AI Summarization
Condenses technical error logs into simple, actionable summaries so your team can focus on fixing — not parsing.
Pig.engineer transforms complex error logs into clear, human-readable reports. Like a truffle-hunting pig, it digs deep into raw data to uncover patterns, highlight root causes, and present insights anyone can understand.
We built pig.engineer after one too many 2 am incidents staring at thousands of log lines. The pig sniffs out what matters so you don’t have to.
Learns your stack’s error history to spot recurring issues before they become incidents.
Summaries readable by your on-call engineer and your VP — no jargon required.
Paste a log, connect a stream, or drop a file. Insights in seconds.
Error stream
Pig found it: Expired JWT causes auth failure → memory leak → DB drop. Fix token refresh first.
Three steps. No configuration. No PhD in log parsing required.
Paste raw text, upload a file, or pipe a live stream. We accept any format — structured, unstructured, or mixed.
Our AI clusters related events, identifies causal chains, and surfaces the root cause — filtering all the noise.
Get a human-readable summary and step-by-step fix. Send it to Slack, Jira, or your incident doc instantly.
A focused set of tools designed to turn chaos into clarity.
Condenses technical error logs into simple, actionable summaries so your team can focus on fixing — not parsing.
Sniffs out underlying problems with intelligent pattern recognition, saving hours of manual debugging.
Clear reports for both developers and stakeholders — no jargon, just clarity.
Send reports to Slack, Jira, Linear, or PagerDuty in seconds. No copy-pasting.
Track how error patterns evolve. Catch regressions the moment they reappear.
Logs processed in-memory, never stored. SOC 2 compliant with end-to-end encryption.
Questions, feedback, or want a demo — we’re all ears (and snout).
We’ll sniff out a reply within one business day.
Join the beta. Free while we’re sniffing out the last bugs ourselves.