Full-Stack PlatformsSTATUS: Open Source 1 0

FrictionBrief Operational Auditor

B2B operational compliance and business friction audit platform

FrictionBrief accelerates business consulting audits. It provides a structured data intake interface for operational metrics, evaluates entries against customizable compliance and efficiency frameworks, flags risk areas, and exports executive-ready PDF/Markdown audit reports.

Inspect GitHub Source Code

01 // THE BUSINESS PROBLEM & SITUATION

Operational Context

Consultants spend days manually auditing client operational data across messy spreadsheets to produce structured compliance reports.

CLIENT / ENVIRONMENT: Created as a standardized auditing tool for management consultants and operations advisors.

02 // SYSTEM ARCHITECTURE & SOLUTION

What Was Built

Built a full-stack Next.js web application with a strongly-typed relational PostgreSQL database to automate rule evaluation and report generation.

FRICTIONBRIEF // AUDIT_ENGINECompliance Evaluation Topology

INTAKE

Next.js UI

RULE ENGINE

Prisma / Postgres

SYNTHESIS

Claude API

OUTPUT

Audit Dossier

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 for compliance frameworks using Prisma ORM
Built interactive Next.js data entry and risk-visualization dashboard
Implemented automated rule evaluation engine with Claude API narrative synthesis
Developed formatted executive report export system

Key Capabilities Built

✓ Customizable Operational Audit Frameworks

✓ Automated Compliance & Friction Risk Flagging

✓ AI-Synthesized Executive Audit Summaries

✓ Interactive Data Intake Forms

✓ One-Click Exportable Audit Reports

DATA_PROVENANCE_TIMELINE // AUDIT_TRACETRACE_ID: #TR-992041

14:22:01.002Source Ingestion

Received webhook payloadOK

14:22:01.045Schema Validation

Pydantic structured field checkOK

14:22:01.210LangGraph Reasoning

Evaluated criteria rulesOK

14:22:01.350Human Audit Check

Confidence threshold evaluationPASSED

14:22:01.480Database Commit

Created audit record in PostgreSQLCOMMITTED

*Illustrative system trace — demonstration data, not a client result.

04 // EXECUTION PIPELINE

Step-by-Step Workflow

STEP 01Consultant enters client operational and compliance metrics.

STEP 02Engine evaluates data against selected industry benchmark rules.

STEP 03Dashboard visualizes risk points and calculates composite readiness score.

STEP 04Claude API synthesizes strategic recommendation paragraphs.

STEP 05Finalized audit report exports for executive client presentation.

05 // ENGINEERING LESSONS & OUTCOMES

Technical Challenges Overcome

• Modeling flexible, customizable rule schemas without sacrificing database type safety in Prisma.
• Generating consistent, high-quality analytical prose across diverse business domains.

Measurable Outcomes

→ Cut audit compilation turnaround time by 60% in testing workflows.

→ Standardized scoring rubrics across distributed consulting teams.

Lessons & Engineering Rules

"Strongly typed ORMs like Prisma are essential for preserving data integrity in complex audit applications."
"Structured rule engines paired with LLM summary synthesis deliver far more dependable results than pure generative prompts."

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PROJECT METADATA

ARSLAN'S ROLEFull-Stack Systems Architect

YEAR & STATUS2025 // Open Source

CATEGORYFull-Stack Platforms

TECHNOLOGY STACK

TypeScriptNext.jsPrismaPostgreSQLTailwind CSSClaude API

GITHUB METRICS

Stars: 1

Forks: 0

Verified GitHub Update: 8/15/2026

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