The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (2024)

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Ben Bergman

2023-08-15T09:00:00Z

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (1)

TRAC developed an AI model to predict the startups most likely to become unicorns.
The firm revealed 30 startups its model identified and pulled back the curtain on its methodology.
TRAC says the companies it identifies have a one-in-five probability of becoming a unicorn.

Even though venture capitalists invest in tech, they have traditionally chosen early-stage investments in a decidedly low-tech manner, based largely on gut feelings, founder background and personal relationships.

TRAC, a San Francisco-based early-stage venture firm cofounded by Fred Campbell, Joseph Aaron, Scott Pyne, Steve Marek, and Dick Fredericks in 2020, wants to change that.

The firm developed a propriety model that uses AI to predict which early-stage startups are most likely to become unicorns, which are companies valued at more than a billion dollars. TRAC agreed to reveal 30 of the startups its model identified exclusively with Insider, and also pull back the curtain on its methodology.

"This is the first time we have shared the 'family jewels' or our secret sauce," said Aaron, who at age 74 jokes he is the oldest person ever to start a venture fund.

A few things are surprising about TRAC's model, which is based on over 30 sources of both public and private data and Aaron calls "Moneyball for venture capital."

For one thing, the firm says it is much more effective to focus on which startups are not likely to succeed versus picking the winners.

"Our algorithms are not really selecting needles from a haystack, as much as removing all the hay," Aaron explained. "Our AI eliminates about 99% of all early-stage companies from consideration, because our data predicts these companies have a higher probability of failure."

Another surprising thing about TRAC's model is it does not value founders as predictive. Instead, it finds the 255,559 investors in its database much more useful for determining a startup's success, especially a tiny number of just about 300 top angel investors and firms it calls "SuperForecasters."

"These extraordinary investors make a profit on two-thirds of their positions and one in five of their investments returns over 10X," Aaron explained.

Aaron declined to share the names of these SuperForecasters, with the exception of Sam Altman, the OpenAI cofounder and CEO. Aaron did share the characteristics most of the SuperForecaster angels share:

They are in their mid-40s
They were either math, computer science or engineering majors
They probably didn't go to business school. MBAs make up less than 20% of the SuperForecasters
Almost two-thirds have started a technology company
Almost half have started two technology companies
The average SuperForecaster has 9.58 years' operating experience at a startup.

Less than 2% of all startups attract a SuperForecaster so that eliminates over 98% of all startups from TRAC's formula.

TRAC says its formula identifies about 150 companies in a normal year though this year its only came up with less than half that, partly because there are fewer deals happening.

"If we could, we would invest in every company our AI scores above our investment threshold," Aaron said. (Of the companies below, TRAC is an investor in Albedo, Doppler, Golden, Rain, Superplastic, and Zendar.)

But TRAC only has limited funds and more critically, it has to battle with other VCs to get on cap tables, which Aaron points out is the most challenging part of being a venture investor.

"The companies we approach are hot and they don't need our money," Aaron said. "A portfolio company told us for his last raise, he had 274 requests from investors to meet. Believe me, that is a monumental hurdle for getting a seat on their cap table."

Only four of future unicorns TRAC identified include at least one female on the founding team (Playbook, Rain, Xata, and Kalshi). As low as that is, it is actually a significantly higher proportion than the average of just 1.9% VC dollars that went to all female founding teams last year.

"The reason why TRAC is 4X more likely to invest in women-led startups than most VCs, is because a substantially higher percentage of Angel SuperForecasters' capital is invested into women-led startups than is typical of VCs," said Campbell, who said he hopes and expects more female-led companies on next year's list.

And how accurate is TRAC's formula? Like early-stage investing as a whole, it takes a long time to know who is truly good at their job because venture investing is typically judged after a decade or more.

The firm says the companies it identifies have a one-in -ive probability of becoming a unicorn, and it has been especially good at eliminating false positives, or an investment that goes bust.

"Most early-stage companies fail within 18 months of raising a round," Aaron said. "Similar vintage early-stage VCs would have had upwards of 20% of their portfolio be false positive within the first few years. TRAC has made 53 Deal #1 investments, and none have lost money. That is the only stat we have with bragging rights."

