Without ProdRescue
- 2+ hours log digging
- Slack back-and-forth
- Guess-based RCA
ProdRescueIncident workspace
Evidence-first incident RCA
Your last incident cost real money.Find the root cause, with proof, in ~120s.
Paste logs, drop a Slack thread, or run /incident where you already work. Every RCA claim cites the exact line that proves it—not generic AI filler.
Time to root cause
0s
Typical focused run
Confidence on last run
0%
Cited to log lines
Where it lives
Slack-first
/incident in your channel
Add to Slack
Not on Slack yet? Open the workspace and paste logs—one full analysis included free.
No signup requiredEphemeral processing95% confidence scoring
incidents
war-room · 12 members · production
YOMLKPAI
12ML
Maya Lopez11:14
checkout-api alerts firing 🚨 — anyone else seeing 5xx?
KP
Kai Park11:14
yep, PSQLException pool exhausted — started ~17:31. tied to the v2.15.0 deploy?
Message #incidents…
Live preview — same flow runs in your channel after /incident.
With ProdRescue
- 2-minute first draft
- Evidence-linked root cause
- Clear next fix actions
If an engineer hour costs ~$50, one 2-hour incident is ~$100+ in debugging time. A $5 run is usually cheaper than one incident hour.
After your free run: use $5 pay-per-run for the next deep dive, or Pro when you want unlimited analyses and /incident in Slack.
Integrations · models · clouds
Plays well with the stack you already ship
SlackGitHubOpenAIAnthropicGeminiDatadogSentryPagerDutyAWSGoogle CloudKubernetesVercelNext.jsPostgresRedisGrafanaPrometheusNotionJiraLinearSlackGitHubOpenAIAnthropicGeminiDatadogSentryPagerDutyAWSGoogle CloudKubernetesVercelNext.jsPostgresRedisGrafanaPrometheusNotionJiraLinear
AWSGoogle CloudKubernetesVercelNext.jsPostgresRedisGrafanaPrometheusNotionJiraLinearSlackGitHubOpenAIAnthropicGeminiDatadogSentryPagerDutyAWSGoogle CloudKubernetesVercelNext.jsPostgresRedisGrafanaPrometheusNotionJiraLinearSlackGitHubOpenAIAnthropicGeminiDatadogSentryPagerDuty
The problem
Debugging incidents is messy
Logs are noisyErrors are unclearEveryone guesses
ProdRescue shows what broke—with line-level citations, not vibes.
Evidence mapping
Every claim, traced to a log line.
Not just “the AI said so.” Every sentence in a ProdRescue RCA carries a numbered citation back to the exact log line that proves it — clickable, auditable, and printable in the PDF.
Generated RCA — claims
Tap a claim to jump to its source. In your real report, every citation is a clickable link to the exact log line.
checkout-api · productionsource.log
- INFO[deploy-runner]release="v2.15.0" pool_size=10 prev_pool_size=30 changed=true
- ERROR[checkout-api]request_id=ab12c upstream_timeout_ms=30000 endpoint="/cart/checkout"
- FATAL[checkout-api]org.postgresql.util.PSQLException: connection pool exhausted (active=10/10)
- WARN[checkout-api]fallback=redis-cache cache_miss_rate=0.94 cart_ops_affected=true
- ERROR[edge-router]service="checkout-api" 5xx_rate=0.73 window=60s requests=4218
- INFO[deploy-runner]rollback initiated from="v2.15.0" to="v2.14.3" reason="db_pool_exhaustion"
- INFO[checkout-api]pool recovered active=12/30 5xx_rate=0.04 status="normalizing"
Every claim is grounded in raw evidence — no AI guesswork.
Zero hallucinations policyClick any [N] to open the source lineCitations survive into the executive PDF
Same rule for Slack
And every Slack message gets the same citation.
When you run /incident in Slack or paste a thread, ProdRescue treats human chatter, pager events, and bot messages as evidence — each RCA claim points back at the exact message in your war room.
RCA from Slack — claims
Tap a claim to jump to its Slack source. In a real RCA, every citation is a clickable link to the exact message in the war-room thread.
