In most sectors, technology improves access by making systems faster and easier to use. In law and justice, the situation is different.
The system is complex by design. Legal language is dense. Processes are slow. Information is scattered across documents, courts, and institutions. For many people, especially outside large cities, navigating this system is difficult even before a case begins.
OpenNyAI works at this layer. It does not build a single product for users. It builds the underlying tools that others can use to create solutions for the legal system.
The origin
OpenNyAI was established in 2021 as a collaborative initiative rather than a traditional startup.
It is anchored by a group of organisations including Agami, EkStep, Thoughtworks, National Law School of India University (NLSIU), and Rohini Nilekani Philanthropies.
The founding idea was shaped by a simple observation. Legal systems generate large amounts of text—judgments, filings, contracts, laws—but very little of it is structured or easy to process.
At the same time, advances in artificial intelligence, especially in language models, created an opportunity. If these tools could be adapted to legal contexts, they could help interpret documents, answer questions, and support decision-making.
But there was a problem. Building such systems requires data, infrastructure, and shared standards—none of which were easily available in the legal domain. OpenNyAI was created to address this.
What OpenNyAI does
OpenNyAI is not a single application. It is a platform for building applications. It develops what are called AI digital public goods—open-source datasets, models, and tools that others can use to build legal technology solutions.
These include:
datasets that help train AI models on legal language
tools that process and structure legal documents
interfaces that enable question-and-answer systems in multiple languages
The idea is similar to building roads instead of vehicles. OpenNyAI focuses on infrastructure so that many different solutions can be built on top of it.
One example emerging from this ecosystem is Jugalbandi, a conversational interface that allows users to ask questions about government schemes and rights in local languages.
How the system works
The approach has three layers.
The first layer is data. Legal documents are collected, cleaned, and structured so that they can be used by machine learning models. The second layer is models and tools. These include natural language processing systems that can read, summarise, or answer questions based on legal text.
The third layer is applications. These are built by different organisations using the underlying infrastructure.
For example, a developer can use OpenNyAI datasets and models to build a
a chatbot that explains legal rights, a tool that checks contracts and
a system that helps lawyers search case law. OpenNyAI itself focuses mostly on the first two layers.
Why this approach matters
Most legal technology products face the same starting challenge: they need access to structured legal data and trained models. Without this, each organisation has to build everything from scratch. OpenNyAI reduces this duplication.
Instead of ten teams building ten separate datasets, a shared resource is created. Instead of each team training its own model, common tools can be reused. This lowers the cost and time required to build legal tech solutions.
It also creates consistency. When multiple systems use the same underlying data and models, outputs become more comparable.
Community and ecosystem building
A key part of OpenNyAI is its community model. It brings together lawyers, engineers, researchers, policy experts, and students. This is important because legal problems are not purely technical.
A system that works technically may not work legally or ethically. By combining different disciplines, the initiative aims to create more usable solutions. Programs like maker residencies and hackathons bring participants together to build prototypes and test ideas. These are not just events. They function as testing grounds where concepts are validated before being scaled.
Pilots and early applications
Since OpenNyAI is an infrastructure initiative, its impact is best seen through the applications built on top of it.
Projects emerging from the ecosystem include conversational systems for legal queries, document analysis tools, and platforms for grievance redressal. In some cases, prototypes have been developed to help citizens understand land records, government schemes, or legal procedures through simple question-and-answer interfaces.
These systems often work in regional languages, which is critical in a country with linguistic diversity. The use of AI allows these tools to process large volumes of text quickly and respond in natural language.
Funding and support structure
OpenNyAI does not operate like a venture-funded startup. Its support comes from a mix of philanthropy, institutional backing, and ecosystem partnerships.
Organisations like Rohini Nilekani Philanthropies and initiatives like Agami play a central role in enabling its work. Technology partners like Thoughtworks contribute technical expertise, while academic institutions contribute research and validation. This structure reflects its role as a shared infrastructure rather than a commercial product.
What makes the approach different
OpenNyAI stands apart because of how it defines the problem. Most companies in the legal tech space build applications—tools for contract review, legal research, or compliance. OpenNyAI focuses on what comes before that.
It builds the foundational layer that makes these applications possible.
Another difference is its open model. The tools and datasets are made available under open-source licences, allowing anyone to use and adapt them.
This creates a multiplier effect. Instead of one organisation scaling a product, many organisations can build on the same base.
The initiative also focuses on multilingual capability, which is essential in the Indian context.
The global context
OpenNyAI sits within a broader global movement toward legal technology and AI-driven systems. In many countries, efforts are underway to digitise legal records, automate document review, and build AI-assisted research tools. However, much of this work is led by private companies and focused on enterprise use cases.
OpenNyAI represents a different approach. It emphasises open infrastructure, shared datasets, and community-driven development.
This aligns with a growing interest in digital public goods—systems that are built for broad access rather than proprietary control.
-Our correspondent
