Anja Zehfuss

[Anja Zehfuss @anjazehfuss]

join us in austin!!

[Nurcan Sonmez @CoRL @nurcannsonmezz]

In Austin for CoRL? Orchestral Labs is hard at work building the fastest inference platform for robotics. Come hear our vision this Wednesday at Physical AI Night with @CRV and @lancedb. https://t.co/zTLHdjvCSI

[Anja Zehfuss @anjazehfuss]

@caitlinbolnick1 @carlpeterson GT represent

[Anja Zehfuss @anjazehfuss]

stoked to be in business with @jimbelosic and the SCS team, LFG!!

[Caitlin Bolnick Rellas @caitlinbolnick1]

Broke all the rules for this one. Absolutely STOKED to make this partnership official.

It all started when I went to Jim for help with an anodizing line that I was considering buying. He told me I was nuts, I soon realized I was nuts, and a friendship was born.

Investing in Jim might have been one of the easiest decisions I’ve ever made. He’s the EXACT type of founder and business I want to be a part of. What he has built is truly incredible. And the best part is that Jim and SCS are just getting started.

@CRV is honored to be on the ride. LFG!!!!🔥🔥🔥

[Anja Zehfuss @anjazehfuss]

@jimbelosic LFG!!

[Anja Zehfuss @anjazehfuss]

@danielchingwq 🫡🫡🫡

[Anja Zehfuss @anjazehfuss]

let's go theker! stoked to work with carla, jia, and the team driving towards the future of robotics

[THEKER Robotics @THEKER_ai]

We just raised $85M, Europe's largest ever robotics Series A, led by @CRV, with backing from @Samsung and @LVMH.

But this story did not start today.

Carla and Jia have been obsessed with robots since they were kids. They met as engineers at UPC, started the university's robotics club, and competed and won at an international level.

Years later, that obsession became THEKER: a company built from Barcelona to be the largest in the world, and to crack the technical problems other people call impossible.

Today we are well on our way to the goal we set on day one: solve 100% of physical work. Our robots are live in production, improving every day, and the pace is only increasing.

This round is not the destination. It is one more step in the right direction.

Thank you to everyone who got us here. To our team, who hold a standard most people would call unreasonable. To our customers, who push us to become better. And to our investors, old and new, who saw it before the rest of the world did.

If this mission excites you, we are hiring across the board. Come build it with us.

We will win.

[Anja Zehfuss @anjazehfuss]

We've seen a ton of activity in AI x bio lately, so what does this mean in practice and how does this foot with big pharma's current strategy?

From a macro perspective, big pharma view early discovery (tools like Boltz, Chai, etc handle the protein structure prediction bottleneck) and pharma commercialization as great solutions due to recent developments in AI. Focus has recently shifted to buying vs building - big pharma is generally quite concerned their core competencies have eroded. This is due to some consistent themes across pharma (e.g. 50+ stakeholders for decisions), as well as some more recent ones (challenging to attract + retain best in class researcher talent). Willingness to pay can be quite high (~$5-10M+ ACVs), especially to access the right talent pools.

Generally, have heard a few people I respect say that data as a moat will only continue to matter for the next 6-24 months; diffusion across pharma is essential for that period. Afterwards, this is likely to be less of an issue (rise of synthetic data, agents will be able to parse multimodal data better).

As we think about what matters and what the needs are within this shifting landscape, the focus has / will continue to be how you accelerate trial speed and success rates in a newer future with a proliferation of AI-generated assets. So the goal becomes accelerating the time from discovery to commercialization. Generally, interesting ideas could look like optimizing Phase 1 - Phase 3 transitions (e.g. the transition between running a Phase 2 trial where ~50 patients can drive a $500M go / no go decision with ~40% chance of success), improving and automating manufacturing / CRO / CDMO capabilities, and improving patient selection using multimodal data. If you're a startup building across any of these areas or work in biotech / pharma and are thinking about these problems as well, would love to chat!

[Anja Zehfuss @anjazehfuss]

@reidRMC @shomikghosh21 2nd to right may be more of a tech enabled services narrative but who am I to say

[Anja Zehfuss @anjazehfuss]

@andrewziperski let's go!!

[Anja Zehfuss @anjazehfuss]

@Divya_ch_ So exciting Divya!! Couldn't be more proud