects of the absence of tax credits on this luxury EV maker and a reverse stock split must also be taken into account. Hence, it might be wise to observe LCID stock from the sidelines for now. On the date of publication, Anushka Dutta did not have (either directly or indirectly) positions in any of the securities mentioned in this article. All information and data in this article is solely for informational purposes. This article was originally published on Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data


Fast Company
23 minutes ago
- Fast Company
AI is transforming business and giving leaders new options for low-friction change
AI stubbornly persists at the extremes: One extreme is limiting, treating AI as a fast-commoditizing tool that boosts performance by 5%-10%. The other is expansive, portraying AI as a disruptive force that is reshaping jobs, the nature of work, and what's fundamentally possible. Both are critical, but compelling outcomes live between those extremes. Ironically, AI, which promises disruption, may also enable transformation without massive organizational change. We often treat AI like a moonshot—a high-risk, high-reward bet requiring bold, expensive, and dramatic changes. But moonshots can have higher failure rates and cause disruption; they should be used strategically. Like an investment portfolio, diversity and balance yield the right gains at the appropriate risk levels. A smart investment strategy should include roof shots (measured upside, steady growth with scalable change) and chip shots (incremental and reliable, but limited structural change at scale). If a business chases extremes, it misses the value found between them. One middle-ground benefit is what I call low-friction transformation. The goal isn't for teams to overhaul how they work to accommodate AI; it's for AI to absorb as much change as possible. AI agents can flex around new or non-standard processes, so humans adapt only where it's required. Agents handle complex data and variability in processes, and give humans the outputs they need. AI works as an extension of humans by navigating complex systems and processes, and driving performance benefits and productivity gains without massive disruptions. This is where AI's precision matters most. Its strength isn't just what it can do, but how intentionally it's applied. AI can enhance the operating model in targeted ways that use agents to manage the differences where practical. It becomes part of the system and a lever for innovation—quietly powerful, deeply effective, and built for long-term impact. THE 'GOOD ENOUGH' AI REVOLUTION For years, executives have sought standardized processes, as standardization drives consistency and optimization. Variability was the enemy of quality. AI evolves that thinking. A marketing team once followed a content production process; AI now generates tailored drafts in seconds. A support team escalated tickets through multiple layers, but AI can interpret and triage instantaneously. Rigid processes become less valuable when AI can consistently produce high-quality results. The goal is no longer blanket standardization. Instead, standardize where it creates value and let agents manage process variability or non-standard data. Standards still matter, but AI can bridge gaps where standards don't exist. AI's promise lies not just in its upside, but in raising the baseline. 'Good enough' becomes 'better.' With quality outcomes from AI, executives can loosen their grip on standardization. AI doesn't need to be perfect to be powerful. The right framework makes outputs consistently valuable. CHANGE LESS, TRANSFORM MORE Transformation once meant sweeping change: reorgs, retraining, and disruption. But today's AI strategy changes that—change less, transform more. That's why 66% of executives reported increased productivity and 57% reported cost savings from adopting AI agents, according to PwC's AI Agent Survey. Value is being captured early and often from these agents. Transformational outcomes come from minimizing human behavior change. Machines can now work like humans. We should rethink an employee's daily habits to leverage AI agents, or reshape customer value with greater intelligence and personalization. Deeper change may still be needed for business model shifts, and the value will justify a greater degree of change. But change only where it counts. Think of a busy hospital. Doctors have limited time with patients and deal with a wide range of complex symptoms. AI can help analyze these symptoms and give the doctor a more accurate diagnosis to work with. The result: faster, more personalized, and precise medical care. The only change is using the input from an AI agent instead of consulting a physician. With any new technology, the less people need to change, the less organizational friction you'll see. That's the essence of low-friction transformation. TOMORROW'S BUSINESS MOATS Why does it matter? Traditional strategies are shifting, new threats are emerging, and we need to accelerate innovation to be ready. AI may still be emerging in enterprises, but upstarts are already using it to disrupt. We have seen startups with small teams—using AI to write their code—take market share from industry heavyweights. AI-native competitors are designed for change and are therefore fast, nimble, and threatening. Competitive advantage often comes from brand power, capital, high barriers of entry, economies of scale, and so on. These traditional moats are blunted by AI if scale and specialization can be achieved with AI agents via low-cost models. The question becomes: How do companies stay great when 'good enough' is cheap and instant? There will be tremendous pressure on big companies to maintain their growth and defend their positioning. Not enough companies are thinking about AI's business impact. Only 44% are developing new agentic products and services, and just 42% are redesigning processes around AI agents, according to our AI Agent Survey. That's a problem. Tomorrow's advantages won't come from size and staying power. They'll come from speed, creativity, and human-led innovation, amplified by AI agents. Enterprises need small, independent teams—innovation labs—tasked with reimagining their business with AI. These teams need to be well-resourced and free to experiment. This work can feel ambiguous to executives. It can take up budget or pull your star players from other resources. The payoff isn't always immediate, but if you don't do it, someone else will. THE PRAGMATIC PATH AHEAD AI has changed the game, but too many executives still treat it like past technology implementations. They assume it will disrupt teams and require major changes. The power of AI lies in its adaptability. It integrates into existing workflows, supports human output, and creates profound impact without huge change management. When deployed thoughtfully, AI strengthens teams and reduces friction. Tomorrow's leaders won't chase perfection. They'll pursue pragmatic, low-friction transformation on the path to reinvention.


