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QuickCloud AI Platform

AI Built for App and Mainframe Modernization —
Not Borrowed from a Chatbot

Tenant-Isolated. Governance-First. Embedded in Every Product — Not an Add-On.

A proprietary AI Gateway, purpose-built code analysis and transformation, autonomous self-healing, and per-phase governance — built into the platform, not bolted on after the fact.
Your source code and infrastructure data never touch a third-party API directly.

The Problems No Human Can Fully Solve Alone

Legacy Java EE monoliths, aging .NET Framework services, and decade-old Python codebases have the same problem as COBOL: no documentation, minimal comments, and business logic scattered in ways that make confident refactoring nearly impossible. A senior developer can tell you what the code does — but not always what it means to the business, or how to safely decompose it into cloud-native services.

Cloud cost environments have a parallel problem: hundreds of accounts, thousands of resources, and spend patterns that no human can monitor continuously. The architecture decision that's costing you $40K/month extra isn't visible in a dashboard — it requires pattern recognition across your entire infrastructure graph.

QuickCloud AI reads the full picture — source code, infrastructure topology, migration state, and cost patterns — and surfaces what matters for your engineers and architects to act on. It's not replacing your team. It's giving them the understanding and automation they need to move fast without breaking things.

How the AI Gateway Works

Your Source Code & Infrastructure

Stays in your tenant

QuickCloud AI Gateway

Tenant-scoped proxy

Audit + governance layer

Anthropic Claude
OpenAI GPT
QuickCloud Inference

Your source code and infrastructure data are analyzed within the Gateway — raw inputs never reach provider APIs directly. Results return to your tenant environment.

Six AI Capabilities Running Across Every Product

Not a plugin. Not an add-on. These capabilities run automatically across all seven products — from cost governance to app replatforming to mainframe modernization.

Core Infrastructure

Proprietary AI Gateway

Your code never touches a third-party API directly.

  • Tenant-scoped proxy — each customer's requests are isolated at the network level
  • Zero customer API key exposure — QuickCloud manages all provider auth internally
  • Configurable at runtime — switch providers or models without code changes
  • All AI traffic logged by tenant, project, phase, and analysis type
Migration Analysis

AI Code & Logic Analysis

Understand what your legacy code actually means — before you touch it.

  • Analyzes Java, Python, .NET, COBOL, and RPG source — including nested dependencies and implicit data flows
  • Produces plain-English descriptions of business rules for architect and analyst review
  • Approval workflow — business team validates logic before migration proceeds
  • I/O contract mapping and data flow documentation generated automatically
Code Generation

Code Transformation Gateway

From legacy code to cloud-native — with test stubs.

  • Transforms COBOL, RPG, Java EE monoliths, and .NET Framework apps to cloud-native targets
  • Output targets: Java, Python, C#, Node.js, containerized microservices
  • Microservice boundary detection for legacy app decomposition
  • Unit test stub generation on every transformed component
Autonomous Operations

Self-Healing Agent

Autonomous per-phase healing — no human intervention required.

  • Monitors each migration phase for unhealthy state automatically
  • Detects: compilation failures, test regressions, schema errors, deployment failures
  • Applies targeted fix, retests, and continues — without waking a human at 2am
  • Every action emits a full audit record: what changed, why, and the result
Assessment

Code Quality & Anti-Pattern Detection

Quantify modernization opportunity before you commit to it.

  • Identifies dead code, duplicate logic, and unreachable branches across any codebase
  • Flags legacy anti-patterns: COBOL GO TO spaghetti, Java EE monolith coupling, Python 2.x incompatibilities
  • Each finding includes a modernization opportunity description and effort estimate
  • Prioritizes remediation by impact — so teams tackle the highest-value changes first
Enterprise Governance

Phase-Scoped AI Governance

Full visibility into what AI did, when, and at what cost.

