From error to answer

What happens the second your app breaks.

When something goes wrong in your software, most teams find out when a customer complains. Guardian Logs turns that moment into a quiet, useful signal — in about a tenth of a second. Here’s the whole journey, start to finish.

One-way: we never touch your servers~0.1s to acceptA human confirms every finding

The journey of a single error

// eight checkpoints, one secure lane
  1. 01

    Your app sends it to us

    The instant something breaks, your server quietly ships the error to us over a secure connection. Data only ever flows one way — outward. We never reach back into your systems, so there’s nothing new for an attacker to knock on.

    Under the hoodPush-only over HTTPS. No inbound access, ever.

  2. 02

    We check its ID badge

    Every message carries a unique key that tells us exactly whose it is. Your account’s data — and its AI analysis — can never cross into another customer’s, and no key can read anything back out.

    Under the hoodWrite-only credential. Identity comes from the key, not the message body.

  3. 03

    We scrub out secrets

    Before a single thing is saved, we sweep the message for passwords, keys, and tokens that shouldn’t have been sent — and strip them. A safety net on top of the redaction that already happens on your side.

    Under the hoodDefense-in-depth redaction at ingest.

  4. 04

    We ignore the echoes

    Networks hiccup and retries happen. If the exact same error reaches us twice, we count it once — so your numbers stay honest and nothing gets double-flagged.

    Under the hoodIdempotency keys + a unique index = effectively-once.

  5. 05

    We turn noise into signal

    Five hundred copies of the same bug become one clear issue — not five hundred alarms. Repeat offenders get flagged, and the constant hum of bots and scanners probing your site gets folded quietly out of the way.

    Under the hoodErrors are fingerprinted and grouped; scanner traffic is collapsed.

  6. 06

    We rank by real impact

    We don’t panic over raw counts. We weigh how many people are actually affected and how fast it’s spreading, then grade it in plain terms — so the thing that matters rises to the top.

    All clearMinor issueNeeds attention

    Under the hoodImpact-aware severity: reach and burst-shape, not raw volume.

  7. 07

    AI drafts the likely cause — a human decides

    Our AI reads the error, checks whether a recent code release lined up with it, and writes its best explanation with the evidence behind it. But it only ever suggests. A person reviews and confirms every finding, and nothing is ever changed in your live systems automatically.

    Advisory only · human-in-the-loop · never auto-acts

    Under the hoodAI triage with deployment correlation + cited evidence.

  8. 08

    You see it in plain English

    It lands on a dashboard anyone can read — no engineering degree required. Green means all clear, amber means we’re watching it, red means it may be affecting people. You know what’s happening before your customers do.

    Under the hoodPlain-language executive view, tenant-isolated.

Why it’s built this way

Know what your apps are doing — before your customers do.

One-way

Logs are pushed out to us. We hold no keys to your servers and never connect in.

Isolated

Every record belongs to one account. No customer’s data or AI context touches another’s.

Human-led

AI advises with evidence and confidence. A person makes every call.

Fast

Your app gets a confirmation in about a tenth of a second. The heavy thinking happens after.

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