How ALICE Works End-to-End: Autonomous Application Lifecycle Management Explained

How ALICE Works End-to-End: Autonomous Application Lifecycle Management Explained

Your application estate does not manage itself. Until now.

For most enterprise IT teams, application lifecycle management is a series of manual handoffs between disconnected processes: someone discovers what is installed, someone else decides what to keep, a team packages it, another team tests it, operations deploys it, and nobody monitors whether it drifts back to the previous state next week.

Each handoff creates delay. Each delay creates risk. And the whole thing starts again the next time a vendor releases a new version.

ALICE (Application Lifecycle Intelligence and Compliance Engine) was built to automate this entire workflow from the moment an application is discovered in your Intune environment to the moment it is retired, updated, or replaced. This is what Autonomous Application Lifecycle Management looks like in practice.

What Is Autonomous Application Lifecycle Management?

Autonomous Application Lifecycle Management (AALM) is the practice of using an intelligent platform to govern every stage of an application’s life within an enterprise estate automatically, continuously, and without manual handoffs between teams.

It is distinct from traditional ALM in one critical way: the lifecycle runs itself.

Discovery, rationalisation, packaging, testing, deployment, governance, updating, and retirement are connected into a single governed workflow. When a new version of an application is released, the system detects it, repackages it, routes it through testing, stages the rollout, and monitors the result without a human initiating each step.

ALICE is the platform that delivers this. Built on Microsoft Intune, it does not replace your existing infrastructure. It makes it intelligent.

Stage 1: Discovery and Normalisation

ALICE begins by connecting to your Microsoft Intune environment via Graph API and pulling your full detected application inventory.

What it finds is rarely clean. Raw application data from enterprise estates is notoriously messy: multiple versions of the same software across business units, inconsistent naming between installer sources, and redundant entries that inflate the apparent complexity of the estate.

ALICE normalises this raw inventory into application families one managed row per application family, with all versions and device counts rolled up beneath it. You see what you actually have, not what the installer log says you have.

The result: complete estate clarity, typically within hours of connection.

Stage 2: Rationalisation

With the estate visible and normalised, ALICE moves to rationalisation identifying what you actually need to manage.

ALICE matches discovered applications against a curated in-house database using multi-pass fuzzy matching: exact match, then normalised, then partial, then token-based. This resolves naming inconsistencies across installations and versions.

Matched applications inherit structured metadata: category classifications and flags such as system component, driver, runtime, deprecated, bundle, or non-business. This metadata drives the rationalisation engine.

Non-actionable software is filtered out, applications are grouped into functional families, and duplicate or overlapping tools are surfaced automatically. Your estate view focuses on the software that actually requires active management.

For most enterprise estates, this reveals a 60–70% reduction opportunity applications that are duplicates, redundant, or candidates for retirement.

Stage 3: Governance

Once your estate is rationalised, ALICE governs it.

Governance means assigning ownership, lifecycle status, and version exclusions at the application family level. Every application knows who is responsible for it, where it sits in its lifecycle, and which versions are approved for deployment.

This creates the foundation for audit-ready reporting. At any point, you can evidence what is approved, what is current, and what has been reviewed continuously, without a project to compile it.

For regulated organisations in finance, defence, or local government, this is the difference between scrambling for compliance evidence and having it available on demand.

Stage 4: Automated Packaging

ALICE automates the packaging pipeline one of the most time-consuming manual processes in enterprise IT.

When an application requires packaging, ALICE matches it to the catalogue to pull installer metadata and silent install inputs. It generates packages automatically, extracts MSI property tables, and exposes configuration in the UI including enterprise deployment standards without requiring manual MSI editing.

Custom MSI or EXE uploads are supported: ALICE analyses the installer, applies the same automated pipeline, compiles to .intunewin, and uploads to Intune as a Win32 LOB app with required configuration.

For teams previously spending days per application on manual packaging, this represents an ~85% reduction in packaging time.

Stage 5: Testing and Approval Gating

No application progresses to production without passing through ALICE’s testing gate.

ALICE deploys each new package to a designated test group. Named testers approve or reject with full tracking. The application cannot progress to production until all assigned testers have approved it.

This is a hard gate not optional. Every change, whether a new application or a version update, follows the same governed path. The result is a controlled, audit-traceable release process that satisfies both operational and compliance requirements.

Stage 6: Phased Deployment

Once approved, ALICE stages production rollout in three phases: 10% → 50% → 100%.

ALICE creates AAD security groups for each phase and supports version exclusion groups so teams that need to remain on a specific version for operational reasons can be protected without breaking the broader rollout.

A background scheduler monitors deployment success at each threshold and can automatically progress phases based on tenant-configurable intervals. This is not faster deployment for its own sake. It is deployment with built-in risk control.

Stage 7: Auto-Update as Compounding Value

The most powerful aspect of the ALICE lifecycle model is what happens after the first deployment.

ALICE monitors sources for new versions of every application in your estate. When a new version is detected and the per-application auto-update toggle is enabled, the entire governance and deployment workflow re-runs automatically, without manual initiation.

The new version is repackaged. It routes through the same test group. It receives the same approval gate. It deploys through the same phased rollout. Your existing governance configuration, test group assignments, and exclusion groups are reused.

Over time, your application estate becomes self-maintaining. Versions stay current. Vulnerabilities are addressed before they accumulate. Manual patch-cycle effort reduces by ~40% compared to estates managed without automation.

Multi-Tenant Architecture

ALICE is built for complex enterprise environments, including post-merger and multi-division organisations.

Each tenant operates in isolation separate tenant database, per-tenant Azure AD app registration whilst sharing the ALICE governance framework. Consistent lifecycle standards across all entities, with the operational separation required by data and compliance boundaries.

All packaged applications are stored in customer-owned Azure Blob Storage. You retain ownership and control of every packaged asset.

The ALICE Lifecycle at a Glance

See ALICE in Your Environment

The only way to understand what ALICE finds in your estate is to connect it and see.

We offer a 14-day trial full access, connected to your Intune environment, showing your actual application estate mapped and normalised within hours.

Or, if you would prefer a guided 30-minute session first, book a demo and we will walk through your estate with you.

ALICE is built by Camwood, with 25 years of application lifecycle management expertise embedded in every recommendation.

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