Super excited to close a seed round in this environment for @RyghtAI. We have created an AI digital twin of every clinical trial site in the world and changing the game for sponsors and CROs needing the best sites for their trial fast. We also automate documents and research.
Ryght AI (@RyghtAI) secured $3M seed (@FoothillVenture, @aixventureshq, @virtue_vc) to compress #clinical timelines. @sarkell, Johnny Crupi, and Alex Dickinson are using AI to create digital twins of 100,000+ trial sites, automating what CROs struggle to plan. It speeds up activation, targets protocol complexity with precision, and runs global orchestration that outpaces #biopharma bottlenecks.
Let’s keep the conversation going on LinkedIn: (https://t.co/6Ay9rwHd2P)
Dive deeper over on Substack (iterating): (https://t.co/ofFNKUVllt)
#Startups #StartupFunding #EarlyStage #VentureCapital #SeedRound #Data #DataDriven #ClinicalResearch #DeepTech #GenAI #AI #Research #Operations #Technology #Innovation #TechEcosystem #StartupEcosystem
If engineering peace of mind is what you crave, @ventionteams is your zen.
Delighted to keep adding major academic medical centers to the @RyghtAI Research Network. Clinical trial sponsors and CROs now access tens of thousands of sites around the world, including major partners like this with #AgenticAI driving real time selection and fast activation.
AI Agents will be the biggest shift to enterprise software business models that we've ever seen.
The typical business model of enterprise software has generally been that one user on the system equals one licensed seat. This model is obviously logical in a world where most users get roughly the same amount of value from each license of the software.
But it's also had the limiting effect where your TAM is naturally constrained by the employee headcount tied to the particular use-case of your customer. Historically, this has meant that the only solution to growth is going after larger and larger seat-based categories of software. There are exceptions recently in vertical SaaS that have made a killing on flipping the trend, but even they get TAM-limited too soon.
In a world of AI Agents, clearly this is going to be very different. Agentic workflows have no upper limit on how much they can be deployed by an enterprise. And all of a sudden the software categories that were once constrained by seat volume, have no such limits anymore. We're already seeing examples of AI Agents in coding, research, legal work, and other advanced categories that are being billed at multiples of their prior seat-based software equivalent price.
This provides a completely new growth vector for software companies in AI, and has major implications to software business models. For a wide number of use-cases, there may be little to no connection between the number of users on a platform and the total amount of usage of AI Agents that use the software -- and what the value is that those Agents can deliver. And for many use-cases, the idea of a user seat being tied to the agentic workflow altogether is unnecessary when agents are just running around completing work in the background for an enterprise.
We're still very early in discovering how this will ultimately evolve, and a big open question will be how the industry lands on the units of measurement of these AI Agents. AI Agents may logically be represented by a single agentic user performing an action in a system (like a superuser of the platform), but there's little architectural difference between having 100 agents complete one action a minute vs 1 agent completing 100 actions a minute.
No matter the ultimately pricing construct -- which will likely have to correlate to the amount of output the AI Agents are producing -- it's clear that this will lead to a TAM increase in software. Very exciting times ahead.
Excited to share the close of our second fund, “V2”, at $55.75 million.
Thank you to all the founders that we’ve had the privilege to work with and our LPs for their support!
Upwards and onwards 🚀
Our Founder, Simon Arkell, joined Bradley Bostic today on the Boombostic Health podcast. They discuss how Ryght AI is at the forefront of innovation by utilizing generative AI in clinical trials.
🎧Listen here -https://t.co/kzveikY6Er
#AI#healthcare#podcast#innovation
Imagine being Sundar Pichai now:
- you had the largest continually updated data set of any company to train AI on (the Google Index)
- you invented the underlying technology of LLMs like ChatGPT in 2017 called Transfomers
- you had complete search dominance: all you had to add was AI and you'd own the market
And yet:
- you managed to complete fumble your massive head start and was late to everything
- you made your APIs so hard to use nobody seriously integrated it into their apps and people instead went Anthropic and OpenAI
- you now see your search dominance quickly slipping away to Perplexity and yesterday's launched ChatGPT Search
This will be a business case studied in universities for decades
Big day as we announce the the great Tarek Sherif as an investor and advisor to Ryght . Tarek has one of those amazing stories, having co-founded Medidata Solutions from the dot com era, not having been able to raise VC, bootstrapping an IPO and exiting to @Dassault3DS for $5.8B
Big news. Tarek Sherif, Co-founder of Medidata, joins Ryght as an investor & advisor to accelerate clinical trials with AI. His experience will help us bring life-saving treatments to market faster: https://t.co/q9tooPMrhB
#HealthcareTech#AI#ClinicalTrials#GenerativeAI#RyghtA
@Jason Yeah sorry @Jason that was my least favorite in years. I love Cuban but he went down an irrelevant rabbit hole for too long about what caused inflation and 80% of it was people talking over each other. Sacks was boring in his defense. Keep politics to 20%, 80% to tech and biz.