Agentic Assistant - 2026 Pricing, Features, Reviews & Alternatives

Agentic Assistant is a multi-agent artificial intelligence platform integrated into a leading electronic data capture system for clinical trial management. It delivers a conversational interface that enables clinical research professionals to query protocol documents, retrieve operational metrics, and access live trial data using natural language. The product supports pharmaceutical sponsors, contract research organizations, clinical data managers, medical monitors, and operations teams in regulated environments. It addresses the challenge of fragmented data access by unifying protocol intelligence, operational insights, and data querying into a single interface requiring no technical expertise.

The architecture relies on three distinct AI agents, each powered by a dedicated retrieval-augmented generation pipeline. The protocol intelligence agent generates a study-specific knowledge base from uploaded protocols, indexing eligibility criteria, endpoints, visit schedules, procedures, prohibited medications, safety timelines, and amendment histories. The operations insights agent connects to an operational metadata pipeline that dynamically computes metrics such as enrollment trends, visit completion rates, query aging, site comparisons, and data entry lag from live trial data. The clinical data agent leverages an electronic data capture metadata pipeline to translate natural language prompts into validated database queries that return formatted tables, counts, and summaries exportable to spreadsheets or images for reporting.

Agentic Assistant operates natively within the electronic data capture platform without middleware or external configuration. It generates the study knowledge base at study creation with zero manual setup, synchronization delays, or external API dependencies. Role-based dashboards display real-time metrics tailored to user responsibilities, including enrollment key performance indicators, data quality alerts, and operational risk flags. Study-level isolation ensures that data remains confined to its source study, while role-based access controls restrict user visibility to authorized information only. Comprehensive audit trails record every interaction with user identification, time stamps, and source references in alignment with global regulatory requirements.

The modular framework is designed for future expansion into predictive analytics, automated data quality checks, safety monitoring, and risk-based oversight. Clinical operations, data management, and medical monitoring teams collaborate through a common interface that promotes consistency and reduces departmental dependencies. The platform’s exportable outputs and traceable sources support regulatory traceability and oversight. Scalability across studies of varying size allows seamless adaptation to evolving trial demands while preserving data integrity and security.