Top 10 Tech Startups to Watch in the US This Year

Tech startups to watch are usually easy to spot once you know where to look: they're the ones investors are fighting to get into, the ones poaching talent from the biggest labs, and the ones whose products people can't stop talking about on X and Hacker News. This year, the story is dominated by one theme above all others, artificial intelligence, but it's not the flashy chatbot kind anymore. It's AI baked into coding tools, chips, robots, voice systems, and financial software that businesses actually pay for.

If you've been following the US startup ecosystem over the past year, you've probably noticed the pace hasn't slowed down. Funding rounds that would have made headlines for a month in 2022 now get replaced by an even bigger one two weeks later. A four-person team can go from a garage project to a multibillion-dollar valuation in under two years. That's not hype talk, it's just what's happening right now across San Francisco, New York, Pittsburgh, and a handful of other hubs.

This list pulls together 10 of the most promising startups in America right now, based on recent funding, product traction, and the kind of buzz that tends to precede an IPO or acquisition. Some of these names you may already know. Others are flying a bit under the radar but are quietly becoming infrastructure that half the tech industry depends on. Either way, these are the companies worth keeping an eye on.

How We Picked This List

Before ranking anyone, it helps to explain what actually makes a startup worth watching. We looked at a few things:

• Recent funding rounds and how quickly valuations have climbed
• Revenue growth, especially annualized recurring revenue (ARR) where it's public
• Product adoption among real paying customers, not just free users
• Investor quality, since top-tier VCs tend to do real diligence before writing large checks
• Industry influence, meaning whether the company is shaping how others build products

We also leaned on public reporting from outlets like TechCrunch and CNBC, along with startup tracking platforms, to confirm the numbers below are current as of mid-2026.

1. Anysphere (Cursor)

Anysphere, the company behind the AI coding tool Cursor, is probably the single biggest startup success story in the US right now. Cursor is a fork of VS Code that adds AI-native features like multi-file reasoning and agentic workflows that can plan and execute code changes across an entire codebase, not just autocomplete a line here and there.

The growth numbers are hard to overstate. Cursor crossed $1 billion in annualized revenue faster than any SaaS company in history, then kept climbing to roughly $4 billion in ARR by mid-2026. In November 2025, the company raised a $2.3 billion Series D at a $29.3 billion valuation. By June 2026, SpaceX agreed to acquire Anysphere in an all-stock deal worth $60 billion, reportedly the largest acquisition of a venture-backed startup ever.

Why it matters: Cursor proved that AI-assisted coding isn't a novelty feature bolted onto an existing product. It's a category of its own, one that Microsoft, Google, and a wave of well-funded challengers are now racing to compete in.

2. Cerebras Systems

Based in Sunnyvale, California, Cerebras Systems builds wafer-scale AI chips, essentially giant processors built to train and run large models faster than traditional GPU clusters. The company positions itself as a real alternative to Nvidia for large-scale AI training workloads.

Cerebras raised $1.1 billion in a Series G round in September 2025 at an $8.1 billion valuation, and has continued expanding through 2026 with new manufacturing partnerships and enterprise deals, including work with CrowdStrike and AMD. The company has also committed to building its first European data center capacity by the end of 2026.

Why it matters: As AI companies hit compute bottlenecks, chip startups that can offer a real alternative to Nvidia's dominance are becoming strategically important, not just technically interesting.

3. Skild AI

Skild AI, headquartered in Pittsburgh and founded out of Carnegie Mellon, is building what it calls a general-purpose "brain" for robots. Instead of training a separate AI model for every robot and every task, Skild's model is designed to control robots it has never even seen before, adapting in real time to new hardware and environments.

In January 2026, Skild AI raised $1.4 billion in a round led by SoftBank, with participation from Nvidia's venture arm and Bezos Expeditions, pushing its valuation past $14 billion.

Why it matters: Robotics has always struggled with the "one robot, one model" problem. If Skild's approach works at scale, it could do for robotics what large language models did for text and code.

4. Fireworks AI

Fireworks AI runs inference infrastructure, meaning it handles the actual compute needed to serve AI models to real users after they've been trained. Founded in 2022 by a former Meta director, the company has grown fast by managing serving costs and latency better than many rivals.

Fireworks reportedly handles around 40 trillion AI tokens per day and hit a $17.5 billion valuation by mid-2026, backed in part by Nvidia. It also struck a partnership with Microsoft, letting Foundry customers access models through Fireworks' platform.

Why it matters: As more companies deploy AI in production, the bottleneck shifts from training models to serving them cheaply and reliably at scale. Fireworks sits right at that pressure point.

5. Baseten

Baseten competes directly with Fireworks in the inference infrastructure space, and the competition between them has been one of the more interesting rivalries in AI this year. Baseten raised a $1.5 billion Series F in mid-2026, and by some measures its revenue and inference-volume growth have outpaced its rivals over the past several months.

