See enterprise AI before issues become incidents
Axium Lab provides operational visibility across latency, reliability, cost, quality, and system health so teams can monitor and act with confidence.
Detect issues before they escalate
Axium Lab's observability layer provides teams with the real-time visibility needed to understand performance, control costs, and ensure quality across all AI operations.
Complete visibility across AI operations
Performance & Latency
Track response times, throughput, and performance across all endpoints, models, and workflows with real-time latency monitoring.
Error Monitoring
Detect failures, timeouts, and exceptions across deployments with detailed error tracking and automatic categorization.
Cost & Usage Visibility
Monitor spending across providers, models, and teams with granular cost tracking and budget alerts.
Quality Monitoring
Measure output quality, model accuracy, and response relevance with continuous evaluation pipelines.
Operational Health
Track system uptime, availability, and infrastructure health across all AI operations and dependencies.
Alerting & Incident Awareness
Receive intelligent alerts for anomalies, thresholds, and operational issues before they escalate.
Real-time operational insights
Axium Lab surfaces the metrics that matter, giving teams immediate visibility into system performance and operational health.
Performance Metrics
Detect issues before they escalate
Axium Lab continuously monitors for unexpected changes in cost, performance, quality, and reliability, surfacing anomalies with context and recommended actions.
Cost Spike
mediumUnexpected 40% increase in provider costs detected
Latency Regression
highResponse time degraded from 47ms to 180ms average
Error Spike
criticalError rate increased to 8.2% on production endpoint
Intelligent alerting
Axium Lab uses statistical models and baseline learning to reduce alert fatigue, surfacing only meaningful deviations with contextual information for faster resolution.
From detection to diagnosis
Axium Lab goes beyond surface-level dashboards, giving teams the tools to investigate issues, trace executions, and understand system behavior at every layer.
Execution Traces
Follow request flows through workflows, agents, and model calls with detailed execution traces, timing breakdowns, and dependency mapping.
Endpoint Visibility
Monitor individual endpoints and deployments with granular metrics, request logs, and provider-level performance breakdowns.
Historical Analysis
Query historical data to identify patterns, compare performance over time, and understand long-term trends across all dimensions.
Contextual Search
Search across logs, traces, and metadata to quickly locate specific requests, errors, or anomalies with advanced filtering and correlation.
Complete request traceability
Every request through Axium Lab is fully traceable, from initial endpoint call through workflow execution, model invocations, and final response—with timing, metadata, and provider attribution at every step.
Understand the tradeoffs that matter
AI operations require balancing performance, cost, and quality. Axium Lab helps teams visualize these dimensions together, enabling informed decisions.
Cost Tracking
Monitor spending per model, provider, workflow, and team with real-time cost attribution and forecasting.
Latency Analysis
Track response times across percentiles and identify performance bottlenecks in workflows and deployments.
Quality Metrics
Evaluate output quality, model accuracy, and response relevance with continuous evaluation pipelines.
Multi-dimensional visibility
Axium Lab correlates cost, latency, and quality data across your entire AI stack, helping teams understand how changes in one dimension affect the others.
Bring visibility and control to AI operations
Join enterprise teams using Axium Lab to monitor, diagnose, and optimize their AI systems. Request early access to experience operational clarity built for production.
Currently in development • Built for enterprise teams