Offer Bengal

1 appearance on the record.

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

8statements → 5claims → 0claims resolved → 3.62/5average certainty → 1.62/5average debate potential →

5 not checkable as stated how the 5 claims stand · each chip opens the sources

1 prediction · 4 assertions · 2 opinions · 1 disclosure · every statement was checked. The prediction and assertions are the 5 claims: statements the public record can support or contradict. 0 are resolved, and 5 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 Offer argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

How they sound: not measured why? →

We measure speaking style by listening to the audio itself, and a fair number needs at least 2,000 words from one person on tape we have measured. There is too little of Offer Bengal on measured tape to publish a rate. This says nothing about how they speak.

Everything Offer Bengal said on Top Founders that made the record, most notable first. Filter by type, assessment or year in the ledger →

Opinion
Bengal: Redis Labs is way more capital efficient than MongoDB
“If you take a company like MongoDB, they raised approximately north of three hundred million before they went public. This means that we probably are way more efficient than MongoDB, and that is considered a very successful company.”
Offer Bengal Mar 23, 2019 ▶ 18:38 1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB
Opinion
Bengal: Redis Labs rejects professional services model
“No, we do not do professional services. We are against this model. We think it's not good.”
Offer Bengal Mar 23, 2019 ▶ 4:06 1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB
Prediction Not checkable as stated
Bengal: Redis Labs is two to two and a half years from an IPO
“We think that, you know, in order to do You know, a nice sizable IPO we need approximately two, two and a half years.”
Offer Bengal Mar 23, 2019 ▶ 9:02 1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB
Assertion Not checkable as stated
Bengal: Redis Labs manages 8,500 enterprise clients with five DevOps engineers
“Well, we have today approximately 8500 enterprise clients and approximately a 100,000 free customers on our free tiers. And all that is managed by five DevOps.”
Offer Bengal Mar 23, 2019 ▶ 4:24 1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB
Assertion Not checkable as stated
Redis Labs has 250 enterprise software customers out of 8,500 total
“So we have, you know, we have 8500 customers. Out of them, approximately 250 are software customers, and these are the big enterprise customers. The service customers are much smaller.”
Offer Bengal Mar 23, 2019 ▶ 7:41 1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB
Assertion Not checkable as stated
Redis Labs grows revenue at approximately 60% year over year
“The company is growing approximately 60% year over year.”
Offer Bengal Mar 23, 2019 ▶ 8:55 1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB
Assertion Not checkable as stated
Bengal: Half of Redis Labs growth is expansion; accounts double in 24 months
“In any given quarter, half of our growth comes from expansions, and if you look at cohorts, et cetera, so, you know, typically, a customer doubles its expenditure in two years, in 24 months.”
Offer Bengal Mar 23, 2019 ▶ 13:14 1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB
Disclosure
Bengal: 60% to 70% of Redis Labs future hiring will be sales staff
“I would say, 60, 70% of the growth in headcount in years to come will be in sales staff.”
Offer Bengal Mar 23, 2019 ▶ 12:23 1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB

Appearances (1)

EpisodeDateSpeaking time
1337 How RedisLabs Scaled to $60m+ in ARR More Efficiently than MongoDB Mar 23, 2019 11m
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