Equip your agents with the right telemetry
Give them clean, contexutal data to make faster, smarter decisions.
Stop debugging your AI
AI agents need clean, contextual data to operate effectively. Without it, they make costly mistakes, miss critical patterns, and require constant human intervention. Mezmo's Active Telemetry Platform and its Model Context Protocol (MCP) Server deliver the real-time context and intelligent interface agents need to act intelligently and autonomously.
From reactive to proactive intelligence
Structured, noise-free data helps agents identify patters and act faster
Add business, user, and system data to improve agent reasoning and insights.
Telemetry pipelines format, enrich, and route data directly into your AI/ML systems.
Smarter data, better agents
Enable operational AI in minutes with context engineered data sets. Give your agents simple prompts with context fueled accuracy reducing the window of failure to almost none.
Give devs the flexible use of AI to access and act on any high-context telemetry, right within their workflows for a superior experience—without putting budget, performance, or control at risk.
Process telemetry in-stream to accelerate Root Cause Analysis (RCA) with an agentic SRE. Extract key information and spot anomalies with full context – before data is ever stored.
Direct data with intent, reshape and normalize for agentic and human consumption, including "easy button" migration to Open Telemetry. Separate signal from noise by its value, triggering automated actions to dodge spikes or flag faults in real time.
Key capabilities for AI-powered observability
Automatically analyze log patterns and system behavior to identify incident causes.
Remove low-value logs (DEBUG/INFO) to reduce noise and manage costs effectively. Learn more about supported processors.
Decide what stays hot, what moves to cold storage (S3, Azure Blob, GCP), or gets dropped. Learn more about supported destinations.
Stream telemetry data in real-time and replay buffered events for instant incident investigation without waiting for indexing or storage delays.
Continuously analyze telemetry patterns to identify high-volume, low-value data streams and provide actionable recommendations for cost optimization. Learn how to use data profiling.
Automatically adapt pipeline behavior based on real-time conditions, scaling processing capacity and adjusting sampling rates to maintain performance during traffic spikes.
Enhance telemetry data with contextual metadata from external sources, standardize formats, and add business context to improve observability and enable better analysis.
Monitor and control metric cardinality in real-time to prevent exponential cost increases from high-cardinality tags while preserving essential dimensional data.
Real-world use cases from real teams
"Mezmo’s MCP Server analyzed over 160,000 logs and immediately identified our payment service token validation failures affecting all gold-tier customers. What would have taken hours of manual investigation was resolved in minutes with natural language queries."
— DevOps Engineering Lead
"Mezmo's MCP Server analyzed 164,122 raw logs for $0.66, while competitor approaches cost $0.50+ for smaller datasets."
— Engineering Manager
"Successfully identified payment failures, cache leaks, and database connectivity issues accross mutliple services. "
— Site Reliability Engineer
Stop drowning your agents in noise
Start delivering intelligence
- ✔ Schedule a 30-minute session
- ✔ No commitment required
- ✔ Free trial available