Here are the 30 companies TRAC's model identified as being the next unicorns, in alphabetical order, all with a valuation of less than $250 million.

Albedo

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (2)

What it does: Develops low-flying satellites to capture aerial-quality imagery from space.

When it was founded: 2020

Last post-money valuation: $128 million

Total raised: $60 million

CEO: Topher Haddad

Founders: Topher Haddad, Winston Tri, and AyJay Lasater

Major investors: Shield Capital, Initialized Capital, and Breakthrough Energy Ventures

Correction: August 17, 2023 — An earlier version of this story misstated when Albedo was founded; it was founded in 2020, not 2019. It also misstated the name of an investor; the investment firm is Initialized Capital, not Commodity Captial.

AssemblyAI

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (3)

What it does: Helps organizations build AI-applications with ease by creating superhuman AI systems that are made available through a developer platform.

When it was founded: 2017

Last post-money valuation: $185 million, according to Pitchbook

Total raised: $64 million, according to Pitchbook

Founder and CEO: Dylan Fox

Select investors: Insight Partners, Accel, Y Combinator, and TechNexus Venture Collaborative

Ashby

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (4)

What it does: Helps companies achieve their growth targets by enabling teams of all sizes to run a fast and efficient hiring process. Customers include Quora, Ironclad, FullStory, Duolingo, and Deliveroo.

When it was founded: 2018

Last post-money valuation: $170 million, according to Pitchbook (2022)

Total raised: $36 million, according to PitchBook

CEO:Benjamin Encz

Founders: Benjamin Encz and Abhik Pramanik

Select investors: F-Prime Capital, Base Case Capital, SemperVirens Venture Capital, Gaingels, Reform Ventures, Millennia Capital, Quint Capital, People Tech Partners, Elad Gil, Lachy Groom, and Cristina Cordova

Censys

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (5)

What it does: A web-based search platform for assessing cyber attacks for internet-connected devices.

When it was founded: 2017

Last post-money valuation: $155 million, according to Pitchbook (2022)

Total raised: $55 million, according to PitchBook

CEO: Brad Brooks

Founder: Zakir Durumeric

Select investors: GV, Intel Capital, Decibel Partners, Greylock Partners, and Blu Stone Management.

ChartHop

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (6)

What it does: A unified platform for data and operations that also enables executive alignment and facilitates employee connection and engagement across companies.

When it was founded: 2018

Last post-money valuation: $260 million, according to PitchBook (2023)

Total raised: $74 million, according to PitchBook

Founder and CEO: Ian White

Select investors: Andreessen Horowitz, Cowboy Ventures, SemperVirens and Elad Gil.

CommandBar

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (7)

What it does: An AI-powered user assistance platform that lets product, engineering, and design teams drive engagement and retention by embedding experiences in-product that guide users to success.

When it was founded: 2020

Last post-money valuation: $123 million, according to PitchBook (2022)

Total raised: $23 million, according to the company

CEO: James Evans

Founders: James Evans, Richard Freling, and Vinay Ayyala

Select investors: Thrive Capital and Insight Partners

Courier

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (8)

What it does: Enables users to design notifications once and deliver them to any channel — push notifications, direct messages, SMS, and email.

When it was founded: 2019

Last post-money valuation: $145 million, according to PitchBook (2022)

Total raised: $57 million, according to PitchBook

Founder and CEO: Troy Goode

Select investors: GV, Slack Fund, Twilio Ventures, Matrix Partners, Bessemer Venture Partners, and Y Combinator

Curebase

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (9)

What it does: Provides decentralized clinical research software solutions and services to patients and medical providers.

When it was founded: 2017

Last post-money valuation: $220 million, according to PitchBook (2022)

Total raised: $59 million, according to PitchBook

Founder and CEO: Tom Lemberg

Select investors: Industry Ventures, Phoenix Investment Club, Gilead Sciences, Gaingels, Mount Pleasant Ventures, Breyer Capital, 10X Capital, Future Planet Capital, Xfund, Bold Capital Partners, GGV Capital, Acrew Capital, World Innovation Lab, StartX, and Positive Sum.

