AI Cohort Explorer

AI Cohort Explorer, developed by Manifold, is an AI-powered research tool designed to help scientists and clinical researchers build research-ready patient cohorts in minutes rather than months. Purpose-built for cancer and rare disease research, it enables users to define complex cohort criteria using natural language—no coding or deep data expertise required—making it accessible to researchers who need to move quickly from question to insight.

The platform is part of the broader Manifold ecosystem, which spans cancer observational studies, cancer center biobanks, cancer center registries, and rare disease registries. AI Cohort Explorer serves as the starting point for a secure, scalable, AI-native research workflow, bridging the gap between the language of science and the reality of underlying data.

Core Capabilities

• AI-Powered Natural Language Interface: Define cohort criteria in plain language without writing code. The AI understands biomedical terminology and research concepts, enabling researchers to explore and filter unfamiliar datasets with ease.
• AI Transparency and Control: Review and adjust AI-generated cohort criteria through a visual interface. Researchers can modify, approve, or refine the AI's suggestions at any step, maintaining full control over cohort definitions.
• Instant Feasibility Assessment: Receive immediate cohort size estimates and demographic breakdowns as case and control groups are designed, allowing study design to be optimized before finalization.
• Real-Time Visual Interface: Build inclusion and exclusion criteria using an intuitive CONSORT-style interface that mirrors familiar clinical trial design workflows. Interactive charts and tables update dynamically as criteria are refined.
• Advanced Criteria Support: Define complex nested conditions and multi-variable logic, with support for full conjunctive normal form logic for maximum flexibility in cohort definitions.
• Genomic Scale: Filter and analyze hundreds of millions of variants—including germline and somatic—within seconds, enabling cohort building across massive molecular datasets to accelerate discovery.

Integration and Configuration

• Seamless Workflow Integration: Export cohort definitions to preferred analysis environments or save them for future use, allowing researchers to continue working within existing pipelines and tools.
• Flexible Dataset Integration: Connect to any research dataset—clinical, genomic, imaging, or biomarker data—without transformation. Supports both OMOP standard schemas and custom data structures.
• Self-Service Configuration: Use an intuitive configuration UI to define tables, metadata, and few-shot examples. Customize visualization options, column displays, and export variables without requiring technical support.

Platform Context and Broader Research Workflow

• AI Cohort Explorer is one component of the Manifold platform, which is designed to accelerate every step of the research data journey.
• The broader platform includes AI-assisted data ingestion, batch bioinformatics, and AI agents for scientific analysis, enabling teams to move from raw data to actionable insight without friction.
• Fit-for-purpose solutions are available for clinical research leaders in cancer and rare disease, including cancer observational study management, cancer center biobank management, cancer center registry unification, and rare disease registry tools.

Manifold's platform is designed for research institutions seeking to streamline legacy systems, connect biospecimen and clinical data, and unify multimodal data on a modern, AI-native infrastructure. The cohort explorer reflects Manifold's philosophy that AI should serve as the bridge between scientific language and data reality, removing barriers so research ideas can move at the speed of discovery.