Continuous Analysis

The loop from a standard you wrote to compliant code

Continuous Analysis is our name for the whole cycle, not just the part that runs a scanner. It begins with a standard you authored, carries it into the context of whoever or whatever is writing the code, checks the result against the same standard, scores it, gates the merge on it, and turns what it learns into the next revision of the standard.

Book a Demo Start at the Standards Center

The Continuous Analysis loop

A six stage cycle. Standards are authored in the Standards Center, delivered into the agent's context, used by the agent as it writes, checked again when the pull request is opened, scored and gated at the merge, and turned into insight. The insight stage feeds back into the first stage, so the loop closes rather than ending.

1 Author the standard Policies, principles, language and architecture standards in one governed libraryExplore
2 Into agent context MCP server, agent skills and agent apps deliver it automaticallyExplore
3 The agent writes Compliant by construction, not by correctionExplore
4 Reviewed on the PR Five perspectives, checked against the same standardsExplore
5 Measured and gated A compliance score per file, and a merge gate that uses itExplore
6 Insight Where standards hold, where they slip, and which need to changeExplore

Continuous Analysis runs on every commit and every pull request, not on a nightly schedule.

Stage by stage

What happens at each turn of the loop

Six stages, each owned by a part of the platform. Follow any of them into the detail.

Author the standard

Policies, general and secure principles and language standards are written, reviewed, versioned and published from one governed library.

Deliver it into context

The MCP server, agent skills and agent apps carry the published standards into the agent's working context automatically.

The agent writes

With your rules present and this file's open findings already injected, the change comes back compliant rather than coming back for rework.

Review the pull request

Five review perspectives check the change against the same standards, and propose the compliant rewrite rather than just flagging the fault.

Measure and gate

Compliance is scored per file and rolled up per project, and the merge gate holds anything below the threshold you set.

Turn it into insight

Where standards hold, where they slip, and which ones need to change. That answer becomes the next revision, and the loop closes.

Continuously, not on a schedule

Every commit and every pull request

Webhooks arrive from your source control and CI the moment code moves, orchestration schedules the work, and a cluster of workers carries it out. Nothing waits for a nightly window.

Ingest the event from GitHub, GitLab, Bitbucket or Azure DevOps, and from your CI.
Fetch and diff so the work focuses on what actually changed.
Build and test the way your teams do, extracting coverage as it goes.
Apply your standards and record the result against the branch or pull request.

See how the estate is managed

Built to scale

A cluster that scales to your enterprise

The loop runs on a dedicated, isolated cluster that scales for peak loads, so results keep up with every team even when the whole estate pushes at once.

Dedicated and isolated so your code and your throughput are never shared.
Scales for peak loads with more workers when the queue grows, fewer when it drains.
Results while it is fresh so the agent or the engineer is still in the change.

Guard your branches

The loop ends at the merge gate, on purpose

A loop that only reports is a dashboard. Three independent merge checks turn it into a control: compliance against your minimum score, AI review completion, and human sign-off.

Every commit

and every PR

Six stages

one closed loop

Three checks

at the merge

Insight

back into the standards

Underneath

Rules-based analysis is one input, not the story

Deterministic checks still earn their place on regressions, known-bad patterns and legacy code nobody is actively working on. They are not how you govern what an agent writes, so they sit inside the loop rather than in front of it.

See the rules engine

Questions

Continuous Analysis, answered

Why call it Continuous Analysis rather than continuous integration?

Because it is not about building the code, it is about continuously checking it against the standards your organisation decided on, from the moment an agent or an engineer starts writing through to the merge. The build is one step inside that.

What triggers the loop?

Every commit and every pull request. Webhooks from your source control and CI start the work, so analysis follows your code as it moves rather than waiting for a scheduled scan.

Where does the loop actually close?

At insight. Strategic Insights shows which standards are being breached, where, and by whom, and that is the input to the next revision in the Standards Center. A standard nobody can comply with is a standard that needs rewriting, and the loop is how you find out.

Can it block merges?

Yes. Three independent checks can hold a merge: compliance below your minimum score, the AI review not having run, and human sign-off not yet given. You choose which of them your organisation enforces.

See the loop running on your code

Book a demo and follow one change from your published standard all the way to a gated merge.

Book a Demo