DataGrail

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (10)

What it does: A privacy control center for modern brands.

When it was founded: 2018

Last post-money valuation: $205 million, according to the company

Total raised: $84 million, according to the company

CEO: Daniel Barber

Founders:Daniel Barber, Ignacio Zendejas

Select investors: Third Point Ventures, American Express Ventures, Decent Capital, HubSpot, Gunderson Dettmer, Okta Ventures, DocuSign Ventures, Thomson Reuters Ventures, Sixty Degree Capital, Basis Set Ventures, Browder Capital, Operator Collective, Felicis Ventures, Next47, and Cloud Apps Capital Partners.

Doppler

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (11)

What it does: Provides a simple way to sync, manage, orchestrate, and rotate secrets across any environment.

When it was founded: 2018

Last post-money valuation: $170 million, according to the company

Total raised: $29 million, according to PitchBook

CEO: Brian Vallelunga

Founders: Thomas Piccirello and Brian Vallelunga

Select investors: CRV, GV, Sequoia Capital, Y Combinator, Thomas Dohmke (GitHub), Greg Brockman (OpenAI), Guillermo Rauch (Vercel), Frederic Kerrest (Okta), Christina Cacioppo (Vanta), and Olivier Pomel (Datadog)

EigenLayer

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (12)

What it does: Developer of a protocol built on Ethereum that introduces restaking, a new primitive in crypto-economic security.

When it was founded: 2021

Last post-money valuation: $262 million, according to PitchBook (2022)

Total raised: $71 million, according to PitchBook

Founder and CEO: Sreeram Kannan

Select investors: Blockchain Capital, Polychain Capital, Ethereal Ventures, Coinbase Ventures, Electric Capital, Khalili Brothers, Figment Capital, Ambush Capital, Hack VC, Polygon Ventures, and Hash3.

Facilio

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (13)

What it does: Harnesses AI to centrally consolidate existing building systems and automation data across portfolio, onto the cloud.

When it was founded: 2017

Last post-money valuation: $171 million, according to PitchBook (2022)

Total raised: $45 million, according to PitchBook

CEO: Prabhu Ramachandran

Founders: Prabhu Ramachandran, Yogendrababu Venkatapathy, Krishnamoorthi Rangasamy, and Rajavel Subramanian

Select investors: Dragoneer Investment Group, Accel, Tiger Global Management and Brookfield Growth.

Forma

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (14)

What it does: Creates customizable, inclusive and global benefits programs for employees.

When it was founded: 2017

Last post-money valuation: $195 million, according to PitchBook (2021)

Total raised: $57 million, according to PitchBook

Founder and CEO: Jason Fan

Golden

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (15)

What it does: On a mission to map human knowledge, Golden uses sophisticated natural language processing techniques to extract canonical information from a wide range of public and private sources

When it was founded: 2017

Last post-money valuation: $160 million, according to PitchBook (2022)

Total raised: $59 million, according to PitchBook

Founder and CEO: Jude Gomila

Select investors: Andreessen Horowitz, Liquid 2 Ventures, GigaFund, Founders Fund, SV Angel, Joe Montana, Aston Motes, Christina Brodbeck, Lee Linden, Immad Akhund, Josh Buckley, Howie Liu, James Smith, James Tamplin, Jack Smith, Mike Einziger, Sumon Sadhu, Paul McKellar, Trip Adler, Ola Okelola, Matt Humphrey, Cyan Banister, and Marc Andreessen.

Harvey AI

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (16)

What it does: An AI tool that uses legal-specific data, including case law and reference materials, to create a virtual assistant for lawyers.

When it was founded: 2022

Last post-money valuation: $150 million, three sources told Insider (2023)

Total raised: $26 million, according to PitchBook

CEO: Gabriel Pereyra

Founders: Gabriel Pereyra and Winston Weinberg

Select investors: Sequoia Capital, OpenAI Startup Fund, Conviction Investment Partners, SV Angel, Sarah Guo and Elad Gil.

Hebbia

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (17)

What it does: A LLM (Large Language Models) native productivity tool, Hebbia is a copilot for document workflows. Users can leverage Hebbia to extract answers, compare, and structure any unstructured files.

