The world's first LLM specifically built for DevOps

Our large language model (LLM) can understand and reason through any and all observability data, including unstructured data, so that you can rapidly restore software and systems to health.

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Root Cause Analysis

Incident RCAs in seconds. Our LLM has a vast understanding of incident types. Once an incident has occurred, the LLM will automatically consult the relevant observability data and generate a custom playbook on the fly.

Our LLM will conclude its debugging playbook when it has found enough evidence to support its hypothesis, including root cause and mitigation of the incident.

We believe in grounding our LLM to evidence found in your systems so that engineers can easily follow a step-by-step debugging flow and verify its results.

Clustered and Repeated Incident Alerts

Flip groups repetitive alerts and incidents by identifying causal relationships.

Most alerting and incident management systems contain a high percentage of noise and repetition. Flip is able to logically cluster alerts to help developers cut through false positives and the noise, while also giving developers an “urgency” index to determine if the incident is something that needs immediate attention.

Trace Intelligence

Flip can summarize problematic code pathways based on thousands of traces in seconds.

Traditional APM systems require developers to investigate thousands of individual traces with hundreds of spans to identify microservice patterns that cause latency or other performance issues. This type of manual debugging can take hours or days. Flip Trace Intelligence specializes in identifying the subset of microservice call chains that cause performance bottlenecks.

Log Summarization & Semantics

Flip generates human readable explanations and summaries from millions of log lines.

Our LLM specializes in understanding unstructured, semi-structured and structured log messages. Logs are notoriously noisy and debugging with logs often feels like looking for a needle in a haystack. Crafting the right query into observability systems is a challenge, followed by sifting through hundreds or thousands of repetitive log lines. Our LLM can parse through hundreds of thousands of log lines and identify the log lines that are the most relevant to the issue being investigated.

Prediction & Catastrophic Pattern Detection

Flip can predict catastrophic incidents that may cause availability drops in your systems.

Flip’s forecasting capability can dive into specific interaction patterns in your application and infrastructure that can cause downtime or degradation to customer experience. Our LLM will surface a “future incident” with a timeline, the evidence supporting it, and mitigation recommendations.

Integrations into ChatOps and Incident Response Tools

Flip integrates seamlessly with your system to grant your entire team real-time visibility into business disruptions & root causes.

All of the information Flip presents can be easily integrated into existing ChatOps and Incident Response tools used in your incident management processes, helping enterprise developers maintain context within existing incident management workflows and tools. 

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