  • Every AI call tracked by tenant, project, phase, and analysis type
  • Per-provider and per-model usage dashboards with cost breakdown
  • Model access governed by license tier — plan controls available models
  • Usage data available via API for FinOps and compliance integrations

Supported AI Models

Model access is governed by license tier — your plan determines which models are available to your team.

Claude SonnetAnthropic

Business rules extraction, complex legacy code analysis

Claude OpusAnthropic

Deep semantic analysis, edge case reasoning

Claude HaikuAnthropic

High-volume classification, fast phase tasks

GPT-4oOpenAI

Code generation, transformation, test stub creation

GPT-4 TurboOpenAI

Large-context codebase and infrastructure analysis

QuickCloud InferenceQuickCloud

Specialized fine-tuned tasks for migration workflows

6
Distinct AI capabilities built into migration
Zero
Third-party API keys required from customers
Multi-model
AI across 3 providers — Anthropic, OpenAI, QuickCloud
100%
AI actions auditable with phase-scoped logging

Where AI Runs Across All Seven Products

Every product in the QuickCloud platform has AI capabilities running automatically — not just Mainframe Modernization.

App Modernization (AI)Legacy app decomposition, microservice boundary detection, code transformation
Modernization, Security & Cost Intelligence (AI)Spend anomaly detection, architecture cost pattern analysis, governed action recommendations, policy gap detection, compliance evidence packs
Database Migration (AI)Schema analysis, cloud-optimized schema recommendations, cutover risk scoring
Mainframe Modernization (AI)COBOL/RPG/NATURAL analysis, business rules extraction, transpilation, dead code detection
QA Automation (AI)Test case generation, regression pattern detection, parallel-run diff analysis
Performance & Load Testing (AI)Baseline SLA calibration, anomaly detection, pre-cutover validation scoring
Identity & Access (IAM) Migration (AI)Access rule mapping, IAM policy generation, role hierarchy analysis
All productsAutonomous failure detection, targeted repair, and full audit trail

Frequently Asked Questions

No. The QuickCloud AI Gateway is a tenant-scoped proxy that sits between your environment and AI providers. Your source code and infrastructure data are routed through QuickCloud's infrastructure — they never touch OpenAI or Anthropic APIs directly. Customer API keys are never configured, stored, or exposed. This is the same data isolation model your legal and security teams require for any cloud SaaS tool.
QuickCloud supports the current Claude and GPT-4 model families from Anthropic and OpenAI, along with QuickCloud's own inference endpoints. Model selection is configurable at runtime and governed by license tier — the models available to your team are controlled by your plan.
The analyzer reads your legacy source — Java EE monoliths, .NET Framework services, Python codebases, COBOL programs, RPG, and more — and produces plain-English descriptions of the business rules and logic encoded in each component. Output appears in a dedicated UI tab and goes through an approval workflow before migration proceeds. This gives your architects and business analysts the ability to validate that migrated logic is correct without reading the original source.
The Self-Healing Agent monitors each migration phase for unhealthy state — compilation failures, test regressions, schema validation errors, deployment failures. When detected, it autonomously applies a targeted fix, retests, and emits an audit record describing what it changed and why. It works within defined phase boundaries and cannot make changes outside its scope. Every action is logged and reversible.
Every AI call is tracked by tenant, project, phase, and analysis type. Usage dashboards show per-provider and per-model breakdowns, so your FinOps team can see exactly what the AI layer costs, which phases consume the most, and how usage changes as the migration progresses. This data is available via API for integration into your existing cost governance tools.
No — and that's intentional. The Gateway manages all provider authentication internally so your team never needs to configure or rotate API keys. This eliminates a class of security risk (exposed keys in config files or CI pipelines) and simplifies onboarding. All AI spend is billed through your QuickCloud subscription.

See the AI Platform in Action

Schedule a walk-through and we'll run code analysis and complexity scoring against your actual environment — so you see AI output on your codebase before committing to anything.

Schedule Personalized Walk-throughSee Quick Product Video

No obligation · Your source stays private