Flowlines vs Datadog.
Flowlines is not a Datadog LLM Observability replacement, it's a focused behavioral layer that reads the same OTEL traces. Datadog gives you native tracing, per-response evaluations (hallucination, toxicity, safety), and cost and quality dashboards; Flowlines adds what a per-response view can't see, recurring failures grouped into one signal by root cause, behavioral user cohorts, and production prompt-version impact. If you already run Datadog, Flowlines connects to the same OpenTelemetry source.
Datadog LLM Observability is the agent slice of the broader Datadog platform. It captures each request as a trace, groups a session's traces together, and layers on managed production evaluations (hallucination, toxicity, sentiment, topic relevancy, failure-to-answer), plus offline datasets and experiments, sensitive-data scanning, and cost and latency dashboards. It's deep and full-featured, and it lives next to the rest of your infrastructure monitoring.
Flowlines is narrow and behavioral. It reads the same OpenTelemetry traces Datadog can ingest and emit, and concentrates on what a per-response evaluation can't see: recurring failures grouped into a single signal by root cause, happy / at-risk / churning user cohorts, and before/after impact for every prompt version in production. You don't replace Datadog, you read from the same traces.
Datadog is the broad platform, tracing, evals, security, and dashboards, for teams that want their LLM signals sitting next to the rest of their infrastructure. Flowlines is the opinionated behavioral layer for agents specifically: it reads the same OTEL traces and answers the cross-session questions, which cohort is churning, is the agent drifting week over week, did the last prompt deploy actually help, that per-response evals and dashboards aren't built to answer.