#incident-checkout8 msgs
- PagerDutyApp17:31
Triggered:
checkout-api 5xx spike· severityP1· routing to #incident-checkout - Jenny Liu17:31
Seeing
PSQLException: pool exhausted (active=10/10)— that 17:25 deploy from alex ? - deploy-runnerApp17:32
Release
v2.15.0shipped 17:25 ·pool_size: 30 → 10(config drift) - Alex TanakaOn-call17:33
Redis cache_miss_rate climbed to
0.94— cart traffic is fanning straight back to the saturated DB. - edge-routerApp17:33
Window 60s ·
5xx_rate=0.73·requests=4218· service=checkout-api - Jenny Liu17:34↳ replying to msg 3
Rolling back to
v2.14.3now. oncall-platform standing by. - deploy-runnerApp17:35
Rollback complete ·
v2.14.3live · reason=db_pool_exhaustion - Jenny Liu17:36
Pool back to
active=12/30·5xx_rate=0.04· I think we're recovering. ✅
Bots, humans, and pager events — all cited the same way.
PagerDuty + Opsgenie events cited inlineHuman chatter mapped just like log linesBot deploys, rollbacks & mentions preserved
Sample
Demo output
Root cause: DB connection pool exhausted
Fix: Increase pool size (10 → 30)
Preview — full confidence scoring and exports unlock in the workspace. Run your free analysis →
Product
Everything in one workspace
Structured output for production—not another noisy chat thread.
Find the root cause
Pinpoint what broke from raw logs in seconds.
Understand logs instantly
Turn noisy traces into a clear failure story.
Get fix suggestions
Receive next actions you can ship right away.
Why not generic AI
Built for production reliability
Stop cowboy troubleshooting. Run structured incident response.
ProdRescue is designed for incident workflows, not generic chat. It verifies claims with evidence, filters noisy logs, and connects cross-stack signals into a clear root-cause path.
01Pillar
Evidence over guesses
Every conclusion maps back to real log lines.
Proof
Claim + source line references in one report.
02Pillar
Workflow, not chat noise
Output is structured for incident response and handoff.
Proof
Timeline + RCA + action items in board-ready format.
03Pillar
Context filter for noisy logs
ProdRescue pre-filters signal before deep analysis.
Proof
Error/warn + correlation context, not 5k-line dump.
04Pillar
Multi-stack incident context
Logs, Slack context, and deploy signals are reconciled.
Proof
Cross-team symptom + root-cause chain in one narrative.
Board-ready exports
Copy your RCA and paste directly into your incident ticket workflow.
JiraConfluenceNotion
Context filter · multi-stack
Input stream
5,000 raw lines + Slack thread + deploy metadata
ProdRescue output
Relevant error chain, correlated IDs, cross-team narrative with evidence links.
Example: Frontend reports latency, but correlated backend logs show DB connection timeout after a recent deploy. ProdRescue links the timeline, evidence lines, and fault boundary in one RCA.
Pricing
Simple, transparent
Default path: start free in the workspace, then add $5 runs when incidents are occasional—or Pro when your team lives in Slack and runs RCAs often.
Transparent usage · No surprise seat fees · Upgrade or downgrade anytime
Pick in one glance
- Exploring or one incident a quarter? Stay on Free, then buy a $5 run when you need another full-depth RCA.
- On-call most weeks and want
/incidentin-channel? That's Pro ($29/mo after trial)—unlimited analyses, no per-run meter.
Starter
Free
$0
1 analysis included
- Fast RCA preview
- Root cause + fix summary
- No migration required
After your free run
Pay-per-use
$5/ run
Occasional incidents—pay only when you need depth
Flat price · no seat math
- Full incident debugging output
- Best when RCAs are rare or unpredictable
- Buy credits inside the workspace when you're ready
Teams in Slack
14-day trial · then billingPro
$29/ mo
Unlimited analyses + in-channel /incident
- Unlimited analyses (no per-run meter)
- Slack in-channel RCA (/incident, mentions)
- Built for weekly on-call and recurring incidents
- 14-day trial before your first invoice
Contact
Talk to us about your incident workflow
Share your use case, integration needs, or rollout questions. We will reply with a practical setup path.
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