Entrepreneur
23 minutes ago
- Entrepreneur
Is Voice AI Becoming India's Next Digital Backbone?
According to NASSCOM, the Indian voice AI market is projected to reach USD 1.82 billion by 2030 Opinions expressed by Entrepreneur contributors are their own. You're reading Entrepreneur India, an international franchise of Entrepreneur Media. Voice AI is quickly becoming the new battleground in shaping the future of human-machine interactions. The recent USD 45 million acquisition of a voice AI startup Play AI by Meta brought renewed attention to the space. But why the Sudden Rush in India? "There's a rush towards voice tech startups because the country's vast linguistic diversity and rising demand for high-quality, real-time voice translation have made voice AI a natural solution," explains Ganesh Gopalan, Co-founder & CEO of Gnani AI. "With the rapid adoption of smartphones and consumers increasingly expecting seamless, human-like interactions, voice is emerging as the preferred interface for digital engagement." According to NASSCOM, the Indian voice AI market is projected to reach USD 1.82 billion by 2030. While India has 22 official languages, it is home to over 400 living languages. English, often assumed to be the digital default, is neither the first spoken nor written language for the majority of Indians. Until now, much of emerging tech has catered only to metro markets and English-speaking audiences. Voice-led AI startups, however, are disrupting that trend. Indian entrepreneurs are now tapping deeper into Tier 2/3 markets, targeting vernacular language speakers and building inclusive solutions for non-English and non-Hindi audiences. Where the action is Gopalan notes that sectors like banking, finance, and insurance (BFSI) have seen the most traction. "Voice AI is being used for customer support, lead qualification, EMI collections, policy renewals, and reminders. This growth ties closely to India's digital inclusion push, enabling businesses to engage a much wider audience in their native languages." India is also becoming a strategic growth market for global Voice AI firms. ElevenLabs, for instance, recorded a 50 per cent growth in usage in India between November and January, making the country its fastest-growing market globally. Siddharth Srinivasan, GMT–India at ElevenLabs, observes, "India was always a market waiting for a solution in this space. We're inherently multilingual, most of us are bilingual or trilingual. The need for high-quality, real-time voice solutions has always existed." Still early days? But is this rush solving meaningful, scalable problems, or are we still in an experimentation phase? Arjun Malhotra, General Partner at Good Capital, believes the sector is at "an interesting middle ground." "In BFSI, voice AI is solving real operational challenges around lending and collections at scale. Companies are successfully reaching lakhs of customers simultaneously. However, the broader ecosystem is still evolving. While enterprise applications have found clear product-market fit in certain use cases, consumer applications remain largely in the discovery phase." From an investor's perspective, technical differentiation is key. "Given the competitive landscape, we evaluate whether startups are building foundational technology or merely implementing existing solutions," Malhotra explains. "Companies that differentiate on the core mechanics of voice AI rather than just the application layer have stronger moats." He also emphasises the importance of domain expertise. "Voice AI requires deep technical expertise combined with domain knowledge. We look for teams that understand both the technology's limitations and the specific market needs they're addressing." The bigger question still remains. Can Voice AI become foundational digital infrastructure? Malhotra thinks the answer depends on the use case. "In enterprise contexts, we're seeing voice AI evolve from a feature (like automated calling) to a platform that can handle complex workflows and multiple touchpoints." The opportunity, he adds, lies in companies that can expand beyond single-use cases and integrate deeply into business workflows. What's next for voice AI in india? Looking ahead, Malhotra sees the next 24 months as pivotal. "Voice AI will likely become deeply embedded in workflows rather than remain a standalone tool. Companies that can demonstrate this workflow integration will command premium valuations." He also foresees the emergence of breakthrough consumer applications such as voice companions, therapy, and coaching tools where Indian startups could potentially create globally competitive products, especially given the market's natural comfort with voice-based interactions. Finally, Malhotra believes we'll see the rise of foundational voice AI infrastructure startups that provide the "picks and shovels" enabling the entire ecosystem.