Strengthening Judicial Capacity through Real-Time Transcription and Workflow Automation
Case at a Glance
Impact
45-60
minutes reduced to under 10 minutes for order writing using AI-enabled documentation
2–3×
increase in witnesses examined per day, shortening hearing timelines
30-50%
faster case disposal reported in matters using AI-generated documentation
About the organisation
Adalat AI is a non-profit justice-tech organisation building an end-to-end AI platform for courts in India and the Global South. Working directly with High Courts and District Courts, Adalat AI modernises core courtroom workflows (transcription, documentation, case-flow management, and evidence handling) to make justice delivery more timely, efficient, and accessible.
Problem Statement
India’s judiciary faces over 50 million pending cases, with an average case taking nearly 13 years to conclude. Despite sustained effort by judges and court staff, manual documentation processes and chronic shortages of stenographers create severe bottlenecks. Courts spend disproportionate time on routine tasks such as dictation, order writing, and evidence summarisation, limiting judicial capacity for adjudication.
Solution
Adalat AI built an AI-powered courtroom operating system that enables real-time transcription, automated documentation, and streamlined case-flow management within courtrooms. Optimised for Indian legal language and multilingual proceedings, the platform reduces manual workload for judges and court staff, accelerates hearings, and strengthens the efficiency of justice delivery.
Quick Facts
Organisation Name
Adalat AI
Organisation Website
Visit Site
Founding Year
2024
Number of Beneficiaries served
4,000+ courtrooms across 9 states
Geography Served
Andhra Pradesh, Delhi, Karnataka, Odisha, Bihar, Madhya Pradesh, Haryana, Kerela, Punjab
Focus Area
Operational Efficiency Programmatic Impact
Functions Impacted
Program Delivery / Beneficiary Services Technology & Data Management Others (Judicial Administration)
SDG Addressed
Full Case Study
Challenge
Manual documentation and workflow bottlenecks constrained judicial capacity
India’s courts operate under extreme case loads, with over 50 million pending cases nationwide. A critical constraint is manual documentation particularly live transcription and order drafting which relies heavily on a limited pool of stenographers.
Key challenges included:
- Severe stenography shortages causing delays in evidence recording and hearings
- Judges spending significant time on routine documentation rather than adjudication
- Limited ability to conduct multilingual proceedings efficiently
- Fragmented case records, making evidence tracking and retrieval cumbersome
- Inconsistent documentation quality across courts and states
- These constraints slowed hearings, extended case timelines, and disproportionately impacted litigants from low-income and marginalised communities.
Solution
An AI-powered courtroom operating system embedded into judicial workflows
Adalat AI built a comprehensive courtroom Operating System anchored around live, high-accuracy speech-to-text transcription optimised for Indian accents, dialects, and legal vocabulary. The platform integrates natural language processing and custom legal large language models to automate core courtroom workflows.
Key features of the solution include:
- Live courtroom transcription with speaker attribution and timestamps
- Multilingual translation between English and major Indian languages
- AI-generated orders, judgments, evidence summaries, and case notes
- Case-flow management dashboards for judges and court staff
- Searchable transcript and evidence repositories
- Secure on-premise or sovereign cloud deployment meeting judicial data standards
- Low-resource optimisation for courts with minimal hardware infrastructure
Outcomes & Impact
Accelerating hearings and strengthening justice delivery
- Policy-level validation: Kerala mandated Adalat AI for evidence recording; the first statewide AI mandate in courts globally
- Faster documentation: Order-writing time reduced from 45–60 minutes to under 10 minutes
- Improved hearing throughput: Courts are able to examine 2–3× more witnesses per day
- Faster case disposal: Judges reported 30–50% quicker disposal in cases using AI-generated documentation
- Reduced bottlenecks: Significant reduction in reliance on stenographers, addressing a long-standing systemic constraint
Technology Stack
| Name of the Tool | Where it was used | What it enabled | Category |
|---|---|---|---|
| Automatic Speech Recognition (ASR) | Live hearings | Real-time transcription of legal proceedings | Custom-built |
| Natural Language Processing (NLP) | Documentation workflows | Summarisation, entity tagging, and exhibit mapping | Custom-built |
| Custom Legal LLMs | Orders and judgments | Drafting and automation using privacy-preserving legal models | Custom-built |
| Machine Translation Models | Multilingual courts | Translation across major Indian languages | Custom-built |
| Secure Web Platform | Courtrooms | Role-based access to transcripts and dashboards | Custom-built |
| Azure Cloud & On-Prem Deployment | Judicial infrastructure | Secure, scalable hosting compliant with data standards | Commercial |
Key Project Learnings
- Automation Unlocks Judicial Capacity: Reducing time spent on routine documentation enabled judges to focus more on adjudication, accelerating hearings and case disposal.
- Embedding AI into Core Workflows Drives Adoption: Deploying AI directly inside courtrooms, rather than as a peripheral tool, supported sustained use by judges and staff.
- Trust and Security Are Non-Negotiable: Privacy-preserving models and sovereign deployment options were essential for institutional acceptance in the justice system.
Potential for Wider Adaption
| Sector | Adaptability of the Solution |
|---|---|
| Judicial Systems | Applicable across district and high courts facing case backlogs |
| Global South Courts | Relevant for multilingual, resource-constrained justice systems |
| Quasi-Judicial Bodies | Adaptable for tribunals, commissions, and administrative courts |
The information provided here is created as a community resource and is not intended as professional advice or a recommendation by ILSS or Koita Foundation. While we strive to ensure the accuracy of the content, we do not take responsibility for any errors or omissions. Users should use their own discretion before making any decisions based on this information. ILSS or Koita Foundation assume no liability for any actions taken based on the information provided.