Legara provides a specialised AI platform that automatically summarizes and analyses large legal evidence bundles for dispute‑resolution professionals. By using a proprietary, domain‑trained model and unlimited‑length processing, it delivers context‑aware, accurate summaries without the word‑limit constraints of generic AI tools, while maintaining end‑to‑end encryption and secure data isolation.
Funding
Funding not disclosed
Founders
Product
Problem
Professionals in dispute resolution must review and analyse massive evidence bundles, but existing AI tools struggle with contextual understanding, have word‑count limits, and often produce inaccurate or incomplete summaries.
Solution
Legara AI offers a specialised summarisation platform built for large legal evidence sets. By training a private custom model on domain‑specific data and integrating a tailored workflow, the system generates accurate, reliable summaries without the word‑limit constraints of generic AI. The platform automates analysis, reducing summarisation time by up to 50% and minimising manual editing. All processing occurs within a secure, privacy‑focused environment, ensuring confidential client information remains protected. The resulting concise reports can be reviewed directly by lawyers, arbitrators, and mediators, streamlining case preparation and improving organisational efficiency.
Target Audience
Primary users are law firms, in‑house legal teams, arbitration centres, and mediation providers that regularly handle large evidence packages in commercial, construction, and employment disputes.
Features
- Proprietary, domain‑trained language model optimised for legal evidence and dispute‑resolution terminology
- Unlimited‑length document handling that processes entire evidence bundles in a single run
- Context‑aware summarisation that preserves critical facts, arguments, and citations
- Automated quality checks to detect missing information or hallucinations before delivery
- End‑to‑end encryption and secure data isolation to meet confidentiality requirements
- Integration‑ready API for embedding summaries into existing case‑management or document‑review systems