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Apoorv Agarwal

Adjunct Associate Professor, Columbia University · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

founderexecutiveacademicscientisthostinvestorcs.columbia.edu/~apoorv ↗

Agarwal co-founded and served as CEO of Text IQ, an AI enterprise startup using natural language processing to identify sensitive information in unstructured data, which was acquired by Relativity in 2021. Holding a Ph.D. from Columbia University, he currently teaches startup creation at Columbia and advises corporate leaders on enterprise AI adoption.

10statements → 6claims → 2claims resolved → 4.4/5average certainty → 1.8/5average debate potential →

2 supported 0 partly supported 0 contradicted 4 not checkable as stated how the 6 claims stand · each chip opens the sources

6 assertions · 3 insights · 1 what if · every statement was checked. The predictions and assertions are the 6 claims: statements the public record can support or contradict. 2 are resolved, and 4 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Apoorv argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported
Text IQ infers employee roles and relationships to flag sensitive information
“We can analyze human communication, we can infer things about roles of people within an organization, their relationship, and that allows us to zoom into or find many different kinds of sensitive information.”
Apoorv Agarwal May 13, 2019 ▶ 5:21 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)

How they sound: speaking style how? →

239 words/min while actually speaking · 107.2 um and uh per 1k words

No argument clarity score for Apoorv Agarwal: no usable question→answer exchanges on raw tape (a fair score needs 8+). We do not score a sample that small. Roundtable and news formats yield far fewer direct exchanges than interviews.

Measured by listening to the audio itself: 3,033 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

Everything Apoorv Agarwal said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Assertion Not checkable as stated
A major New York bank hired 13,000 compliance reviewers since 2012
“A major bank in New York alone, they've hired over 13,000 people since 2012 looking for sensitive needles in this haystack.”
Apoorv Agarwal May 13, 2019 ▶ 3:37 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Insight
Structuring enterprise unstructured data requires unsupervised machine learning
“There's just so many different types of documents and types of data that there's just no way we can, you know, tackle this problem using supervised machine learning. So a lot of the machine learning we use in-house you know, is, is mostly unsupervised and that…”
Apoorv Agarwal May 13, 2019 ▶ 9:37 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Insight
Enterprise AI only needs to outperform keyword searches and human reviewers
“The bar is not to be hundred percent accurate. The bar is search tomes and 500 humans, right? And as it turns out that bar is not that hard to beat with AI.”
Apoorv Agarwal May 13, 2019 ▶ 14:39 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Assertion Not checkable as stated
Enterprise compliance still relies mostly on keyword search and manual review
“The status quo method, the most popular method of finding these needles in a haystack remains to be based on search terms, ah, and manual review.”
Apoorv Agarwal May 13, 2019 ▶ 3:24 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Assertion Supported
Text IQ infers employee roles and relationships to flag sensitive information
“We can analyze human communication, we can infer things about roles of people within an organization, their relationship, and that allows us to zoom into or find many different kinds of sensitive information.”
Apoorv Agarwal May 13, 2019 ▶ 5:21 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Insight
Agarwal: Analyzing short text requires different ML techniques due to context limits
“Dealing with short text, it's a totally different you know, animal compared to longer text. There's very little context.”
Apoorv Agarwal May 13, 2019 ▶ 10:58 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Assertion Not checkable as stated
Text IQ achieved profitability by 2017 with a 100% pilot conversion rate
“We've been profitable since 2017 but really the metric that we are proud of is that we, we've had a hundred percent pilot to customer conversion rate.”
Apoorv Agarwal May 13, 2019 ▶ 2:11 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
What-if
Legacy compliance review for a healthcare client would have cost $4 million
“Had they used the status quo method, which is very much based on search terms and manual review, it would have taken them about 20 weeks To review all these documents. Ah, we later showed them that their search would have missed about 10% of the sensitive info…”
Apoorv Agarwal May 13, 2019 ▶ 6:43 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Assertion Supported
Text IQ was launched via a government research grant in 2014
“Around the time in 214, ah, when I was graduating, ah, the government, ah, who had funded a lot of my research, saw a lot of commercial potential in what we had built, ah, they gave us a grant, ah, and that's how we got started.”
Apoorv Agarwal May 13, 2019 ▶ 1:33 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Assertion Not checkable as stated
Agarwal: Text IQ grew 5x over 6-7 months
“We've grown like five times over the past six, seven months.”
Apoorv Agarwal May 13, 2019 ▶ 13:27 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)

Appearances (1)

EpisodeDateSpeaking time
AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC) May 13, 2019 17m
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