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    Tech Nova Mindset – Empower Innovation and Forward Thinking
    Home»Startups & Innovation»CoLabs has a new deep tech accelerator tackling the biggest problem founders face
    Startups & Innovation

    CoLabs has a new deep tech accelerator tackling the biggest problem founders face

    kirklandc008@gmail.comBy kirklandc008@gmail.comJune 24, 2026No Comments3 Mins Read
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    Eldin Rostom
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    Everyone knows the ‘fail fast’ mantra.

    Sure if you have a deep well of cash for Plan B, but it only makes sense in a software startup where the sunk costs are nothing like the challenges faced by deep tech.

    That’s the problem Melbourne innovation hub CoLabs wants to solve by launching Kinesis, a new pre-accelerator to help deep tech founders find product-market fit before they commit to building expensive solutions.

    Backed by $397,074 from LaunchVic’s Grants for Pre-Accelerators program – just days before it’s merged with Breakthrough Victoria – Kinesis will support founders developing applied biology, AI-enabled and deep tech startups across sectors including health, agriculture, advanced manufacturing and sustainability.

    The underlying premise is that founders spend more time with users understanding the problem before they potentially waste time on solution people don’t want.

    Product is a global challenge. US firm CB Insights took a deep dive into 431 failed venture-backed startups and nearly half, 43%, cited poor product-market fit as a key reason for failure.

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    Funding as symptom

    CoLabs executive director Andrew Gray said that while startups often run out of funding, that’s usually a symptom rather than the cause.

    “Running out of money is what kills most startups, but it is almost never the real reason,” he said.

    “Underneath it is product-market fit. The founder post-mortems consistently show that building something the market does not need is the leading root cause of failure, and most of those are early-stage teams that never found their market.”

    Gray said Kinesis will put founders in front of real partners and customers early, to find the fit before the well runs dry.

    The startup founders involved receive access to CoLabs’ PC2 laboratories, specialist scientific equipment, co-working facilities and a network of commercialisation experts, industry partners  and investors.

    CoLabs takes no equity. You might also nab $5,000 in non-dilutive funding to support prototyping and early technical validation, with graduated ventures eligible for continued laboratory access and milestone-based support for up to a year.

    The first two cohorts will run through to early 2028, and Kinesis aims to support at least 17 startup teams and graduate at least 15 ventures.

    The program will also host two investor and industry demo days, alongside four public ecosystem events.

    Entrepreneur in Residence Eldin Rostom, founder of respiratory biology startup Diag-Nose, said many technical founders assume commercial success automaticallys follow scientific success.

    “In reality, you can spend millions of dollars and multiple years building something technically brilliant that nobody is willing to pay for,” he said.

     “The earlier founders speak with customers, industry, manufacturers and investors, the more likely they are to build something that can actually survive outside the lab.”

    Applications for the first cohort are now open. Find out more here.

    accelerator biggest CoLabs Deep Face Founders problem Tackling Tech
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    • AI models need more data about biology, and OpenAI is paying to create it
    • Single CAR T Injection Eases Multiple Sclerosis Symptoms in Small Trial
    • AI ‘Actor’ Tilly Norwood Told Me That ‘All Lives Matter’
    • Roundtables: Could AI really kill us all?
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    AI models need more data about biology, and OpenAI is paying to create it

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    Single CAR T Injection Eases Multiple Sclerosis Symptoms in Small Trial

    September 15, 2026

    AI ‘Actor’ Tilly Norwood Told Me That ‘All Lives Matter’

    September 15, 2026

    Roundtables: Could AI really kill us all?

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