AI for Marketing
Knowing when to use AI in campaigns, and when to keep it out.
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Hiring AI talent is broken. Companies have no real way to tell who knows what they are doing. Practitioners have no way to prove it. Everyone is guessing.
Assertif AI fixes that. Every professional in our marketplace has been tested against work that actually matters: proctored assessments, scenario-based tasks, and a Responsible AI baseline that no chatbot can sit in for.
We pull in the certifications you already recognise (Claude, ChatGPT, Gemini) and stack our own on top, built around real functions: marketing, finance, legal, sales, operations, code, HR, data.
Hire for what someone can actually do. The credential does the vetting for you.
Knowing when to use AI in campaigns, and when to keep it out.
Producing outputs you can actually put in front of an auditor.
Working with legal AI without crossing the lines that matter.
Using AI to reach the right people without making things up.
Designing workflows where AI does the heavy lifting, safely.
Writing code with AI that you would actually ship.
Using AI in hiring without building the wrong assumptions in.
Knowing what an AI output actually means before acting on it.
Not a checklist. A working baseline we test for in scenarios designed to fall apart when someone cuts corners.
What goes into the prompt, and what stays out.
Outputs validated before they become action.
When AI involvement is named, and to whom.
Spotted in the work, not quietly left in.
Knowing when to stop, and whom to escalate to.
Co-Founder
Matthew is a Sydney-based entrepreneur focused on fixing how businesses hire AI talent. He co-founded Assertif AI to bring verifiable standards to a space where credentials have been largely meaningless. His background spans business development, product strategy, and applied AI adoption across Australian markets.
Co-Founder
Dylan leads product and engineering at Assertif AI. He brings a technical background in software and AI systems, with a focus on building assessment infrastructure that is rigorous enough to matter and practical enough to scale.