New
Relativity aiR
Description
Relativity aiR is an artificial intelligence application built to enhance efficiency in ediscovery tasks within the legal profession. It applies language models and data processing techniques to automate complex reasoning traditionally performed by attorneys. The system is trained on large volumes of legal text and supports precision outputs that align with professional expectations and regulatory standards.
Its architecture allows lawyers to generate, review, and validate documents or research outputs within secure and auditable environments. Through contextual understanding, the tool reduces the time needed for information retrieval, drafting, and risk assessment without compromising quality. Integration with existing legal workflows enables seamless use across case management, document review, and advisory functions.
It supports structured data extraction and maintains traceability for all AI‑assisted operations to ensure accountability and defensibility of work product. The platform’s performance improves with continued use, refining predictive accuracy and aligning outputs with the user’s practice area and jurisdiction. Its key functional emphasis lies in Summarization,Analytics, reflecting its specialization in that domain of legal work. Further product information and access options are provided through relativity.com.
Features
Features
✅ Intelligent prioritization and culling — Relativity AIR uses AI to highlight and prioritize relevant documents, reducing the volume for human review.
✅ Continuous learning with reviewer feedback — The system adapts from reviewer decisions in real time to refine predictive models and surface better results.
✅ Clustering & concept expansion — Documents are grouped by thematic similarity and the system expands concept searches to uncover related content.
✅ Integrated review triggers & workflows — AIR seamlessly injects AI-driven tags, batch assignments, and predictive workflows into Relativity’s review pipeline.
✅ Explainability & ranking transparency — Each AI decision is accompanied by scoring and rationale, so reviewers can trust or challenge the model’s suggestions.
✅ Continuous learning with reviewer feedback — The system adapts from reviewer decisions in real time to refine predictive models and surface better results.
✅ Clustering & concept expansion — Documents are grouped by thematic similarity and the system expands concept searches to uncover related content.
✅ Integrated review triggers & workflows — AIR seamlessly injects AI-driven tags, batch assignments, and predictive workflows into Relativity’s review pipeline.
✅ Explainability & ranking transparency — Each AI decision is accompanied by scoring and rationale, so reviewers can trust or challenge the model’s suggestions.
Review
Login to Write Your ReviewThere are no reviews yet.
