01

Spot the noisy log

Prilog monitors GCP, AWS, Azure, Datadog, and Sentry feeds to surface the log bursts worth fixing.

[11:02:07] ERROR checkout.retry panic nil pointer
[11:02:10] WARN  retry loop x6
[11:02:12] INFO  muted · recovery policy
02

Trace it to the code

We cross-match stack traces and repo history to pinpoint the TypeScript service responsible.

matchLog({ file: 'checkout/logging.ts' })
  .find(({ fn }) => fn === 'handleRetry')
  ?.linkCommit('8b2ada1');
03

Draft the fix

Review the suggested remediation and approve a pull request or task without leaving Prilog.

Pull Request draft · GitHub
  • Auto-patch `logging.ts`
  • PR title: “Mute recovered checkout retries”
  • Jira follow-up: LOG-482 created

Why Prilog

One intelligence layer across logs, code, PRs, and your backlog.

Prilog continuously mines production signals, traces the blast radius across your repositories, and proposes the clearest path to resolution before debt slows the roadmap.

Log-to-code correlation

Stitch real-time logs with their exact call sites, related deploys, and regression history to understand severity in seconds.

Human-in-the-loop fixes

Prilog drafts safe patches, highlights side effects, and lets engineers choose whether to open a PR, ticket, or snooze.

Log hygiene automation

Remove redundant noise, tune log levels, and standardize telemetry across services for cleaner on-call dashboards.

Pipeline

How platform teams prevent tech debt pileups.

  1. Monitor. Ingest multi-cloud logs, deduplicate noise, and detect anomalies from stream to snapshot.
  2. Diagnose. Cross-reference repositories, recent deploys, and incident history to explain root causes.
  3. Resolve. Approve generated fixes, launch PRs, or sync directly into work management tools.
  4. Refine. Continuously tune logging strategy to keep observability actionable and compliant.

Plug into your stack

Native integrations across cloud, observability, and delivery.

Prilog connects securely to your infrastructure so every alert, trace, and ticket stays in sync with the AI co-pilot.

Google Cloud AWS Azure Datadog Sentry GitHub GitLab Jira Linear

Full-fidelity ingest

Stream structured logs, traces, and metrics from GCP, AWS, and Azure with security-first scopes.

Delivery ready

Auto-create PRs in GitHub or GitLab, nudge backlog updates in Jira and Linear, and keep audit trails aligned.

Observability aware

Feed Datadog and Sentry context back into the model so false positives get quieted and insights stay relevant.

For engineering leaders & investors

Deliver measurable debt reduction the Board can see.

Prilog turns qualitative log chaos into quantifiable debt burn-down so you can prove operational excellence and investor-ready discipline.

$540k Annual maintenance savings per 40-engineer org*
94% Fixes merged within the same sprint
5 weeks To log hygiene baseline across services

*Based on pilot cohort across fintech and SaaS customers.

Stakeholder dashboard snapshot

  • Debt burn-down -41% QoQ
  • Noise suppression 1.4M logs muted
  • Fix velocity 128 PRs shipped
  • Coverage score 98%

Export audit packets that demonstrate reliability and responsible AI in production.

“Prilog gave us confident fixes for crash-looping services while cleaning up the noisy logging debt that buried us for months.”

Lena Ortiz Director of Platform Engineering, Series B fintech

“Our investors finally see a weekly metric that proves we’re eliminating tech debt instead of letting it age in the backlog.”

Marcus Han CTO, Cloud security startup

Join the private beta

We onboard a limited number of teams each month to ensure smooth integrations and visibility for leadership stakeholders.