Lavashak IO
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About Lavashak IO

Engineers first. Good with people.

We started by building apps and software for start-ups. Today we help organisations of 20 to 500 people turn AI from stalled pilots into tools their teams use every day.

01 — Our story

Why lavashak?

Lavashak is Persian fruit leather: ripe fruit pressed into something concentrated, durable and useful. “IO” is input/output. It’s a fair description of what we try to do with AI: take a lot of raw possibility and press it into a few tools that last.

We’ve spent years shipping web and mobile apps for start-ups, where software has to work on day one and keep working. When our clients started asking for help with AI, we brought the same habits: prototype on real data early, build it properly, and stay until people use it.

02 — How we work

Small team, senior people, short loops.

You work directly with the engineers building your solution. We demo every week, share our working, and hand over everything at the end.

  1. 01

    Pick

    Map the work, data and risk; choose the use cases worth doing.

  2. 02

    Press

    Prototype and build on your data and systems.

  3. 03

    Cure

    Harden it: security, privacy, evaluation, governance.

  4. 04

    Roll out

    Train, support and measure until it's everyday practice.

03 — Values

What we hold ourselves to.

  • 01

    Practical over hype

    We start from the work people do, and we're honest about what AI can and can't do yet.

  • 02

    Built to last

    Tested, documented and secure. We build so your team can own it without us.

  • 03

    People first

    Adoption is the job. We train, listen and adjust until the tool is part of the week.

  • 04

    Plain English

    No jargon, no black boxes. You'll always know what we're doing and why.

04 — Where we are

Based in Melbourne. Working across Australia.

We meet in person in Melbourne and work remotely with teams across the country, on Australian time.

  • Melbourne, VIC
  • Remote across Australia
  • AEST / AEDT hours

Next step

Find your first AI win in two weeks.

A fixed-price readiness sprint with a working prototype on your data.