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Varun Cumbamangalam.

Senior IoT and Edge AI Engineer, AI Product Manager at OraLens Healthcare

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// Provider policy: residency-safe by default export function resolveAiProvider(env: ProviderEnv) { if (env.AZURE_OPENAI_RESOURCE && env.AZURE_OPENAI_KEY) { return createAzureProvider({ region: "centralindia" }); } if (env.ANTHROPIC_API_KEY && env.AI_ALLOW_NON_INDIA_FALLBACK) { return createExplicitFallbackProvider(); } throw new Error("No policy-compliant AI provider configured"); }
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VakeelOS - Legal Practice Operating System logoVakeelOS - Legal Practice Operating System logo
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VakeelOS - Legal Practice Operating System

Legal practice software for Indian advocates, with court workflows and AI-assisted drafting.

Explore interactive demoVakeelOS website
India-first

Workflow & Residency

On-device

Document OCR

Modular

Domain Architecture

Tech Stack

Next.jsTypeScripttRPCPrismaPostgreSQL + pgvectorAzure OpenAIAzure Container AppsClerkRazorpay

The problem

Solo advocates and small Indian law firms still coordinate matters across paper causelists, messaging apps, spreadsheets, and disconnected document folders. Generic practice-management software misses court-specific workflows; generic AI adds a second risk by producing confident text without a reliable link back to the advocate's own case material.

The challenge

The product had to unify daily legal operations without flattening the way Indian advocates actually work. That meant CNR-linked matters, hearings, causelists, drafting, documents, fee collection, and phone-first access - while keeping primary data in Azure Central India and making non-India AI fallbacks an explicit opt-in. The interface and the underlying service boundaries needed to tell the same story: a dense professional system that still feels legible on first use.

Architecture & System Design

Full system schematic available upon request

VakeelOS is a Next.js and TypeScript application organised around thin route adapters and domain modules. tRPC exposes typed application boundaries; Prisma and PostgreSQL with pgvector store operational and retrieval data; Azure Blob Storage handles documents; Inngest runs background jobs; and Redis supports cache and coordination paths. Azure OpenAI is the primary AI provider, while browser-side PaddleOCR keeps initial document extraction on-device. Production runs on Azure Container Apps with Key Vault, Log Analytics, Sentry, and fail-closed release checks.

Code Walkthrough

Non-proprietary extract demonstrating the core integration pattern.

typescript
// Provider policy: residency-safe by default
export function resolveAiProvider(env: ProviderEnv) {
  if (env.AZURE_OPENAI_RESOURCE && env.AZURE_OPENAI_KEY) {
    return createAzureProvider({ region: "centralindia" });
  }

  if (env.ANTHROPIC_API_KEY && env.AI_ALLOW_NON_INDIA_FALLBACK) {
    return createExplicitFallbackProvider();
  }

  throw new Error("No policy-compliant AI provider configured");
}

Results

The platform now has a production deployment path on Azure Container Apps, a modular route-and-service architecture, on-device OCR, grounded document retrieval, and explicit residency controls around AI providers. The same court-native design language carries through the product dashboard, mobile flows, brand identity, and responsive marketing site, so prospective users can understand the product before signing in.

Explore the product system

This case study covers the main product surfaces. Use the buttons to move between the dashboard, app, website, and brand work.

Open Product dashboard

Product surfaces

VakeelOS website
Product dashboard

Explore matters, hearings, documents, drafting, and practice operations.

Live Demos

VakeelOS website

https://vakeelos.com

VarVik Technologies Private LimitedVarVik Technologies Private Limited

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Interested in this work?

I can walk through the architecture and code during an interview.

Get in Touch All Projects