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Solutions · Technology Optimisation

See how your technology estate actually fits together.

Pometry maps the real dependencies between your applications, infrastructure and the teams that run them, so single points of failure, vulnerability exposure and wasted spend are visible before they cost you something.

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The challenge

No one has a current map of the estate.

Large institutions run thousands of applications across decades of accumulated infrastructure. The record of how they connect lives in configuration databases, architecture diagrams and the heads of the people who built them.

Documentation describes intent

A CMDB records what was meant to be deployed. It drifts from what is actually running within weeks, and nothing reconciles the two.

Dependencies surface during incidents

The true blast radius of a system is usually discovered when it fails, and the map that emerges from the post-mortem is out of date by the next change.

Spend has no owner

Compute, licence and token spend accrues across teams with no line back to the service consuming it, so nothing can be safely switched off.

What it does

One model of the estate, built from what is running.

Pometry reads your existing sources where they sit: configuration databases, deployment pipelines, code repositories, observability tooling, ticketing and cloud billing.

Discovery

Live dependency map

Applications, services, data stores and the teams that own them, connected from observed behaviour.

Drift detection

Because the model is temporal, you can compare the estate as it is now against any earlier point and see exactly what changed.

Resilience

Single points of failure

Components that many services depend on through paths nobody has mapped, ranked by how much of the estate they would take with them.

Vulnerability blast radius

When a CVE lands, trace every downstream service that inherits the exposure, including the ones reached indirectly.

Efficiency

Where spend goes to waste

Compute and token consumption attributed to the services and teams actually driving it, including capacity provisioned for workloads that no longer run.

Redundant capability

Systems doing substantially the same job for different business lines, surfaced as candidates for consolidation with their dependencies already mapped.

Getting started

Three weeks from engagement to first findings.

A forward-deployed engineer works inside your environment, alongside the stack Pometry is reading.

Discovery

Agree the questions worth answering first, and identify which of your existing systems hold the signal to answer them.

Installation

Deployed on-premise, in your cloud or air-gapped. A single 10MB binary, reading data where that data already sits.

Mapping

The context model is built with minimal engineering resource from your side.

Experience Pometry in action
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Find out how you can close your visibility gap with unique, institutional intelligence.