When it was founded: 2020

Last post-money valuation: $136 million, according to PitchBook (2022)

Total raised: $30 million

Founder and CEO: George Sivulka

Select investors: Index Ventures, Peter Thiel, Naval Ravikant, Jerry Yang, Ram Shriram, Kevin Hartz, and Marty Chavez.

Inscribe

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (18)

What it does: Helps banks, lenders, and enterprise companies identify trustworthy and creditworthy customers in seconds with the power of AI.

When it was founded: 2017

Last post-money valuation: $115 million, according to the company (2023)

Total raised: $38 million

CEO: Ronan Burke

Founders: Conor and Ronan Burke

Select investors: Threshold Ventures, Y Combinator, Crosslink Capital, Uncork Capital, and Foundry Group.

Kalshi

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (19)

What it does: A federally regulated financial exchange that allows investors to trade directly on the anticipated outcome of future events.

When it was founded: 2018

Last post-money valuation: $120 million, according to PitchBook (2021)

Total raised: $36 million

CEO: Tarek Mansour

Founders: Tarek Mansour and Luana Lopes Lara

Select investors: Sequoia Capital, Neo, VentureSouq, LYVC, Mantis VC, Human Capital, Y Combinator, Justin Mateen, Charles Schwab, Henry Kravis, and SV Angel.

Netomi

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (20)

What it does: Enables conversational AI solutions so clients canresolve 80% of routine customer service inquiries, decrease resolution time, increase customer satisfaction and support quality to reduce costs.

When it was founded: 2015

Last post-money valuation: $210 million, according to PitchBook (2021)

Total raised: $58 million

Founder and CEO: Puneet Mehta

Select investors: WndrCo, Fin Capital, Bare Ventures and Eldridge.

Obie

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (21)

What it does: An insurance technology solution designed for real-estate investors to get quotes in under five minutes.

When it was founded: 2017

Last post-money valuation: $155 million, according to the company (2023)

Total raised: $39 million

CEO: Ryan Letzeiser

Founders: Ryan Letzeiser and Aaron Letzeiser

Select investors: Battery Ventures, MetaProp NYC, Thomvest Ventures, Brick & Mortar Ventures, DivcoWest, Y Combinator and FundersClub.

Playbook

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (22)

What it does: Creates an organized home base for all creative work to make it easy to share and collaborate on visual projects.

When it was founded: 2019

Last post-money valuation: $90 million, according to PitchBook (2022)

Total raised: $22 million

CEO: Jessica Ko

Founders: Jessica Ko and Alex Zirbel

Select investors: Bain Capital Ventures, Founders Fund, Maple VC, Abstract Ventures, Blank Slate Ventures, Elad Gil, Hyphen Capital, Blank Ventures, Caffeinated Capital

Rain

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (23)

What it does: A voluntary financial wellness benefit for employees.

When it was founded: 2019

Last post-money valuation: $250 million, according to PitchBook (2023)

Total raised: $129 million

CEO: Alexander Bradford

Founders: Alex Bradford and Jennifer Terrell

Select investors: QED Investors, Invus Opportunities, Ensemble VC, Tribe Capital, Patamar Capital, Dreamers VC, Realm Capital Ventures, and WndrCo.

Reggora

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (24)

What it does: Appraisal management software for mortgage lenders and residential appraisers.

When it was founded: 2016

Last post-money valuation: $160 million, according to PitchBook (2020)

Total raised: $46 million

CEO: Brian Zitin

Founders: Brian Zitin, William Denslow

Select investors: Spark Capital, Boston Seed Capital, 1984 Ventures, Shine Capital, Tupancy Capital, Gutbrain Ventures, and GreenPoint Partners.

Roboflow

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (25)

What it does: Empowers developers to easily build their own computer-vision applications.

When it was founded: 2020

Last post-money valuation: $155 million, according to PitchBook (2021)

Total raised: $22 million

CEO: Joseph Nelson

Founders: Joseph Nelson and Brad Dwyer

Select investors: Craft Ventures, Quiet Capital, A* Capital, Earl Grey Capital, Max Altman, Sam Altman, DJ Patil, Realist Ventures, Mike Maples, Harry Hurst, Joe Morrissey, Cassidy Williams, Greg Brockman and Jack Altman.

