For CTOs and engineering leads · Built for product & platform teams — from lean squads to orgs of 200+ engineers, Seed through growth stage
Professional, Board-Ready Incident Reports in 2 Minutes.Even Without an SRE Team.
Stop spending 4 hours digging through logs at 3 AM. Turn noisy alerts, chaotic Slack threads, and log exports into a clear timeline, evidence-backed RCA, and action items you can track — in a board-ready report your leads and execs can actually use.
Pro · 14-day free trial · Full product access
Credit card at checkout — no charge until the trial ends
See real incident report examples→Used by engineering teams from early startups to larger product orgs — Seed through Series B and beyond, including teams of 200+.
Paste logs from Datadog, CloudWatch, Slack, JSON, or any export. Find RCA fast, then generate your report.
Slack · Live
Already using Slack for incidents?
You're already 90% done.
Most teams already run incidents in Slack. ProdRescue turns 200 chaotic messages into one clear RCA timeline with evidence. Datadog shows the problem; ProdRescue tells you why it happened.
"Slack integration's a game changer. We get the report link right in the channel. No more rebuilding the timeline from hundreds of messages."
Your data stays yours
Logs are sanitized in-memory before any AI call. PII, IPs, tokens — redacted locally. Nothing sensitive leaves your session.
Designed for SOC 2 compliance
Controls and reporting structured for SOC 2 readiness.
Local PII Redaction
Sensitive data never leaves your browser.
Zero-Training Policy
Your data is never used to train models.
How it works
Two ways to get root cause fast. Logs or Slack — your choice.
Paste logs
Drop logs from Datadog, CloudWatch, JSON, or any export. No integration required.
Paste logs → Get report
Use Slack
Connect Slack. When an incident happens, the report is generated from your war-room thread.
Connect Slack → Incident happens → Report arrives
From Incident to Resolution
Detect → Diagnose → Fix. Minutes, not hours.
Detect
Incident appears in Slack or logs. ProdRescue ingests context.
Diagnose
AI reconstructs timeline and root cause. Every claim linked to logs.
Fix
Suggested patch → PR in your repo. Review. Merge. Done.
Example: real flow in under 5 minutes
03:47 — Incident detected
"Nil pointer panic in checkout-api" posted to #incidents
03:49 — RCA generated
Root cause: missing nil check in payment processing
03:51 — Fix suggested
PR #847: "Add nil check to PaymentService.Process()"
You know the drill
Production incidents rarely happen at a convenient time.
- 3 AM page. Logs everywhere. Exec asking "what happened?" before you had coffee.
- Slack chaos. 200 messages in #incident. Nobody has the full picture. Context scattered.
- Exec pressure. "What happened?" "How much revenue did we lose?" "When's the postmortem?"
- Revenue uncertainty. Bug fixed. Quantifying impact? Another 4-hour investigation.
- Blame culture. No single source of truth. No evidence. No institutional memory.
Before vs After
Noise → narrative. Tribal knowledge → documented intelligence.
10:23 john: can someone check checkout?
10:24 sarah: seeing 5xx here
10:25 mike: logs? where are logs
10:26 john: s3? cloudwatch?
10:28 ... 200 more messages ...
Nobody has the full picture.
Timeline · Root cause · Evidence [1][6][8]
Understand what broke first. Generate the report in one click when you need it.
Evidence-backed. No finger-pointing.
This chaos → Executive-ready PDF. One click.
The 4-Layer Intelligence Engine
Denoise → RCA → Evidence mapping → Assembly. One model, one job.
Denoising
Cleanup
Clean noisy logs.
RCA
Analysis
Find the root cause. Timeline. Impact. Logs only.
Evidence Mapping
Evidence
Every claim linked to real logs. [1], [6], [8] → source.
Assembly
Assembly
Executive-ready report. Timeline. RCA. Action items.
What you get
- Executive report (optional PDF, one click)
- Timeline with evidence links [1], [6], [8]
- Root Cause + Contributing Factors
- Action Items (owner / priority / deadline)
Fix & PR Flow
Report → evidence → code search → AI fix → branch & PR.
Evidence extraction
From report
[1], [6], [8] and code blocks from the report.
Code search
Repo
Search repo by evidence. Fetch top file contents.
Suggest fix
AI
Report + evidence + code → explanation, risk, diff & file.
Branch & PR
On your approval
You review. We create branch, commit, open PR. No auto-merge.
What you get
- Explainable fix (why + risk)
- Unified diff + full file content for commit
- Optional: create GitHub Issue instead of PR
- Branch protection & approvals unchanged
Engineers stay in control.
Transparency & Evidence
Confidence = how many claims we matched to real log lines. Not AI self-rating.
Generic AI
95%
Self-reported confidence
Model says confident. No way to verify. No log backing.
ProdRescue — Honest Score
60–100%
95% when mapping is solid · 60% when coverage is low
Most claims match logs → 95%. Verified. Low coverage → we cap the score. "Manual review recommended."
Every claim → real log line. No hallucinations. Can't match enough? We tell you.
What Executives See
Real metrics from real incidents. No guesswork. No theater.
