# Emunshi

**Source:** https://www.startuphub.ai/startups/emunshi
**Profile type:** Startup

> AI-powered legal assistant for Indian advocates, automating drafting, case management, and legal research.

## About

Emunshi is an AI Munshi designed for every Indian advocate. It automates a wide range of tasks including drafting legal documents, managing case files, performing gap analysis, maintaining court diaries, and monitoring cause lists. The platform also verifies citations on Indian Kanoon and supports the latest BNS/BNSS 2023 legislation.

## Key facts

- **Slug:** emunshi
- **Website:** https://emunshi.ai
- **Location:** Bengaluru, India
- **Founded:** 2026-05-14
- **Operating status:** Active
- **Total funding:** $1M
- **Sectors / tags:** LegalTech, AI Copilot, AI Coding Assistant, Foundation Model, Large Language Model, Retrieval Augmented Generation, Generative AI, Workflow Automation, API Platform

## Frequently asked

### What does Emunshi do?

Emunshi is an AI Munshi designed for every Indian advocate. It automates a wide range of tasks including drafting legal documents, managing case files, performing gap analysis, maintaining court diaries, and monitoring cause lists. The platform also verifies citations on Indian Kanoon and supports the latest BNS/BNSS 2023 legislation.

### What is Emunshi's revenue?

StartupHub estimates Emunshi's annual revenue at $326K (range $279K to $757K, 27% confidence), based on comparable companies in the sector.

### What is Emunshi's valuation?

StartupHub estimates Emunshi's effective valuation at $3.8M (range $2.5M to $6.0M, 11% confidence), based on comparable companies in the sector.

### How much funding has Emunshi raised?

Emunshi has raised a total of $1M in funding. The most recent round on record is Seed.

### Where is Emunshi headquartered?

Emunshi is headquartered in Bengaluru, India.

### When was Emunshi founded?

Emunshi was founded in 2026.

### What industry does Emunshi operate in?

Emunshi operates in LegalTech, AI Copilot, AI Coding Assistant, Foundation Model, Large Language Model, Retrieval Augmented Generation.

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