Superplastic

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (26)

What it does: A global entertainment brand that creates and manages a roster of world-famous synthetic celebrities and influencers.

When it was founded: 2020

Last post-money valuation: $168 million, according to PitchBook (2022)

Total raised: $28 million

Founder and CEO: Paul Budnitz

Select investors: Amazon Alexa Fund, GV, Kakao Entertainment, XRM Media, Animoca Brands, Kering, Sony Music Entertainment, Wejchert Capital, Galaxy Digital Holdings, Nomu Ventures, Scribble Ventures, Day One Ventures, Craft Ventures, Realm Capital Ventures, Kearny Jackson, and Betaworks Ventures.

Strangeworks

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (27)

What it does: A collaboration of hardware, software, education and service providers, working to develop and test quantum and future computing technologies.

When it was founded: 2017

Last post-money valuation: $124 million, according to PitchBook (2023)

Total raised: $28 million

CEO: William Hurley

Founders: William Hurley, David Cardona and Justin Youens

Select investors: Hitachi Ventures, RTX Ventures, Lightspeed Venture Partners, Raytheon Technologies, GreatPoint Ventures, Ecliptic Capital, and Ultratech Capital Partners

WorkRamp

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (28)

What it does: Training software that helps customer-facing teams onboard, train, and certify their employees.

When it was founded: 2015

Last post-money valuation: $210 million, according to PitchBook (2022)

Total raised: $67 million

CEO: Theodore Blosser

Founders: Theodore Blosser, Arshdeep Mand, and Percia Safar

Select investors: Slack Fund, Salesforce Ventures, Susa Ventures, PeopleTech Partners, GTMFund, DNA Capital, UpHonest Capital, Hat-trick capital, and OMERS Ventures.

Xata

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (29)

What it does: A serverless data platform to match users' development workflow.

When it was founded: 2020

Last post-money valuation: $175 million, according to PitchBook (2022)

Total raised: $35 million

Founder and CEO: Monica Sarbu

Select investors: Index Ventures, Redpoint Ventures, Operator Collective, XFactor Ventures, Firstminute Capital, Andreas Klinger, SV Angel, Shay Banon, Neha Narkhede, Guillermo Rauch, Stephanie Schatz Friedman, Elad Gil, Christian Bach, Liu Jiang, Mathias Biilmann, Charlie Songhurst, Keenan Rice and Uri Boness.

Zendar

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (30)

What it does: Develops high-definition radar for autonomous vehicles.

When it was founded: 2020

Last post-money valuation: $59 million, according to PitchBook (2022)

Total raised: $22 million, according to PitchBook

CEO: Vinayak Nagpal

Founders: Vinayak Nagpaland Jimmy Wang

Select investors: Hyundai Mobis, Alumni Ventures Group, Third Round Analytics Capital and Mandra Capital

Zerion

The 30 early-stage startups most likely to become tech's next unicorns, according to a proprietary AI model known as 'Moneyball for VC' (31)

What it does: Creates blockchain-based products to provide a secure space to track and manage cryptocurrency.

When it was founded: 2016

Last post-money valuation: $142 million, according to PitchBook (2022)

Total raised: $22 million, according to PitchBook

CEO: Evgeny Yurtaev

Founders: Vadim Koleoshkin, Alexey Bashlykov, Evgeny Yurtaev

Select investors: Wintermute Ventures, Coinbase Ventures, Alchemy Ventures, Placeholder Capital, Mosaic Ventures, Polymorphic Capital, Yunt Capital, Press Start Capital, Signum Capital, Anton Bukov, Grégoire Le Jeune, Sergej Kunz and Orest Gavryliak.

FAQs

What percentage of startups become unicorns? ›

While it's not impossible, attaining unicorn status can be incredibly difficult. In fact, a business only has a 0.00006% chance of becoming a unicorn, and it takes an average of seven years for nascent startups to grow into unicorns. That being said, there are startups that beat the odds. How do they do it?

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What are early stage tech startups? ›

An early-stage startup begins with a potentially scalable idea for a product or service targeting a market that is poised to generate value.

