Jacques Baritot

Co-Founder and General Counsel @ OneGC

[Mitchell Leshchiner @MLeshchiner]

Today, we’re introducing Nefesh by @electrokare - a foundation model for human physiology.

The human body produces an extraordinary amount of information. Our ability to understand it, and use it to help, has barely caught up. We started Electrokare to change that.

Our first window into the body is the ECG. A few seconds of electrical activity, collected every day in clinics, hospitals, and wearables around the world. We believe it can tell physicians far more about a patient than it does today.

Nefesh is our foundation for that work: learning from the underlying signal to answer a growing range of questions about cardiac function, structure, and the physiology beyond them.

For a physician, the promise is concrete. Recognizing disease earlier. Knowing which patient needs a closer look. Getting more information from a test already in your hands.
For us, this is the beginning of a much larger undertaking.

We want to bring multiple signals and modalities together into a model of how the human body works, one that can help medicine move from treating disease after it declares itself to understanding what is changing, and acting earlier.

Today, we’re sharing the first chapter.
Introducing Nefesh, by Electrokare. Live across multiple clinical sites, and tens of thousands of patients.

Making physiology computable.

If you’re a physician or healthcare leader who wants to help build this future, I’d love to hear from you.

[Monaco @MonacoGTM]

Name another revenue platform customers have to turn off because it's working too well.

@evan_vandenberg at @onegc_ai set up a campaign in Monaco. So many meetings came in, he had to pause it.

That's a champagne problem for founders.

Grow your startup's revenue with Monaco.

https://t.co/0IrTuVdESs

[Jacques Baritot @jbaritot]

@MonacoGTM @evan_vandenberg @onegc_ai Monaco got me booked and busy 😅

[Gabe Azevedo @gabe_az]

1/ @evan_vandenberg and I are building together again, this time with @jbaritot 🤝

We raised from a16z @speedrun , @tuskventures, and @MontaukCC to build @onegc_ai: the first platform that runs legal for you.

10 months in the making. Here’s why we built it 👇

[Evan Vandenberg @evan_vandenberg]

We've been heads down on this for 10 months. Excited to finally share what we've been building.

We raised from a16z @speedrun , @tuskventures , and @MontaukCC to build @onegc_ai : the first platform that runs legal for you.

Here's why 👇

[andrew arruda @andrewarruda]

this is where legal tech and legal in general will go

[Brad Smith @BradSmi]

Today we’re introducing a new Legal Agent in @Microsoft Word, built to support the precision and rigor legal work demands. Every clause matters. Every redline tells a story. That’s why this agent was built to follow the structured workflows lawyers use while keeping them fully in control.

Early in my career, I asked for a computer on my desk because I believed technology could change how lawyers work. It did. Today, I believe this next generation of tools will do the same, grounded in trust and responsible use.

[Troy Kirwin @tkexpress11]

[New] from a16z @speedrun:
Come for the Agent, Stay for the Network

there's a quiet pattern hiding inside the most defensible vertical AI startups right now:

the agent is the wedge
the network is the moat.

here's what I mean:

an HVAC tech needs a part today.
>>Traditionally: hours to investigate, 5 calls, emailing for quotes, waiting days, and comparing PDF catalogues by hand
>>Now: an AI procurement agent identifies the exact SKU, autonomously contacts suppliers, negotiates price, and orders - in minutes

but - the network forming is the real differentiator:

when that agent is operating across thousands of buyers, the system starts seeing real transaction prices - not list prices
> It can tell you you're paying 18% above market
> It can bundle demand across forty facilities and negotiate bulk pricing
= Suppliers start competing to be plugged into the agentic network

these AI procurement agents can become networked, sticky platforms when an industry has some combo of:
+ Fragmented supply and demand
+ Offline suppliers
+ Opaque yet elastic pricing
+ Frequent purchases
+ Different SKUs; or
+ a commoditized product or services

in the past, suppliers thrived off of the offline nature of these markets

with an agentic platform, the demand side can be aggregated and the power balance flipped

you can start to become the interface buyers default to, the channel suppliers need to be on, and the owner of the richest pricing dataset in the industry

by unlocking an efficient marketplace, you can charge on a % of revenue basis vs token or seat basis.

we’re seeing this trend emerge across several SR006 @speedrun companies including Heavi for truck repair shops and Vereda for farmers

few examples of industries ripe for AI procurement agents include:
-- Freight and logistics
-- Agricultural inputs
-- Field services
-- Food service procurement
-- Construction subcontracting
-- Industrial MRO
-- Healthcare staffing
-- And more

if this sounds like something you're interested in, apply to speedrun now