How Two Founders Are Using AI to Untangle India’s Legal Disputes
Veteran lawyer Rohan K George had grown accustomed to the friction of the Indian legal system manual case reviews, layers of documentation, and endless email chains even for routine disputes. The work was repetitive, time-consuming, and difficult to scale without simply hiring more people.
Then OpenAI released ChatGPT-4 in 2023. George, then a partner at a law firm, saw an opportunity. He shared the tool with colleagues, who connected him to Adarsh Sosale, a technologist who had already built an algorithmic contract generator for other partners at the firm. When the two met, they discovered a shared belief: artificial intelligence could meaningfully automate parts of legal proceedings.
In 2024 they co-founded Adidem (Latin for “of the same mind” or mutual agreement), a legal-tech startup building an AI- and machine-learning-powered platform to help companies resolve arbitration and litigation disputes faster. Bootstrapped with Rs 50 lakh, the two-member team operates remotely between Chennai and Bengaluru.
Focusing on High-Volume Disputes
The founders initially explored a proof-of-concept word-plugin contract generator. They soon pivoted to the disputes space because far more public data was available. “The data on contracts is locked up behind organisation doors. However, we have data on all judgments passed by high courts and the Supreme Court all the way from 1960. That gave us the confidence to build something in disputes,” says CTO Sosale.
Adidem targets companies that manage large volumes of disputes—typically anywhere from 150 to several thousand cases. George offers a common example: a home-loan company will inevitably see a percentage of loans turn into non-performing assets, and a portion of those will end up in litigation. These cases may involve relatively small individual amounts, yet they form the bulk of the workload for most in-house disputes teams.
“It is all done manually—going through 300 pages of case files, reading 200 emails across 30 contacts. It’s a huge amount of work, and the only way to scale is by hiring more people. That’s where we come in with an AI-led solution,” George explains.
AI as In-House Counsel
Adidem currently offers only in-house legal counselling through its flagship product, Adidem Dispute Intelligence (ADI). The platform first pulls information from official online court systems about new and existing case filings involving the client. It effectively assumes the role of an in-house counsel by automating the initial information-gathering and analysis that usually happens through conversations between internal and external lawyers.
Case files are uploaded into Adidem, which then builds a theory of the dispute: summarising the matter, identifying key issues, conflict points, and inconsistencies. Once ready, the platform shares this analysis with both the client’s internal and external counsel teams and establishes a structured line of communication between them.
The time savings are already measurable. According to George, four hours of email validation now take about 90 minutes. Reading a full case file takes a similar amount of time instead of eight hours. Drafting that once required five hours can now be completed in roughly one.
The drafting capability is proprietary. “If you use traditional AI tools to create a legal draft, it’s going to have disaggregated context pulled from different places with no precision. We have built a patent-pending system of drafting which allows us to identify specific locations and specific documents and tie those together with a common united thread,” George says.
ADI also scans large dispute portfolios to surface plausible risk triggers—key events that often signal the start of legal action—helping companies move from reactive to more proactive management.
A Hybrid Tech Approach
Sosale describes a deliberately mixed technology stack. Adidem uses large language models such as Gemini, Claude, and a refined version of Llama. Alongside these, the team employs older but proven techniques: NLP algorithms developed in the 1990s, TF-IDF and BM25 for text search, Random Forests for generalisation, and fine-tuned BERT models from 2018.
“These decisions are to keep the startup’s output traceable and reliable, and its compute cost efficient,” Sosale explains. “We have a pretty complex pipeline with many smaller models that are doing specific tasks well, and LLMs are used in the final step to put the information together.”
Early Traction and Industry Reality
Adidem’s first client was Cadre ODR, a dispute-resolution company specialising in arbitration, in what George describes as a partnership. The startup is currently piloting ADI with two companies, charging between Rs 75,000 and Rs 1.5 lakh depending on volume, and has received strong early feedback.
Adoption across the broader legal sector remains slow. “Very well-paid lawyers were finding it difficult to navigate certain tools that people in tech and tech-adjacent fields take for granted,” Sosale observes. That friction, while frustrating, also highlighted the size of the opportunity. “I realised that if we can make our product stick, it’s going to create a generational impact on the industry—a transformation that no other tool can provide in India.”
Funding Plans and Competitive Edge
Adidem aims to raise a seed round of $500,000 to $1.5 million by the end of 2025 to accelerate product development. One priority feature is linking the platform’s analysis more deeply with the full body of Indian case law to improve case discovery.
The company competes with international players such as London-based Crimson and New York-based Syllo. George believes Adidem’s strength lies in its focus on collaboration and portfolio-level intelligence rather than single-dispute tools designed mainly for private practitioners.
“Most other companies are creating products to resolve private practitioner problems. Their tech is focused on one dispute. We are very clear that our tech should encourage collaboration. While we want to continue specialising in disputes, we don’t want to get trapped in an echo chamber,” he says.
In a legal system long defined by manual effort and information silos, Adidem is attempting something ambitious: turning AI into a practical co-pilot for the high-volume, high-friction work that sits at the heart of corporate dispute management. If it succeeds, the impact could extend well beyond faster case handling—to a more scalable, data-informed way of practising law in India