Prilog

Prilog is a cutting-edge self-healing software designed to revolutionize how engineering teams manage production issues. It eliminates the tedious process of triaging bugs by automatically mapping incidents to exact code paths and drafting review-ready fixes, significantly cutting Mean Time To Resolution (MTTR) by up to 90%. This powerful SaaS is ideal for development teams and SREs looking to streamline their incident response, reduce debugging hours, and transform recurring production issues into actionable, human-approved pull requests. Key Features Automated Incident Mapping: Ingests logs and traces from popular platforms like Datadog, SigNoz, AWS, GCP, and Azure, correlating them to your codebase in GitHub or GitLab. AI-Powered Fix Generation: Leverages advanced AI (OpenAI, Anthropic, Ollama) to draft review-ready code fixes with context and rationale. Workflow Integration: Seamlessly routes follow-up tasks to existing project management tools such as Jira, Linear, or GitHub Issues. Production Remediation Graph: A unique memory system that learns from past incidents, code changes, reviews, and successful remediations to continuously improve fix accuracy and speed. Human-Approved Control: Every generated fix remains reviewable, allowing your team to maintain full control and decide whether to open a PR or route to the backlog. Significant MTTR Reduction: Transforms hours of debugging into minutes of fix review, leading to up to 90% lower MTTR. Use Cases Prilog excels in environments where recurring production issues consume significant engineering time. Instead of engineers spending countless hours sifting through logs and debugging, Prilog automates the initial diagnostic and remediation steps. For instance, a "503 gateway timeout spike" detected in your payments-api service would be automatically mapped to the specific code causing the issue, and a proposed fix would be drafted, ready for a developer's quick review and approval. It's particularly beneficial for teams aiming to shift their focus from reactive firefighting to proactive code improvement. By turning noisy alerts into drafted fixes, Prilog enables teams to address root causes more efficiently, ensuring that every approved fix contributes to a more resilient system over time. This allows developers to concentrate on shipping new features rather than being bogged down by repetitive bug resolution. Pricing Information Prilog offers a usage-based pricing model, starting with a 7-day free trial that includes 3 fixes and 1 project, with no credit card required. After the trial, users can choose from Starter ($249/month + per fix), Professional ($799/month + per fix), or custom Enterprise plans. The pricing is designed to reflect the value delivered, with an emphasis on estimated monthly savings by reducing manual engineering effort and outage exposure. User Experience and Support Prilog is built for seamless integration into existing developer workflows. It connects once to your production logs, code repositories, and task management tools, then operates in the background to surface issues and draft fixes. The emphasis is on providing review-ready PRs, ensuring that the human element of approval and judgment remains central. Support options include email for Starter plans, email and Slack for Professional, and custom support for Enterprise clients, ensuring teams have the assistance they need. Technical Details The core of Prilog's intelligence lies in its "Issue-to-PR engine," which combines advanced AI models like OpenAI, Anthropic, and Ollama with a proprietary memory graph. This graph intelligently correlates incidents, code, reviews, and fixes across services and deployments. It integrates with a wide array of telemetry sources (Datadog, AWS CloudWatch, OpenTelemetry, etc.), code platforms (GitHub, GitLab), and task management systems (Jira, Linear), making it highly adaptable to diverse tech stacks. Pros and Cons Pros: Drastically reduces MTTR and debugging time. Automates the generation of review-ready code fixes. Integrates deeply with existing developer tools and workflows. Learns and improves over time through its "Production Remediation Graph." Maintains human oversight with mandatory fix approval. Strong enterprise-grade security and data privacy features. Cons: Requires initial setup and integration with existing stack. Reliance on AI for fix generation, though human-approved. Pricing scales with usage, which might need careful monitoring for cost optimization. Potential learning curve for adopting a new automated remediation workflow. Conclusion Prilog offers a transformative approach to incident management, turning the reactive process of bug fixing into a proactive, self-healing system. By automating the detection, mapping, and drafting of fixes, it empowers engineering teams to focus on innovation rather than endless debugging. Explore Prilog today to clear your bugs faster and build more resilient software.