When was Q-Ctrl founded?

Q-Ctrl was founded in 2017 and raised its 1st funding round within a year of its incorporation.

Where is Q-Ctrl located?

Q-Ctrl is headquartered in Sydney, Australia.

Who is the current CEO of Q-Ctrl?

Michael Biercuk of Q-Ctrl. They have also founded 1 company.

How many employees does Q-Ctrl have?

As of Sep 30, 2026, the latest employee count at Q-Ctrl is 217.

Is Q-Ctrl a funded company?

Q-Ctrl is a funded company, having raised a total of $166M across 10 funding rounds to date. The company's 1st funding round was a $***** Seed round, raised on Oct 2017.

When was the latest funding round of Q-Ctrl?

Q-Ctrl's latest funding was a $***** Series B round on Oct 08, 2024, with participation from 11 investors.

Where does Q-Ctrl rank among its competitors?

Q-Ctrl ranks 1st amongst 6 active competitors, of which 2 are funded. It stands 1st in terms of total funding among its competitors. The most recent competitor to raise funding was Q-Ctrl, which secured $59M in Oct, 2024.

Who are the top competitors of Q-Ctrl?

Q-Ctrl's top competitors include QuantrolOx, Isingai and Andrew Briggs. Among them, Q-Ctrl secured the most recent funding round in October, 2024.

Q-Ctrl - 2026 Company Profile, Team, Funding & Competitors

Company Details

Developer of cloud-based firmware to stabilise qubits from quantum decoherence. The technology uses engineering-inspired transfer functions to provide realistic error budgeting and closed-loop control stabilisation techniques for mitigating hardware errors. It also provides advanced control protocols to reconstruct sensor features and provide quantum clock stabilisation.

Website: q-ctrl.com
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Key Metrics

Founded Year

2017

Location

Sydney, Australia

Stage

Series B

Total Funding

$166M in 10 rounds

Latest Funding Round

Series B, Oct 08, 2024, $*****

Investors

Horizons Ventures & 25 more

Ranked

1^st among 6 active competitors

Employee Count

217 as on Sep 30, 2026

Similar Companies

Tamr & 4854 more

View Q-Ctrl's full profile

Q-Ctrl has raised a total funding of $166M over 10 rounds. Its first funding round was on Oct 2017. Its latest funding round was a Series B round on Oct 08, 2024 for $*****. 11 investors participated in its latest round. Q-Ctrl has 25 institutional investors and 1 angel investor.

Here is the list of recent funding rounds of Q-Ctrl:

Filter this list

Date of Funding	Funding Amount	Round Name	Post-Money Valuation	Revenue Multiple	Lead Investors	Other Investors
Oct 08, 2024	2531850	Series B	3945437	9182853	8737253	9704146
Feb 06, 2024	3093544	Grant (prize money)	5105113	5495014	4281477	Gov
Jan 30, 2023	8786183	Series B	4189172	8895576	Salesforce Ventures & 3 more	Airbus Ventures & 5 more

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View details of Q-Ctrl's funding rounds and investors

The founders of Q-Ctrl is Michael Biercuk. Michael Biercuk is the CEO of Q-Ctrl.

Here are the details of Q-Ctrl's key team members:

Michael Biercuk: Founder & CEO of Q-Ctrl.
Contact Info: 1 email address

View details of Q-Ctrl's Founder profiles and Board Members

Q-Ctrl's employee count trend

Q-Ctrl has 217 employees as of Sep 26. Here is Q-Ctrl's employee count trend over the years:

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Top competitors of Q-Ctrl include QuantrolOx, Isingai and Andrew Briggs. Here is the list of Top 10 competitors of Q-Ctrl, ranked by Tracxn score:

Rank	Company Details	Short Description	Total Funding	Investors	Tracxn Score
1st	Q-Ctrl 2017, Sydney (Australia), Series B	Developer of cloud-based firmware to stabilise qubits from quantum decoherence	$166M	Salesforce Ventures, Mindrock Capital & 24 others	65/100
2nd	QuantrolOx 2021, Espoo (Finland), Seed	Provider of AI-enabled quantum computing software	$15.9M	Oxford Science Enterprises, 2xN & 10 others	61/100
3rd	Isingai Unfunded	Developer of artificial intelligence models for quantum processor control systems	-	-	16/100
4th	Andrew Briggs Unfunded	Developer of nanomaterials and machine learning software for quantum technologies	-	-	16/100
5th	Yao 2019, Unfunded	Open source framework for quantum computing	-	-	16/100
6th	First QFM Sweden, Unfunded	Developer of machine learning foundation models to enhance quantum computing performance	-	-	16/100