Empowering Life Sciences
with Agentic AI

An IC plan and data processing agent that provides real-time support for home office and operations teams. It identifies data quality issues, resolves processing errors, and streamlines routine updates to incentive plans and data workflows—ensuring accurate, efficient, and compliant plan execution with minimal manual effort.

This agent enables global operations and IT administrators to easily monitor system health, including jobs, data processing, and operational tasks, while allowing them to adjust common configurations like teams, roles, and more.

Helps the field force and home office with effective answers on their HCP alignments and call plans, and allows the field force to submit change requests or inquiries to the home office.

An alignment agent that helps users by suggesting alignment changes, monitoring alignment health, and creating new alignments from scratch based on products and launch types. It continuously monitors alignment health using sales, potential, vacancies, and other parameters to suggest changes that speed up time to market and reduce effort for the home office and field teams.

Analyzes resource optimization plans and makes recommendations for improving customer engagement and ROI, while accounting for practical channel and customer constraints to drive adoption.

Generates concise summaries from text (articles, news, whitepapers), images, and voice recordings to extract key information.

Analyzes and generates textual descriptions or summaries of images, identifying key features and insights.

Assists in planning, researching, and writing well-structured and formatted blog posts on various topics.

Automatically generates relevant questions from a given text to aid in learning, comprehension, and assessments.

Converts input text into a structured interview style, organizing information into a question-and-answer format.

Applies multiple tags to a given text using keyword-based and theme-based tagging techniques.

Customizes responses based on user preferences, adapting to past interactions for a personalized experience.

Converts text into speech and formats it into a podcast-like structure (supports limited voice variations).

Generates high-quality marketing content, including articles, social media posts, and promotional materials.

Reviews and refines marketing content to ensure quality, coherence, and relevance.

Answers questions on structured datasets such as databases, spreadsheets, and tabular data, providing insights, summaries, and analysis.

Performs Q&A and analysis on unstructured data sources, including documents (Word, PDF, PPT), images, and tables, extracting key information.

Supports Q&A on multimodal data, including text, images and audio files, using AI-powered speech and visual analysis.

Constructs graph structures from JSON data and enables querying using shortest path algorithms for optimized navigation.

Crawls the web to extract structured and unstructured information, including news and research data.

Creates research reports on specific topics, using information and insights gathered from external and internal data sources.

Extracts, analyzes, and visualizes key performance indicators (KPIs) from structured business data.

Automatically generates interactive BI dashboards from structured data for reporting and analytics.

Identifies unusual patterns, anomalies, and outliers in business and operational data.

Predicts future trends using historical data and AI-driven forecasting models.

Compares a business' performance against competitors by analyzing market data and benchmarks.

Evaluates and analyzes customer feedback, reviews, and surveys to determine sentiment and trends.

Transforms natural language questions into structured BI insights and SQL queries.

This agent provides instant access to pharma commercial data trends, metrics, and actionable insights without requiring SQL knowledge. It translates natural language queries into real-time, decision-ready intelligence, empowering users to drive smarter strategies with ease.

Converts unstructured electronic health record data into structured formats for seamless clinical trial integration, smartly transforming multi-page logs and notes into a CDASH-compliant layout.

Axtria Rapid CSR utilizes a multi-LLM approach to create first draft clinical study report sections 30%-50% faster than manual efforts with 90% accuracy. Axtria Rapid CSR’s authoring capability delivers substantial time and cost savings, enabling faster regulatory submissions for studies of all sizes and complexity.

This agent serves as an expert guide for navigating operational metadata in Axtria DataMAx. It helps users track when data was processed, what attributes it carries, and its quality score. With full transparency into data lineage, orchestration, and ETL processes, the agent ensures users always know the 'who, what, when, and how' behind their data—empowering better decision-making and governance.

The agent transforms business logic described in plain language or provided in unstructured files into precise, automated rules. It simplifies rule creation, eliminating complexity and ensuring data-driven processes are implemented quickly and accurately.

This agent helps users uncover hidden datasets and identify new KPIs to broaden their analytical scope. Users can count on it to surface additional data sources, seamlessly integrate them with existing insights, and unlock deeper value within their Axtria DataMAx environment—empowering them to make smarter, data-driven decisions.

This agent prepares data based on specific business goals including mix modeling, journey analytics, data product provisioning, and more. This agent automatically creates multi-layered data pipelines and journeys with minimal human intervention.

Generates optimized SQL queries based on user input to retrieve structured data from databases.

Automatically generates code snippets based on specifications, programming logic, and templates.

Executes provided code snippets in a secure environment, returning output, errors, or logs.

Connects to various databases using provided credentials to extract metadata and perform queries.

Enables searching, adding, deleting, and creating temporary files for efficient file management.

Converts text into speech with multiple voice and language options for accessibility and narration purposes.

Transcribes spoken words from microphone input or audio files into text.

Supports the creation and management of vector databases using tools like ChromaDB, Faiss, Pinecone, and Weaviate.

Executes specified functions or processes on request, acting as an automation agent.

Allows selection between large and small AI models, maintaining the same code while modifying prompts as needed.

Uses a lightweight Semantic Kernel to efficiently route requests to appropriate AI models.