8,142 raw lines -> 6 failure groups
The largest failure group clusters around payment gateway timeouts and correlates closely with the latest production deployment.
Built for solo developers, teams, and enterprise responders
Turn noisy incident logs into ranked failure groups.
Upload or paste one incident window. HendrixMojo finds the failure patterns, shows the evidence, and gives your team a shareable report. Upload plaintext logs, JSON, NDJSON, stack traces, HAR exports, packet captures, or ZIP/TAR/GZ incident bundles. HendrixMojo ranks the failure groups and keeps representative evidence in view before the advisory layer weighs in.
Visual proof
See the kind of reduction HendrixMojo gives you before you read another raw stack trace.
Payment timeout spike
412 occurrences • checkout-api, payments-worker, edge-gateway
Start with the failure group that explains the rest of the incident.
Start with the payment timeout group. It is the highest-volume failure group, it began immediately after the latest deployment, and it likely explains the secondary retry backlog.
How HendrixMojo works
Upload, group, and share without turning triage into a manual sorting exercise.
Upload or paste one incident window
Bring in the same messy inputs the on-call team already has: raw log files, JSON or NDJSON streams, ZIP/TAR/GZ archives, HAR exports, and multiline stack traces. Highlights: Plain text logs, NDJSON / JSON logs, HAR exports, PCAP / PCAPNG captures, ZIP / TAR / GZ archives, Multiline stack traces.
Review ranked failure groups
HendrixMojo reconstructs multiline events, normalizes noisy values, and surfaces the failure groups that deserve attention first. Highlights: Ranked failure groups, Occurrence counts, Impacted services.
Inspect representative evidence
Open the lead stack traces, examples, services, and counts behind each group before you decide what likely matters. Highlights: Representative examples, Evidence before explanation, Lead stack traces.
Share the outcome
Once the failure groups tell a clear story, save a report, export the evidence, or draft an incident update without rewriting the analysis from scratch. Highlights: Saved reports, Markdown, JSON, or CSV export, Incident-ready draft.
Reuse prior reports when the issue returns
Reopen the saved report or source analysis the next time the same failure family shows up instead of starting from a blank page. Highlights: Reopen later, Source analysis link, Team memory.
Audience fit
HendrixMojo should feel useful whether you debug alone, triage with a team, or add governance later.
During triage: See the failure families before the raw noise wins
Start with ranked failure groups so the biggest patterns are visible before anyone spends ten minutes skimming duplicate stack traces.
With teammates: Share one analysis instead of pasted snippets
Keep the failure groups, representative evidence, and likely next step in one report the team can review without rebuilding the incident story from scratch.
When it returns: Reuse the report when the same issue comes back
Saved reports turn one finished analysis into team memory, so repeated incidents start from prior evidence instead of another blank Slack thread.
Debug a specific log problem
Use these pages when you already know the kind of issue you are trying to untangle.
Evidence-First Incident Log Triage
Upload or paste one noisy incident window, inspect ranked failure groups, and keep the AI layer grounded in evidence.
Open pageUpload Logs And Find Repeated Errors
Bring exported log snippets, JSON, or stack traces into one analysis and get back ranked failure groups plus a report the team can reuse.
Open pageCapability and support
Use these lower-page routes for deeper setup, connected tooling, and product support after the core upload-and-group flow makes sense.
Supported inputs
Bring the same messy incident window the team already has, from plaintext and JSON to NDJSON, HAR exports, packet captures, ZIP/TAR/GZ archives, and multiline stack traces. Supported inputs: Plain text logs, NDJSON / JSON logs, HAR exports, PCAP / PCAPNG captures, ZIP / TAR / GZ archives, Multiline stack traces, Optional advanced target queries.
What you get back
HendrixMojo returns ranked failure groups, representative evidence, and a readable report so the team can decide what matters without sorting raw logs by hand.
Why teams keep it around
Saved reports and reopened analyses become team memory for repeated incidents, follow-up work, and calmer incident reviews.
Pricing reassurance
Start free, work solo, scale to teams, and add enterprise controls only when you need them.
Prove it first: Use the sample, then one incident window
The first question is whether the ranked failure groups and evidence feel trustworthy on your incident, not whether you need a broader platform.
Make it shared: Give the team one report it can act on
The useful shared artifact is a readable report tied to the evidence, not another dashboard or a rewritten incident summary.
Keep the memory: Reuse prior reports when the issue returns
The durable value is reopening a past incident, not re-triaging the same failure family from scratch every time it shows up again.
Frequently asked questions
Can I see a finished analysis before I upload anything?
Yes. Open a public sample analysis first, then create a free workspace when you are ready to run the same flow on your own incident window.
What should I upload or paste?
Bring one noisy production incident window: plaintext logs, JSON, NDJSON, HAR exports, multiline stack traces, packet captures, or ZIP/TAR/GZ bundles of supported files. HendrixMojo is built for the messy exports teams already have during triage.
Who is HendrixMojo best for?
Small on-call engineering teams at SaaS companies are the clearest fit. HendrixMojo is strongest when a team needs to turn one noisy incident window into ranked failure groups, evidence, and a shareable report quickly.
Why teams choose HendrixMojo
Evidence-first incident analysis for teams that need failure groups fast.