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Unomiq AI transforms production telemetry—metrics, events, logs, and traces—into specialized context graphs designed for developers and AI coding agents. These are called melt-o-graphs and they organize raw operational data around system behavior, dependencies, anomalies, and failure signals, making production problems easier to identify, isolate, and understand. Instead of navigating fragmented dashboards or passing large volumes of raw telemetry to an agent, Unomiq AI provides structured, machine-readable context that enables faster resolution, broader issue discovery, and more computationally efficient agentic workflows.

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How it works

  1. Send traces — Instrument your application with OpenTelemetry and send traces to the Unomiq Gateway API.
  2. Attach a unit — Tag traces with a unomiq.unit attribute (e.g., customer ID, tenant ID) to group costs by the entities that matter to your business.
  3. Connect billing data — Export your cloud billing data (e.g., GCP detailed billing to BigQuery) so Unomiq can match costs to traces.
  4. Query costs — Use the Unomiq Engine API or Dashboard to analyze per-request costs, filter by unit, and understand where your money goes.

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Get started

Getting Started

Start sending & monitoring traces

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Guides

Sending traces

Send OpenTelemetry traces to the Unomiq Gateway using a Collector Sidecar or directly from your application.

Attaching a unit to traces

Link traces to logical entities like customer IDs or tenant IDs with the unomiq.unit attribute.

GCP detailed billing export

Enable detailed usage cost export to BigQuery for resource-level cost analysis.

How cost computation works

Learn how Unomiq matches billing data with traces to compute per-request costs.

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API reference

Gateway API

OAuth and trace ingestion endpoints.

Engine API

Query traces, spans, and cost metrics.

Management API

Manage organizations, applications, and API keys.