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I built an AI that tells you your 3 biggest cyber risks every morning

Every morning, most founders open their laptop and hope nothing broke overnight.

I've spent enough time watching how companies actually deal with cyber risk day to day. Not in theory. In practice.

What I saw was a mess of tabs. A Slack alert from the SOC team. A VAPT report from last quarter still sitting unread. A vendor spreadsheet that nobody updates. A compliance checklist that lives in someone's email.

And somewhere in all of that, a real threat quietly doing its thing.

So we built something inside ๐—š๐—ผ๐—ฟ๐—ฑ๐—ผ๐—ป ๐—”๐—œ.
Every morning, you can give a simple command "๐—ฆ๐—ต๐—ผ๐˜„ ๐—บ๐—ฒ ๐˜๐—ต๐—ฒ ๐—บ๐—ผ๐˜€๐˜ ๐—ฐ๐—ฟ๐—ถ๐˜๐—ถ๐—ฐ๐—ฎ๐—น ๐—ฎ๐—น๐—ฒ๐—ฟ๐˜๐˜€ ๐—ณ๐—ฟ๐—ผ๐—บ ๐˜๐—ต๐—ฒ ๐—น๐—ฎ๐˜€๐˜ ๐Ÿฎ๐Ÿฐ ๐—ต๐—ผ๐˜‚๐—ฟ๐˜€". AI scans your entire risk surface suc as SOC alerts, vulnerability findings, dark web exposure, vendor health, compliance gaps and surfaces the top things that actually need your attention today.

๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ -
๐—š๐—ผ๐—ฟ๐—ฑ๐—ผ๐—ป ๐—”๐—œ | ๐——๐—ฎ๐—ถ๐—น๐˜† ๐—•๐—ฟ๐—ถ๐—ฒ๐—ณ๐—ถ๐—ป๐—ด | ๐Ÿญ๐Ÿฑ ๐—”๐—ฝ๐—ฟ, ๐Ÿฌ๐Ÿด:๐Ÿฌ๐Ÿฌ ๐—”๐— 

๐Ÿญ. ๐—–๐—ฟ๐—ฒ๐—ฑ๐—ฒ๐—ป๐˜๐—ถ๐—ฎ๐—น ๐—ฑ๐˜‚๐—บ๐—ฝ ๐—ฑ๐—ฒ๐˜๐—ฒ๐—ฐ๐˜๐—ฒ๐—ฑ โ€” 2,847 records linked to your domain (3h ago)
๐Ÿฎ. ๐—–๐—ฟ๐—ถ๐˜๐—ถ๐—ฐ๐—ฎ๐—น ๐˜‚๐—ป๐—ฝ๐—ฎ๐˜๐—ฐ๐—ต๐—ฒ๐—ฑ ๐—ฅ๐—–๐—˜ ๐—ถ๐—ป ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฝ๐—ฎ๐˜†๐—บ๐—ฒ๐—ป๐˜ ๐˜€๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฐ๐—ฒ โ€” open for 6 days
๐Ÿฏ. ๐—ž๐—ฒ๐˜† ๐˜ƒ๐—ฒ๐—ป๐—ฑ๐—ผ๐—ฟ ๐—ฟ๐—ถ๐˜€๐—ธ ๐˜€๐—ฐ๐—ผ๐—ฟ๐—ฒ ๐—ฑ๐—ฟ๐—ผ๐—ฝ๐—ฝ๐—ฒ๐—ฑ ๐˜€๐—ต๐—ฎ๐—ฟ๐—ฝ๐—น๐˜† โ€” worth a conversation today

No analyst needed. No dashboard archaeology. Just three things, every morning, so your team knows exactly where to start.

We're still figuring out the right signals for different industries. BFSI looks different from a SaaS company, which looks different from a manufacturer.
What does your morning security routine actually look like right now? Curious whether anyone has cracked this or if everyone is still doing the tab-juggling thing.

๐—•๐—ง๐—ช ๐˜๐—ต๐—ถ๐˜€ ๐—ถ๐˜€ ๐—บ๐˜† ๐˜€๐—ถ๐˜๐—ฒ: https://trygordon.ai/

on April 15, 2026
  1. 1

    The โ€˜dashboard archaeologyโ€™ line is painfully accurate โ€” most teams donโ€™t lack data, they lack prioritization under pressure.

    The daily briefing approach makes a lot of sense, especially if it consistently surfaces what actually needs action.

    Curious though โ€” how are you seeing teams validate whether acting on these alerts is actually reducing real risk vs just improving visibility? That feedback loop feels critical but often missing.

    Iโ€™ve been noticing some teams run small, high-intent experiments (fixed low entry, limited participation, strong upside) alongside systems like this to test what actually drives meaningful outcomes โ€” surprisingly effective for early-stage validation.

    Feels like that layer could complement something like this really well. Have you explored it?

  2. 1

    How has the uptake of this been?

  3. 1

    The "tab-juggling thing" is universal โ€” and the real problem isn't the number of tabs, it's that each one requires context-switching into a completely different mental model. SOC alerts speak one language, VAPT reports another, compliance checklists a third. By the time you've translated all three it's 10am and you haven't actually done anything yet.
    The morning briefing format is the right instinct. The hardest part is probably the signal-to-noise calibration you mentioned โ€” what counts as "critical" varies enormously not just by industry but by company stage. A credential dump means something very different to a 10-person startup than to a bank.
    One question worth thinking through: how do you handle the case where the AI surfaces the same top-3 risks three days in a row because nobody actioned them? Does it escalate, or does the founder start tuning it out like every other alert system?

  4. 1

    This is a solid use case โ€” especially the โ€œjust 3 things that matter todayโ€ angle, feels very practical.

    One thing that stood out though โ€” in security tools, trust and perceived seriousness play a huge role even before someone tries it.

    The product itself feels quite sharp, but the โ€œGordon AIโ€ side leans a bit more casual / assistant-like, while the problem youโ€™re solving is actually pretty high-stakes.

    In spaces like this, even small perception gaps can affect how quickly someone takes it seriously enough to try.

    Curious โ€” have you explored how people react to the name itself vs the actual product value?

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