LLM Bounce Diagnosis · NEW

Bounce storms need a diagnostician.

A purpose-built model reads every bounce cluster in parallel — by default. Nothing to configure. Nothing missed.

50+ failure modes 100% coverage 0 config 40s to a diagnosis
The failure-mode map

Every way mail fails, catalogued

Checks run on every bounce cluster.

Reputation & throttling

9 modes — blocklist hits, throttling and sender-score decay.

Hard bounces & suppression

11 modes — dead addresses, typos and stale lists.

Auth & alignment

8 modes — SPF, DKIM and DMARC failures by hop.

Content filtering

7 modes — spam triggers and URL reputation flags.

Rate limits & deferrals

6 modes — 4xx greylisting and per-IP ceilings.

Vendor-side incidents

10+ modes — provider outages and upstream queues.

The problem

Why bounce storms linger

1

Cryptic SMTP replies

A 5.7.1 from one vendor means six different things — and the queue does not translate itself.

2

Vendor finger-pointing

SendGrid says content, the receiver says reputation. Meanwhile the queue keeps growing.

3

Fixes by folklore

The last person who understood the bounce codes left two reorganizations ago.

The gap

Forty-five minutes, or forty seconds

45min

median manual triage per bounce storm

40s

to an LLM diagnosis, every time

How it works

Collect, read, fix

Three steps between a bounce spike and a closed incident — the model does the reading, you keep the approve button.

1

Collect

Bounce webhooks from every vendor stream into clusters the moment they land.

2

Read

The model classifies root cause against vendor docs, recent changes and routing history.

3

Fix

It proposes a routing change with the evidence attached — you approve with one click.

See it on your own bounce logs

Thirty minutes, your delivery data, real answers.