Eric MacBlane — Why I joined Hebbia

Back in 2014, I took a class at UVA named “Human Machine Interfaces.” I still remember one of the projects: construct a program that could interpret the sentiment of text. My group sat in the dimly lit basement of the 24-hour library, cataloging words and phrases, assigning sentiment weights, and testing models.¹ Building concrete data from freeform text… borderline inconceivable.

Fortunately, I was never asked to build a from-scratch sentiment model again. But much of my career – from consulting to supply chain – became focused on collecting unstructured information, analyzing it, and making it useful. That’s not particularly surprising. After all, the entire knowledge economy from law to finance to strategy to operations does just that: access, analyze, and use information.

So needless to say, just over a year ago when my business school classmate slid their laptop to me before class, intrigued would have been an understatement. “Chat-GPT:” a simple web app that would have finished my sentiment project in seconds, or better yet, even built the code for it. It was immediately clear to me that knowledge work was about to look a whole lot different.

In the coming year, there was no shortage of startups that jumped on the AI train to build point solutions for unstructured data. From recruiting to deal flow to customer support to teaching, it probably exists. (You pick your niche… I just wound down an AI-powered finance platform for residential building contractors). So as I thought about what’s next, how did I land on Hebbia?

Vision. Eric and Usman said it best, “information is only as useful as it is accessible.” Hebbia is solving for the accessibility of information, a problem that transcends any industry or profession. Hebbia is to words as Excel is to numbers or Salesforce is to customers. 

The Hebbia Matrix product evaluates thousands (or millions) of documents to find whatever it is you want to know. If that sounds broad-reaching, it is. It doesn’t get more universal than that. The Matrix product would alleviate pain at every job I’ve ever had – market research at Bain, customer MSAs at WeWork, supplier agreements at Detect, hundreds of interviews at our startup.² It legitimately would have saved years of work. 

The vision is simple, but profound: be the enterprise user experience for LLMs. Change how knowledge work gets done. It is a generational vision, and one I am thrilled to be a part of.

Product. At my onsite interview, I was struck by how natural the product is. Without any explanation from anyone, I was able to easily create my first matrix. 

It really is as simple as pinging a team member: “Hey! Can you analyze trends from the last three years of earning calls from McKesson and their competitors?” And there you have it: summary statistics, sentiment analysis, key takeaways in a cleanly formatted matrix. But now, in a matter of seconds, not days. Export to Excel? Sure. Import more data from SharePoint? Why not? About as easy as onboarding to Google.

But the real vote of confidence came from my first few weeks interacting with customers. Hebbia is deployed in some of the world’s largest financial institutions, law firms, and even the United States Air Force. And everyone I speak with loves Hebbia. They’re willing to double down, offer feedback, try new features, and be part of the Hebbia mission. Partly for the product, and partly for the people.

People. The team at Hebbia is the highest achieving I’ve seen. The founder of Hebbia, George, started the company back in 2020 where he created one of the first (and best) semantic search algorithms. The engineering has only continued to lead innovation in AI, more than willing to jump into customer challenges, and tackle the impossible. 

On the business side, Lainie and George built a crew that thrives in the ambiguity of a startup, but have all experienced the pain point first-hand at banks, consulting firms, and enterprise businesses. The team isn’t afraid to challenge the way it’s “always been done” with the way “it should be done” no matter the audience or use case.

But as a group, Hebbia has built something remarkably special. Everyone has each other’s backs. And while the team runs hard and with urgency, folks are firstly compassionate. Every single person on the business team made time to meet with me before I joined (most caffeinated I’ve been in my life!) And even during late nights and at tough crossroads, the team isn’t afraid to have some fun.

And that’s just the beginning.³ I’m beyond excited for what lies ahead. If you’re interested in Hebbia, please don’t hesitate to reach out. We’re hiring across the board!

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¹ I can’t even imagine the headaches we had around a phrase like “I couldn’t be happier.”

² I like to think I could even use Hebbia to clean up scheduling based on lifeguard availability emails back in high school.

³ Felt more footnote worthy, but Hebbia is also based in New York, the best city on earth. Awesome to see how many “Hebbians” picked up and moved east for a shared vision.

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