INTIENT™ enables the application of AI and advanced analytics to that data, delivering much faster insights that can lead to better patient outcomes. It is built upon Accenture’s market-proven platforms for research, pharmacovigilance, clinical development, and patient services. It enables the integration of new technology, and advanced analytics powered by Accenture Applied Intelligence. The platform improves the continuity and flow of data across life sciences enterprises. Accenture introduced INTIENT™ in May 2019.

Accenture’s touchless testing platform is an automated, AI and analytics-driven testing software. The Teach and Test framework helps companies in building, monitoring and measuring reliable AI systems within their own infrastructure or in the cloud. The testing platform ensures that AI systems are producing the right decisions in two phases. The “Teach” phase focuses on the choice of data, models and algorithms that are used to train the machine learning engine for producing relevant outputs. This phase also involves experimenting and statistically evaluating different models to select the best performing model to be deployed into production, while monitoring bias as well as ethical and compliance risks. In the “Test” phase, AI system outputs are compared to key performance indicators and assessed for whether the system can explain the decision-making process. It uses cloud-based tools and techniques to monitor the system.

The platform integrates analytics applications using machine learning and deep learning with edge analytics and IoT services. The solution is available through OnDemand low-code platform. The platform provides end-to-end security and privacy services that are enhanced through the localization of sensitive data processing. The platform is used for remote monitoring and fleet management solutions. It has access to more than 350 data sources.

Accenture offers an integrated solution of AI, automation, and analytics. It provides intelligent customer engagement through the support of virtual agents and smart automation tools, automates and scales consistency across all channels, increases digital adoption by delivering personalized interactions.It provides data-driven insights across the supply chain network, enhances precision forecasting, augments decision-making, predicts customer’s requirements through the processing of structured and unstructured data, automates real-time flagging. The solution leverages advanced data mining, predictive analytics and pattern recognition for identifying emerging criminal patterns through non-rule based, self-learning detection in the field of crime detection.It increases the ongoing productivity of marketing media through AI and machine learning-enabled attribution; for intelligent healthcare solutions, it improves operational efficiency with optimized scheduling, augmented processes, and streamlined management of claims and payment. 

SCAML automatically determines and labels the sensitivity of documents. It allows an enterprise to apply classification on technology, data protection, and controls. SCAML works by automatically classifying unstructured data in any format, including emails and documents.

The company’s artificial intelligence research and development lab, in collaboration with universities such as Stanford, MIT, and Carnegie Mellon, focuses on critical business problems by applying machine learning, natural language processing, knowledge representation, and reasoning. The problem areas include:

• Inquisitive virtual agents- For providing faster availability of documents to match queries in a chatbot, Accenture is developing new approaches to mine repositories of past customer-agent interactions. This will accelerate the process of extracting and preparing the content necessary for the chatbots. The company is also developing approaches to extend commercial chatbot technologies to enable more complex dialogues required by specific use cases (cases in which queries do not match a particular, pre-existing document to be served by a chatbot and an agent-based diagnostic conversation is called)
• Intelligent risk monitoring- Develops models for different project categories and their associated risks. It then analyzes a combination of structured and unstructured data sources to provide project managers with risk alerts
• Collaborative content synthesis – Develops systems for identifying relevant content by combining technical approaches including machine learning and natural language processing

Accenture Artificial Intelligence Engine, developed by Accenture Labs Bangalore, provides a platform for integrating open-source AI components and allows Accenture to deliver intelligent automation for enterprises quickly. It focuses on issues concerned with vendor-specific AI implementation options such as costs of licensing and implementation, data residence and security, lack of customisability, vendor lock-in, and limited future-proofing. Accenture offers AAIE deployed incident management applications for the retail sector and in email classification applications for the transportation sector.

Accenture Google Cloud Business Group is a collaborative venture between Accenture and Google, established in 2018. The Cloud Business Group is a central hub that unifies the domain expertise and resources of both alliance partners to coordinate joint AI innovation, with a focus on optimizing AI offerings for the cloud environment. It offers enterprise solutions through a combination of Accenture’s industry and data science knowledge, and Google Cloud’s AI and machine learning capabilities. The enterprise solutions include multi-channel customer interactions and improved data management, hyper-personalization in marketing, sales and services.