Our Products

Compliance HyperVisor

The Compliance Hypervisor is our state of the art audit enhancing software. Comprised of two separate guis, our Proof Artifact Engine and our Quadrant Core Mapping Program. The Compliance Hypervisor is not a CRUD compliance app; it is a unifying audit platform that checks compliance, cryptographic tamper evidently records the entire build process, computes the structure of your system and uses that structure to generate independently verifiable audit proof. It builds a typed graph of files, classes, methods, endpoints, IAM resources, data flows, control flows, and external relationships, then ties approvals, access decisions, and other governed events to a Merkle-backed evidence ledger with replayable verification steps. That gives auditors what they actually want when time matters: deterministic evidence packs, verifiable timestamps, historical authorization proof, transparent sampling, and a clean path from control requirement to the exact technical surface it depends on. Instead of spending weeks rediscovering the same environment by hand, reviewers can move much faster because the proof is already structured for verification.

Galvanize Systems’ Compliance Hypervisor is built on a deterministic analysis and verification pipeline designed to produce audit artifacts that are reproducible, cryptographically verifiable, and independently reviewable. At its core, the platform converts software systems and governance events into a structured mathematical model, allowing security and compliance properties to be evaluated using formal constraint solving technology such as Z3. The entire analysis runs inside a controlled, hermetic execution environment so results are deterministic and reproducible across runs, ensuring that evidence can be regenerated and validated at any time. Each artifact generated during analysis is chained into a tamper-evident Merkle evidence structure—similar in principle to the integrity models used in systems like Git—providing a cryptographically anchored record of repository state, verification steps, and compliance decisions. The result is a portable proof bundle that auditors and reviewers can replay independently, allowing them to verify system behavior, historical authorization states, and control enforcement without requiring direct access to internal infrastructure. By combining deterministic execution, formal verification, and cryptographic evidence chains, the Compliance Hypervisor transforms traditional narrative-based audits into a process grounded in transparent, mathematically verifiable proof.

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Proof Artifact engine

The Proof Artifact Engine functions as a singular, unifying force for the evidence process across every operational layer. This sophisticated system integrates multiple specialized components, beginning with a deterministic assurance engine designed for software producers who must provide indisputable evidence of repository contents, exhaustive check histories, and the precise evolution of changes over time. Complementing this is our powerful proof compiler that transforms standard repositories or build artifacts into verifiable forensic proof packages, specifically engineered to satisfy the rigorous demands of security, compliance, quality assurance, and architectural review.

Rather than relying on the common industry standard of best guess heuristics or simple regex patterns, our methodology utilizes advanced Z3 SMT mathematical modeling. This approach first mathematically proves the existence of an error, subsequently determines its exact impact on your specific compliance posture, and finally generates a mathematically modeled solution for your engineering teams to implement with total confidence. Don’t just see what’s broken, see how it breaks compliance, and get the fix all in one place.

The output of this process is a comprehensive suite of high-fidelity artifacts, including a typed evidence graph, a signed proof bundle, and a formal audit evidence binder. The engine also maintains baseline and delta proofs to track integrity over time, alongside policy-gated decisions and integrated waiver governance. Every component is packaged to allow an external party to conduct a thorough review without ever requiring access to your internal environment. By moving away from the traditional reliance on manual screenshots, static PDFs, and verbal promises, you instead deliver definitive proof characterized by explicit assurance levels, least-disclosure packaging, and a transparent verification path. This fundamental shift moves audits, due diligence, and customer reviews away from the era of narrative reconstruction and into the era of direct, mathematical verification.

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Quadrant Core: Mapping Platform

Quadrant Core: Mapping Platform (Standard) is a multi-language analysis engine that turns Python, JavaScript/TypeScript, and Java codebases into a single, navigable map of services, functions, data paths, and dependencies. It systematically traces how information and requests interact and move through your code, databases, APIs, events, and policies so you can see, in plain terms, what calls what, what depends on what, and where risky flows actually run. Standard integration plugs into your existing pipelines to power high-value workflows—change impact analysis, vulnerability tracing, and architecture mapping—without stitching together a pile of separate scanners.

The Quadrant Core: Mapping Platform comes attached to every Galvanize System product; we’re not just interested in making code, we know the importance of maintenance as well. So it comes as no surprise our 3d Code Constellation Viewer adds an entirely new dimension. We map and project the architecture and data paths of your systems into a structured virtual workspace, so groups of engineers can walk together through real call paths, dependencies, and failure points as if they were standing inside the incident diagram instead of staring at a flat wall of tabs. Here we bridge the gap between code and reality allowing users to see with their own eyes the interconnections of their platforms. Designed with professionals in mind, it supports different learning styles—text-first, visual, kinesthetic, and spatial—so teams can grasp how the system actually behaves and agree on a fix faster, turning complex outages and refactors into focused, collaborative repair sessions instead of guesswork. Turn a 2D code into a 3D mapped reality.