Lynceus unifies metrics, logs, traces, profiles, events, topology, security, and business KPIs on one platform. Prometheus governs AI inference monitoring. GEOM-db provides the data foundation for cross-modality observability queries.
Ten monitoring tools replaced by one observability platform
Most organizations run 5-10 monitoring tools — Datadog for metrics, Splunk for logs, Jaeger for traces, Sentry for errors, PagerDuty for alerting, Grafana for dashboards — and a team to maintain the integrations between them. When an incident happens, the investigation starts by correlating timestamps across five tools that do not agree on what time it is.
Observability means joining metrics to logs to traces to topology to deployments in real time — so when a latency spike hits, one query returns the metric, the affected traces, the log entries from the failing service, and the deployment that preceded the spike.
Datadog, Splunk, Jaeger, Sentry, PagerDuty, Grafana
Cross-domain joins
Security logs, configurable per type
Causal correlation, not threshold
One platform replaces ten separate monitoring tools. Every signal type is a first-class citizen.
Lynceus observes. Prometheus governs AI. GEOM-db provides the data foundation.
Metrics, logs, traces, profiles, events, topology, uptime, security, real user monitoring, and business KPIs — all on one platform with one query language.
Model drift, inference latency, token cost, guardrail violations, GPU health — monitored in real time. Every AI inference causally traced.
Cross-modality queries join time-series metrics to graph topology to relational deployment data — in one SQL statement. No ETL pipeline between observability tools.
CI/CD pipeline monitoring, deployment tracking, and infrastructure change audit — all on the same platform as production observability.
99% of queries complete under 2ms. The long tail is where the interesting problems live — the 0.1% of queries over 50ms are the ones that tell you what is broken. Most monitoring tools average their latency and hide the tail. Lynceus shows you the full distribution so you can find the outliers before they become incidents.
One platform, ten domains, one query language — from infrastructure to business KPIs.
Ten observability domains on one platform. 99% of queries under 2ms. Causal correlation, not threshold alerting. Self-hosted, managed, BYOC, or hybrid edge.
AI-specific observability — model drift, inference latency, guardrail violations, GPU health. Every inference causally traced and cryptographically signed.
Cross-modality data foundation — join time-series to graph to relational in one SQL statement. No ETL between observability tools.
One platform replaces ten separate monitoring tools. Every signal type is a first-class citizen.
Architecture to delivery
Map your operating constraints with our solutions team and define the right delivery path.