Both companies lease GPU capacity rather than owning their own chips, which has raised some investor questions about margins long-term. Still, demand for inference serving has been strong enough that both Baseten and Fireworks have reached decacorn status (valuations above $10 billion) within months of each other.

Why it matters: Watching how Baseten and Fireworks differentiate from each other, and from hyperscalers like AWS and Google Cloud, will say a lot about where the AI infrastructure market is headed next.

6. LMArena

LMArena started as a fairly niche project: a platform where users vote on which AI model gives a better response to the same prompt, creating a public leaderboard for model quality. That idea turned out to be exactly what the industry needed as the number of competing AI models exploded.

In January 2026, LMArena raised $150 million in a Series A round, and by early 2026 its valuation had reportedly reached $1.7 billion in under four months.

Why it matters: As AI labs release new models constantly, independent, trustworthy benchmarking has become genuinely valuable. LMArena has positioned itself as one of the few neutral referees in a very crowded field.

7. Deepgram

Deepgram builds voice AI infrastructure, covering speech recognition, transcription, and voice-agent tools used by enterprise customers who need accurate, low-latency audio processing at scale. The company secured $130 million in Series C funding in January 2026 to expand its platform further.

Voice has become one of the more overlooked corners of the AI boom compared to text and image generation, but it's quietly essential for call centers, healthcare documentation, and customer service automation.

Why it matters: As more companies automate phone-based and voice-based interactions, the infrastructure underneath, accurate transcription and real-time understanding, becomes a genuine competitive advantage. Deepgram has built a strong reputation in exactly that niche.

8. OpenBB

OpenBB is trying to do to financial research what open-source software did to operating systems. It's an open, customizable platform for quants, analysts, and developers who don't want to pay upward of $24,000 a year for a Bloomberg Terminal but still need serious data and tooling.

Rather than locking users into a closed set of pre-selected tools, OpenBB lets people bring their own data sources, build their own AI agents, and share workflows with other users. The company is backed by investors including Founders Fund and Khosla Ventures.

Why it matters: Financial data has historically been one of the most locked-down, expensive corners of enterprise software. OpenBB's open approach is a real threat to that model, and a sign that even entrenched industries aren't safe from disruption.

9. Perplexity

Perplexity has spent the past couple of years building an AI-powered search engine that answers questions directly instead of just returning a list of links. It's become one of the most talked-about AI startups in the country, competing not just with traditional search but increasingly with the AI labs themselves.

Perplexity continues to attract significant investor interest into 2026, with capital flowing toward tools that are already being used in healthcare research, enterprise knowledge search, and everyday consumer search.

Why it matters: If AI-native search genuinely starts pulling market share from Google, even a small percentage shift represents a massive business opportunity. Perplexity is one of the few companies positioned to make that case credibly.

10. Together AI

Together AI rounds out this list as another major player in AI infrastructure, focused on training and running open-source models efficiently. The company has continued raising capital through 2026 as demand for flexible, cost-effective AI infrastructure keeps climbing.

Together AI differentiates itself by leaning into open-weight models and full-stack infrastructure rather than competing purely on inference speed, giving it a slightly different lane than Fireworks or Baseten even though all three compete for similar customers.

Why it matters: Not every company wants to build on closed, proprietary AI models. Together AI has built a strong position serving the growing segment of the market that wants more control and lower costs.

What These Startups Have in Common

Looking at this list as a whole, a few patterns stand out:

1. AI infrastructure is where the money is going. Four of the ten companies here, Cerebras, Fireworks, Baseten, and Together AI, are essentially picks-and-shovels plays that make AI cheaper or faster to run.
2. Speed to revenue has replaced speed to users. Cursor's jump from launch to billions in ARR happened faster than almost any SaaS company in history. Investors are rewarding real revenue, not just downloads.
3. Big tech isn't sitting this one out. Nvidia has invested in or partnered with several companies on this list. Microsoft has struck deals with more than one as well. The line between startup and strategic partner to a tech giant is getting thinner.
4. Robotics and voice are catching up. For a couple of years, text and image-based AI got most of the attention. Skild AI and Deepgram are proof that physical and voice AI are becoming just as investable.

Frequently Overlooked Startups Worth Watching Too

This list isn't exhaustive, and plenty of other US tech startups deserve honorable mention, including Hightouch in data activation, Modal and OpenRouter in AI infrastructure, and a growing wave of defense tech and biotech startups raising serious capital this year. The broader startup landscape in the US remains one of the most active in the world, and new names are climbing fast enough that any list like this one is somewhat out of date within a few months.

Conclusion

The tech startups to watch this year share a common thread: they're not chasing hype for its own sake, they're building products that businesses and developers are already paying real money to use. From Anysphere's AI-native coding tools and Cerebras's alternative to Nvidia's chip dominance, to Skild AI's general-purpose robotics brain and Deepgram's voice infrastructure, these companies represent where American innovation is actually headed rather than where headlines say it's headed. Whether you're an investor, a job seeker, or just someone trying to understand where the industry is going next, these are the ten names worth keeping on your radar through the rest of the year.