The AlgorithmWe deploy teams that build compliance infrastructure engineering into your system's DNA — not as an audit layer bolted on after the fact. HIPAA, GDPR, UAE PDPL, UK DPA, SOC 2, FedRAMP — native from day one.
Talk to an Engineer →Applicable obligations become identity, data, workflow, delivery, and evidence controls that teams can test and operate.
Privacy, access, audit, interoperability, and continuity are implemented around actual system roles.
Explore context →Decision evidence, segregation, resilience, and customer-data protection become runtime behavior.
Explore context →Federal, free-zone, and licensed-activity scope must be established before implementation.
Explore context →Privacy, national cybersecurity, critical-system, and sector scope are mapped separately.
Explore context →Compliance infrastructure is the commercial delivery path for organizations that have an established control or authorization scope but cannot operate it reliably through software delivery and runtime change. We engineer enforcement, monitoring, evidence, exception, and remediation paths; accountable authorities and assessors retain applicability and authorization decisions.
Maintain assets, components, identities, data flows, providers, inherited controls, owners, and versions as an operational source for monitoring and change impact.
Translate confirmed requirements into preventive and detective checks across infrastructure as code, CI/CD, identity, configuration, application behavior, and operations. Preserve approved exceptions with expiry.
Normalize asset, vulnerability, configuration, logging, change, incident, and test evidence with source and time context. Automate repeatable collection while retaining owner review and attestation where required.
Deduplicate findings, relate them to affected controls and assets, prioritize by actual exposure, track risk decisions and corrective work, and verify closure. Integrate POA&M records when the governing process requires them.
Connect boundary inventory, scanning, configuration, change, incident, and evidence sources to the organization’s established continuous-monitoring process.
Human accountability. Agency, authorizing, assessment, security, and control owners retain their defined roles.
Engineering constraints. Baseline, agency requirements, inherited controls, evidence formats, cadence, findings, POA&M, and system change.
Compare deployed state with approved technical baselines and route or execute bounded remediation.
Human accountability. System and control owners approve risk treatment and material change.
Engineering constraints. Emergency changes, false positives, provider state, destructive correction, exceptions, and rollback.
Collect control-operation artifacts continuously and assemble reviewer-ready evidence by scope and period.
Human accountability. Control owners attest operation; assessors determine sufficiency.
Engineering constraints. Provenance, completeness, integrity, retention, access, sensitive content, and manual controls.
Identify systems, data, environments, providers, inherited services, exclusions, and boundary-changing events.
Connect each control to owners, frequency, scanners, telemetry, tickets, code, logs, and approvals.
Link deployments, vulnerabilities, exceptions, and POA&M milestones to review and closure evidence.
Compare declared, deployed, and runtime state while distinguishing failure from accepted variance.
Correct only tested, reversible conditions with policy gates, validation, rollback, and escalation.
Measure collection coverage, freshness, failed controls, overdue actions, scanner health, and boundary changes.
Signal. New assets or services operate without the expected scanning, logging, ownership, or evidence.
Architecture response. Discover from authoritative deployment and provider sources, block or quarantine unowned assets, and reconcile inventory continuously.
Signal. Duplicate and context-free alerts overwhelm owners while exploitable paths remain open.
Architecture response. Normalize, deduplicate, enrich with asset and control context, prioritize by reachability and consequence, and retain risk decisions.
Signal. An automated baseline correction causes outage, data loss, or loss of forensic evidence.
Architecture response. Classify safe actions, simulate where possible, require approval for consequence, preserve state, stage change, and rehearse rollback.
Signal. Evidence can be altered, is incomplete, or is broadly accessible.
Architecture response. Protect source identity, transfer, integrity, access, retention, timestamps, and processing lineage; monitor the evidence system itself.
It is tooling that supports ongoing visibility into an authorized cloud system’s assets, vulnerabilities, configuration, controls, changes, incidents, and evidence. Software can automate collection and workflow, but it does not replace required roles, assessment, agency review, or authorization decisions.
The exact sources depend on the boundary and agency process, commonly including asset inventory, vulnerability scanning, configuration, identity, logging, changes, incidents, control tests, findings, remediation and POA&M records, plus the evidence and reporting workflow.
Some bounded, reversible, well-tested corrections can. Material, destructive, stateful, safety-sensitive, or exception-dependent changes should require approval. Every automated runbook needs eligibility, evidence preservation, rollback, and escalation.
No. It improves control implementation, continuous monitoring, evidence, and remediation inside an agreed scope. The relevant agency, authorizing officials, assessors, auditors, and organizational owners make authorization or assurance determinations.
How public outcome claims are reviewed before publication.
Explore this resource →Guide to control, evidence, and remediation architecture.
Explore this resource →Informational context for the framework and boundary.
Explore this resource →Cloud foundations inside established requirements.
Explore this resource →Our compliance infrastructure engineering teams map your regulatory landscape before writing a single line of code. ALICE enforces DevSecOps compliance at every commit — making it mechanically impossible to ship non-compliant code. Automated audit trail generation happens as a byproduct of the build, not assembled afterward.
A structured framework — with scoring — for deciding whether to build in-house, outsource, or adopt a hybrid model. Adapted for regulated industries where the cost of the wrong decision is highest.
Our engineers understand your regulatory domain before they write their first line of code. Compliance infrastructure engineering built at the architecture level — not retrofitted after the fact.
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