P1Payment Processing Degradation
ResolvedRevenue Impact
$67K
net loss
Peak Error Rate
34.7%
Failed Transactions
2,847
MTTR
18 min
vs 24 min avg
Confidence Score
Customer impact, severity, and action owners — all in one report. Every claim linked to logs.
Why teams don't rely on generic AI
Generic AI was never built for incident intelligence.No timeline. No impact. No evidence mapping.ProdRescue was.
Generic AI
- No evidence linking
- No timeline reconstruction
- No incident impact calculation
- No Slack war-room parsing
ProdRescue AI
- 4 models, task-specific — evidence, timeline, impact
- Every claim linked to log line [1], [6], [8]
- Unified timeline + revenue impact & confidence score
- Logs & Slack threads → structured report
Every claim links to evidence. Click [1], [6], [8] — Source Log highlights the line.
No hallucinations. Not in the logs? We don't say it.
Simple, Transparent Pricing
Evidence-first incident intelligence. No training on your data.
One incident cycle = hours of manual work. ProdRescue pays for itself fast.
Solo, Pro, and Team each include a 14-day free trial (card at checkout; no charge until the trial ends). Monthly prices: $49 / $79 / $299. Cancel anytime.
Try your first incident — no login required.
Starter
Free
Saves ~18 senior engineering hours per incident cycle.
- 1 demo incident report (sample data)
- Watermarked PDF
Individual · paste-in
Solo
$49/month
Unlimited incident reports
Saves ~18 senior engineering hours per incident cycle.
Engineers who want board-ready postmortems without Slack or GitHub automation.
- Professional PDF (no watermark)
- Basic workflow — paste logs (Datadog, CloudWatch, JSON, plain text)
- 30-day incident history
- Email support
Card at checkout · No charge until trial ends
Team standard · Slack
Pro
$79/month
Unlimited reports + team features
Saves ~18 senior engineering hours per incident cycle.
When incidents start in Slack, Pro meets your team where they work.
- Everything in Solo
- Slack /rescue · thread fetch
- 6-month incident history
- Evidence-backed RCA — claims tied to log lines [1][6]
- Priority support
Trial terms on Stripe · You won't be charged until the trial ends unless you cancel.
Enterprise engineering
Team
$299/month
Unlimited reports + seats · GitHub
Saves ~18 senior engineering hours per incident cycle.
From postmortem to proposed code fix — shared memory across the org.
- Everything in Pro
- 10 user seats · shared workspace
- GitHub auto-fix · PR from incident findings
- Custom branding on executive reports
- SSO/SAML
- 12-month incident history
- SOC2 compliance-ready reporting
Compare Plans
| Feature | Starter | Solo | Pro | Team |
|---|---|---|---|---|
| Reports | 1 demo | Unlimited | Unlimited | Unlimited |
| Free trial | — | 14 days | 14 days | 14 days |
| Price | Free | $49/mo | $79/mo | $299/mo |
| Slack /rescue · bot | — | Paste only | Full | Full |
| GitHub auto-fix · PR | — | — | — | |
| Incident history (retained) | 30 days | 30 days | 6 mo | 12 mo · SSO |
| SOC2 compliance-ready reporting | — | — | — |
FAQ
Frequently asked questions
Security, integrations, and speed—before you subscribe. Full detail for procurement on the FAQ page.
Is my log data secure and private?
Which platforms do you support for log analysis?
How long does it take to generate a postmortem report?
Can I customize the executive summary for my leadership team?
Does ProdRescue AI integrate with Slack?
Still unsure? —we read every message.
Our Mission
ProdRescue exists for one reason:
Turn 3 AM incident chaos into institutional engineering memory.
Undisciplined docs end. Data-driven transparency begins.
Strong Privacy & Security
- No log retention — we don't store your data
- No training on customer data — ever
- Ephemeral processing — in-memory only, then discarded
Top Incident Struggles
Based on survey of 50+ engineering teams
68%
Struggle writing clear, structured reports
54%
Can't find proper error messages quickly
42%
Spend hours on root cause analysis
Finish your next incident report in minutes
War-room or logs → executive report. Every claim linked.
Get in touch
Turn your next incident into institutional memory.
We'll respond within 24 hours.
Why ProdRescue?
See it in action
Watch your own logs turn into executive-ready reports in seconds.
Security first
No log retention. No training. Ephemeral processing only.
Custom pricing
Team discounts, unlimited credits, and enterprise plans.
Or email us at info@prodrescueai.com
A Note from the Founder

I built ProdRescue because I've lived the 3 AM incident report nightmare. Logs scattered across Datadog and Slack. Exec asking "What happened?" before you've had coffee. Hours spent correlating events into a narrative that holds up to scrutiny.
The vision: every claim in an incident report should trace back to a log line. No hallucinations. No guesswork. A 4-layer pipeline — denoising, RCA, evidence mapping, assembly — so engineers spend time fixing, not writing.
If you're tired of manual postmortems, let's talk. I'm a real person, and I read every message.
I've also published several production engineering playbooks used by hundreds of backend engineers.