Full-Stack PlatformsSTATUS: Working Prototype 0 0

B2B Audit Engine

TypeScript compliance reporting platform

A TypeScript web application that evaluates operational client data against compliance rule frameworks, generating audit reports and risk metrics for business consultants.

Inspect GitHub Source Code

01 // THE BUSINESS PROBLEM & SITUATION

Operational Context

Consultants were manually reviewing operational data in spreadsheets, taking weeks to compile standardized audit reports.

CLIENT / ENVIRONMENT: Designed as an internal tool for consulting firms to scale audit throughput.

02 // SYSTEM ARCHITECTURE & SOLUTION

What Was Built

Built a full-stack Next.js web application with a relational PostgreSQL database to process operational data and generate compliance reports.

business-audit-tool-ai.sysFull-Stack Platforms

VERIFIED ARCHITECTUREB2B Audit Engine

SYSTEMS_ARCHITECTURE_EXPLODER // LAYERED_STACKFULL-STACK SYSTEM DECOUPLING

Frontend Layer

Next.js 16 App Router, React 19, Tailwind CSS, TypeScript

API & Middleware

FastAPI, Pydantic Schema Validation, Rate Limiters

Orchestration

LangGraph Multi-Agent Supervisor & State Machines

Model Providers

OpenAI GPT-4o, Anthropic Claude 3.5, Vision AI

Data Stores

PostgreSQL (Prisma), Qdrant Vector Store, Redis Caching

Observability

LangSmith traces, Pydantic audit logs, Error retries

03 // ENGINEERING CONTRIBUTION & FEATURES

Exact Contribution

Designed relational schema using Prisma ORM
Built interactive Next.js dashboard
Implemented automated PDF report export

Key Capabilities Built

✓ Customizable Audit Frameworks

✓ Automated Compliance Risk Flagging

✓ Dynamic Report Generation

✓ Secure Data Entry Forms

DATA_PROVENANCE_TIMELINE // AUDIT_TRACETRACE_ID: #TR-992041

14:22:01.002Source Ingestion

Received webhook from lead submission formOK

14:22:01.045Schema Sanitization

Pydantic validated 12 extracted fieldsOK

14:22:01.210LangGraph Reasoning

Score intent = 0.94 (Tier A Lead)OK

14:22:01.350Human Audit Check

Confidence threshold passed (>0.85)PASSED

14:22:01.480CRM Commit

Created contact ID #884920 in PostgreSQLCOMMITTED

04 // EXECUTION PIPELINE

Step-by-Step Workflow

STEP 01Consultant inputs client operational metrics.

STEP 02Engine evaluates data against rule sets.

STEP 03Dashboard highlights flagged compliance risks.

STEP 04Finalized report is exported.

05 // ENGINEERING LESSONS & OUTCOMES

Technical Challenges Overcome

• Managing complex nested relational data structures in Prisma.
• Ensuring fast server-side rendering for audit dashboards.

Measurable Outcomes

→ Reduced audit compilation turnaround time significantly.

→ Standardized compliance metric evaluation across audit teams.

Lessons & Engineering Rules

"Strongly typed ORMs like Prisma are essential for preserving data integrity in complex audit applications."

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PROJECT METADATA

ARSLAN'S ROLEFull-Stack Architect

YEAR & STATUS2025 // Working Prototype

CATEGORYFull-Stack Platforms

TECHNOLOGY STACK

TypeScriptNext.jsPrismaPostgreSQLTailwind CSS

GITHUB METRICS

Stars: 0

Forks: 0

Verified GitHub Update: 8/2/2026

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