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What are unicorns in venture capital? ›

Unicorn is the term used in the venture capital industry to describe a startup company with a value of over $1 billion. The term was first coined by venture capitalist Aileen Lee in 2013.

Get More Info Here ›

What is the early stage business model of a startup? ›

Early stage business models often involve finalizing your product or services and gathering market data. This is also called the seed stage of a startup. In many cases, it also includes getting enough funding to support product development.

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What percentage of startups get VC funding? ›

Only 0.05% of startups get VC funding.

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Which is the fastest startup to become unicorn? ›

In November 2021, Mensa Brands raised $135 million at a valuation of nearly $1.2 billion, making it the fastest Indian startup to reach unicorn status! The company is backed by prominent equity investors like Tiger Global Management, Falcon Edge Capital, Accel, and Norwest Venture Partners. Mukesh Bansal (cult.

Learn More Now ›

What is an early stage VC company? ›

The common definition of early stage company is pretty simple. Early stage companies are defined as having tested their prototypes, refined their service model and prepared the business plan. Some early stage startups might be making early stage revenue, but are usually not profitable yet.

Read On ›

Why do early stage startups fail? ›

The top 4 reasons startups fail include: Lack of financing or investors, running out of cash, lack of market demand or poor timing, and people problems.

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How big are early stage startups? ›

Seed stage startups are the riskiest and most dynamic. They're the youngest and the least established, typically with teams of 2-10 people (sometimes just the founders!). Funding: Seed startups typically have raised $1-5M.

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Is Apple a unicorn company? ›

A tech, financial, or fintech companies worth more than $ 100 billion is called Hectocorn. Or there is another name for the company, this corporation is "Super Unicorn". It is not uncommon that one of our familiar names such as Apple, Google, Microsoft, Facebook, Oracle and Cisco are examples of Heactacorn.

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Which VC firms have the most unicorns? ›

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	Investor	Unicorns at Series B+
1	Sequoia Capital	196 196 196
2	SV Angel	41 41 41
3	Accel	72 72 72
4	a16z	67 67 67

11 more rows

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Are unicorn startups rare? ›

Technically speaking, a unicorn company is a startup with a valuation exceeding $1 billion. For venture capitalists, unicorn hunting means investing in companies that they think can quickly scale to that point. These companies are called “unicorns” because they are just as rare as their fairytale counterparts.

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What are early stage startups? ›

An early stage startup is a company that is in its earliest stages of development. This usually means that the company has only recently been founded, has not yet raised any significant capital, and is making minimal investments in its own operations.

What are the 7 stages of startup? ›

Key startup growth stages

Pre-seed stage. In the pre-seed stage, founders define their business idea and prepare for pitching it to potential investors. ...
Seed stage. ...
Early stage. ...
Growth stage. ...
Expansion stage. ...
Maturity stage. ...
Merger and acquisition stage.

Mar 10, 2023

How are early stage startups valued? ›

The discounted cash flow or DCF is the most widely used income approach technique. Income approach techniques seek to determine the value of a company by assessing the value of the future cash flows to be received by the shareholders or the business.

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What is the probability of building a unicorn? ›

Final answer: The expected value of a startup becoming a unicorn, given a probability of 1.1%, can be calculated to be $11 million. This is calculated by multiplying the outcome ($1 billion) by the probability (0.011). This statistical average is a theoretical value and actual outcomes may vary significantly.

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What is the survival rate of startups? ›

The failure rate for new startups is currently 90%. 10% of new businesses don't survive the first year. First-time startup founders have a success rate of 18%.

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How common are unicorn companies? ›

' Such businesses were classified as unicorns due to the scarcity of privately-held startups achieving this billion-dollar valuation — but unicorn companies are no longer so rare. Revisiting the topic in 2023, Lee noted that there are now 532 unicorns in the United States, up from just 39 in 2013.

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What is the average time to become a unicorn? ›

The average time taken for startups to attain unicorn status has fallen from 8.4 years in 2022 to only 5.5 years in 2023, says a report by Orios Venture Partners, which also says that while India witnessed a total of only 2 unicorns in 2023, it continues to be the third largest nation with the most number of unicorns.