Collect the agreed facts.
Build scheduled collection around approved sources and read-only access. Show when each source was observed and where collection needs attention.
A customer-owned application for your Azure estate, system maps, and architecture knowledge. Built around your sources, your team, and the way you work.
From a single resource to the system around it. Explore how infrastructure, knowledge, and engineering work come together.
Your infrastructure. Your knowledge.
One connected view.
Interactive example · Fictional Meridian estate
300 example records. No live sources connected.
Your sources/Your workflows/Your environment/Your application
Explore the interaction behind the application. This sanitized example shows how systems, infrastructure, and source evidence come together.
● Interactive example using sample data. Live Azure integration patterns inform the delivery; documentation automation, AI tools, and additional connectors are agreed and validated within each customer engagement.
Keep observed infrastructure facts separate from engineering judgment. The application brings collection, review, and accepted documentation into one workflow.
Build scheduled collection around approved sources and read-only access. Show when each source was observed and where collection needs attention.
The preview shows a proposed documentation diff with sources and an engineer’s decision. Connected ticket processing and durable approvals are implementation deliverables.
Compare observations and connect changes to approved tickets where evidence supports the link. Unmatched changes can enter a review queue.
Observed facts carry source context. Engineering judgment carries a review decision.
A workflow we can build around your service desk: connect approved tickets to system context, prepare a proposed solution, and carry the engineer’s accepted decision into the record.
Azure DevOps read integrations provide a starting point. Ticket correlation and document updates are scoped and verified for each implementation. Additional connectors are roadmap options. Product names and logos belong to their respective owners.
Extend your application with a scoped context interface for an approved AI client. We agree the sources, access rules, provider, and evidence requirements as part of your implementation.
Choose a provider that fits your hosting and data requirements. Authentication, credential storage, model access, and data destinations are defined and validated for your deployment.
Start with the sources that matter to your systems. Extend the application with agreed integrations for infrastructure, identity, delivery, and code.
Resource Graph, ARM, cost, identity, and network state — the deployed truth.
Licensing, security-plan coverage, and tenant signals for the estate view.
Delivery signals — projects, pipelines, and work-item flow beside the infrastructure they change.
Repositories, IaC, and deployment workflows joined to the running estate.
A preview of how a cited answer can connect system context, dependencies, and recorded changes. Live AI integration is tailored to your approved provider and evidence sources.
payments-platform runs on the private Kubernetes user pool and depends on postgres-prod (Private Link) and redis-cache. One material change this week: a new private endpoint was added Tuesday 14:32 — captured with evidence and pending owner review.
Start with a customer-hosted application and approved read-only sources. Define the access, identity, review, and audit requirements together.
We tailor the application to your estate and deploy it in your Azure environment, or the hosting you choose. You receive the source, deployment assets, and operating documentation. Your application can evolve independently, with support and further development scoped separately.
Prove the workflow on a contained scope, agree success criteria before access, and leave with a working application plus an approved architecture baseline.
No tenant access is needed for the first conversation.