WEBVTT

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Is your data ready for AI?

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Let's find out, in a hundred and three point four seconds.

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Say you run a plumbing firm, and you want AI to draft the forty boiler quotes

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Sarah writes every week.

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That only works if the AI can reach the information it needs,

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and that information is right.

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Gartner expects sixty per cent of AI projects without that to be dropped.

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Step one: pick one job.

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We'll take boiler quotes, like the one John needs.

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Step two: list the data that job uses.

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Customer emails, the price list,

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old quotes, and supplier prices.

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Step three: check each one.

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Can the AI get to it?

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The old quotes are on paper, so no.

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Is it up to date?

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The price list is from 2023, so every quote would come out wrong.

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Is it consistent?

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The inbox says J. Smith, the job sheets say Smith, John.

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You know that's one customer.

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The AI doesn't.

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Is it safe?

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Some of those emails have bank details in them,

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so decide what the AI is allowed to see.

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Step four: score each one.

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Green is ready, amber needs a tidy,

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red is real work.

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Fix the red first.

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Here, that's the paper quotes,

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and AI is good at reading those.

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There are deeper levels to all this,

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and that's where Hone comes in.

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We're the AI engineers who find where it fits in your business,

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then build it and keep it running.

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Pick a job, list its data, check it,

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fix the red.

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A hundred and three point four seconds.