AI agents are becoming part of real workflows. Teams need to know which work completed, where handoffs stalled, and whether failures are affecting business outcomes.

axonpush is an agent-native observability platform that connects application telemetry to the business context around it. Activity, journeys, operational health and supporting evidence come together in a workspace that speaks the language of the product.

The screenshots use a synthetic support desk. Every ticket, person, company and metric is made up.

context is the product

An agent deployment has its own vocabulary: work, customers, handoffs, decisions and outcomes. axonpush adapts its operational views to that domain, so engineering and operations teams can investigate the same work with shared context.

MCP-native workflows bring observability into the tools developers already use. Coding agents can help shape a workspace, while people review changes before they become active. That combines agent-assisted setup with governed configuration as the application evolves.

The complete synthetic Support desk workspace overview, including coding-agent connections, a draft review and navigation. — A business-aware workspace with agent-assisted configuration. Synthetic demo.

operational intelligence

Business-aware visibility. Follow current work, journey progress and outcomes through views shaped around the application.
Evidence-led investigation. Connect operational context with trace evidence when available, helping teams move from an affected outcome to the work behind it.
Focused signals. Business activity gets a dedicated view, with system diagnostics available when needed. Teams can investigate useful signals without treating every background check as customer activity.
Governed capture. Metadata-only content capture is the SDK default. Teams choose what additional content to collect, with redaction and retention controls supporting that decision.

built for operational trust

The engineering challenge is keeping the view credible as telemetry arrives late, repeats or crosses application boundaries. Consistent operational state, evidence freshness and visible ingestion health are central to the product.

The health view exposes delays and capture gaps, giving teams the context to distinguish quiet usage from a pipeline that needs attention.

The complete axonpush integration health view, with freshness, lag charts, capture diagnostics, alerts and navigation. — Operational trust starts with visible evidence health. Synthetic demo.

serverless economics

axonpush is built around serverless, event-driven infrastructure. The latest runtime work focuses activity processing on incoming work and meaningful deadlines, reducing unnecessary idle processing.

That cost-focused runtime is in release-candidate validation ahead of a wider hosted rollout. The aim is a practical operating model for teams building and growing agent-powered products.

from infrastructure to product

I started with Easy-Push, a realtime event project, in 2023. axonpush grew from that foundation into an observability platform in 2026. Its current focus is the operational intelligence layer around AI applications: domain context, useful signals and evidence teams can inspect.

where it is now

Explore axonpush. It’s in pilot mode, with the next phase focused on integration quality, operational reliability and a wider rollout.

I’m building it for teams putting AI agents into production and looking for a shared view of what those agents are doing for the business.

log

2026-10-07 · public product overview and complete synthetic demo screenshots.
2026-10-05 · agent-operations pivot deployed to production.
2026-09-24 · errors, issues and the trace explorer shipped.
2026-09-14 · rebuilt server foundation went live.
2026-03 · axonpush picks up where Easy-Push left off.