Product Guide📅 January 2026⏱️ 12 min read✍️ Krishna Koravadi
GapLensAI: From Code to Compliance — A Complete Developer Workflow Guide
See how GapLensAI integrates into your existing development ecosystem — VS Code, CI/CD pipelines, ALM tools, and enterprise dashboards. Three real-world use cases with architecture diagrams.
Safety-critical software development demands rigorous documentation — but engineers shouldn't spend half their time writing documents that drift from code within weeks. GapLensAI bridges this gap by integrating directly into your existing toolchain, detecting documentation drift in real-time, and generating audit-ready work products with full traceability.
👤 Human-in-the-Loop by Design: GapLensAI generates drafts and detects gaps — but engineers always review, edit, and approve all work products. AI assists, humans decide. This is essential for safety-critical compliance.
This guide walks you through GapLensAI's architecture, integration points, and three core use cases that transform how teams handle compliance.
🏗️ System Architecture Overview
GapLensAI is designed as a modular, integration-first platform. Whether you're a solo developer using VS Code, a DevOps team automating CI/CD compliance gates, or an enterprise managing multi-project dashboards — GapLensAI fits your workflow without disruption.
GapLensAI System Architecture
Integration touchpoints across the development lifecycle
Key Integration Points
💻
VS Code Extension
Real-time gap alerts
🔌
MCP Server
Copilot/Claude integration
🐳
Docker Container
CI/CD & Enterprise
⌨️
CLI Tool
Scripting & Automation
📚 Use Case 1: Legacy Codebase Processing
📦
Bulk Documentation Generation for Existing Code
Safety Engineer • Technical Lead • Quality Manager
ISO/PAS 8926:2024 introduces formal requirements for qualifying pre-existing software elements (PSAE) in safety-critical systems. Whether it's supplier code, acquired codebases, or legacy systems accumulated over decades — you need comprehensive work products with traceability to satisfy auditors.
The Challenge: A typical automotive ECU may contain 500K-2M lines of code, much of it inherited. Manual documentation effort? 6-24 months and $500K-$2M per major component.
Workflow
1
Configure
Point to repo, select standards (ASPICE, ISO 26262)
Documentation drift happens one commit at a time. A developer adds a parameter, modifies an interface, refactors a function — and the SDD becomes stale. GapLensAI catches these gaps in real-time, generates suggested updates, and notifies engineers who then review and decide what action to take.
Developer Flow (VS Code)
1
Code
Developer modifies function signature
2
Detect
GapLensAI flags documentation gap
3
Suggest
Generates draft SDD/SAD/SRS updates
4
👤 Review
Engineer reviews diff, edits if needed
5
👤 Approve
Engineer approves & commits to ALM
CI/CD Pipeline Integration
1
Commit
Developer pushes code
2
Analyze
GapLensAI detects drift from docs
3
Report
Generate gap report & notify team
4
👤 Decide
Engineer reviews gaps, decides action
5
👤 Resolve
Update docs or waive with justification
Gap ReportEngineer NotificationDecision LogAudit Trail
CI/CD Pipeline Integration
Continuous compliance monitoring with every commit
📊 Use Case 3: Project Health Dashboard
📈
Enterprise Compliance Visibility
Quality Manager • Safety Manager • Program Manager
Leadership needs visibility across all projects without diving into code. The GapLensAI dashboard aggregates compliance health, documentation coverage, drift trends, and audit readiness — highlighting where engineer attention and decisions are needed.
Multi-project compliance visibility for enterprise teams
🔌 Bring Your Own LLM (BYOL)
🧠 Flexible LLM Provider Support
GapLensAI supports flexible LLM providers — use your existing AI subscriptions or run fully on-premise. No double-paying for AI capabilities you already have.
OpenAI
GPT-4o, GPT-4
Anthropic
Claude 3.5/4
Azure OpenAI
Enterprise compliance
AWS Bedrock
Claude, Titan
Google Gemini
Gemini Pro/Ultra
Ollama
Local / Air-gapped
LMStudio
Desktop LLMs
vLLM
Self-hosted inference
Already using GitHub Copilot? Use those same credentials with GapLensAI — pay for compliance intelligence, not redundant LLM access.
🚀 Deployment Options
☁️
Cloud SaaS
Fastest setup, auto-updates, Anthropic/OpenAI included
🐳
Docker On-Premise
Air-gapped, local LLMs, full data control
🏢
Enterprise Hybrid
Dashboard in cloud, analysis on-prem
Air-Gapped Environments: Defense, aerospace, and OEMs with strict data policies can run GapLensAI entirely on-premise using Ollama or vLLM. Your code never leaves your network.
Ready to Close the Gap?
See GapLensAI analyze your codebase in a live demo. We'll show you exactly how it integrates with your existing tools.
GapLensAI transforms compliance from a documentation burden into a continuous, integrated part of your development workflow:
Legacy Code (ISO/PAS 8926): Generate draft work products from existing codebases — engineers review components, validate documentation, and approve before export. Weeks instead of months.
Daily Development: Catch documentation drift in real-time with VS Code integration and CI/CD pipeline alerts. Engineers review gap reports and decide what action to take — update docs or waive with justification.
Project Dashboard: Give leadership visibility across all projects. Track compliance trends, audit readiness, and outstanding gaps requiring engineer attention.
All powered by your choice of LLM — cloud or on-premise — with full traceability that auditors trust. AI generates, humans approve.