Showing 154 results
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NEWPEAK Matrix®
Life Sciences AI and Analytics Services for Commercial PEAK Matrix® Assessment 2025
July 16, 2025In recent years, life sciences enterprises have reprioritized and overhauled their R&D investments. They now focus on streamlining their pipelines and shifting toward new and large molecules. This transformation has compelled aggressive cost containment initiatives, prompting organizations to seek innovative commercialization strategies for their drugs and devices. Additionally, the growing focus on patient-centricity and customer experience has accelerated outsourcing to specialized providers. Providers are essential in this transformation. They offer expertise in generative AI, advanced analytics, and AI/ML, to streamline workflows and maximize efficiency. In response to market needs, they have expanded their portfolios to offer comprehensive, end-to-end solutions supporting pre-launch and post-launch commercialization activities. In this report, we assess 30 providers featured on the Life Sciences AI and Analytics Commercial Services PEAK Matrix® Report. Each provider profile highlights the service focus, key IP/solutions, domain-specific investments, and case studies.
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Viewpoint
Systems of Execution (SoE) in Life Sciences: Enabling Enterprise-scale Omnichannel Engagement
June 25, 2025Life sciences enterprises operate in an increasingly complex engagement landscape due to rising content fatigue, expanding Healthcare Professional (HCP)/patient touchpoints, and growing stakeholder expectations for relevance. Traditional engagement strategies, characterized by fragmented data, siloed operational workflows, and legacy technology systems built for function-level enablement, have led to disjointed engagement and effort duplicity across enterprise teams. Systems of Execution (SoE) address this challenge by acting as an intelligent execution layer that unifies data across commercial, medical affairs, and patient services to activate cross-functional synergies in delivering coordinated stakeholder-centric omnichannel engagement across the enterprise. By leveraging real-time data signals, AI-powered next-best-action recommendations, and automated adaptive engagement workflows, SoE enable enterprises to autonomously deliver personalized and contextually relevant stakeholder interactions with minimal human intervention. This report outlines core SoE capabilities and provides life sciences CXOs with a clear implementation roadmap. It helps life sciences CXOs achieve personalized, enterprise-scale omnichannel execution, designed to surface cross-functional insights and autonomously act on them, to deliver coordinated omnichannel engagement across enterprise functions.
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Viewpoint
Maximizing the Power of Real-world Evidence (RWE): AI’s Role in Accelerating Life Sciences' Next Era
June 12, 2025Life sciences enterprises are increasingly turning to Real-world Evidence (RWE) as an essential input for decision-making across the product life cycle – from early-stage R&D to post-market access and safety. RWE offers validated insights into treatment effectiveness, patient outcomes, and safety, but fragmented data sources, inconsistent quality, and evolving compliance expectations often challenge its generation. With the rising volume and diversity of Real-world Data (RWD), traditional analytics approaches are no longer sufficient. AI, including technologies such as NLP, machine learning, and generative models, is redefining how RWE is produced and operationalized. AI is accelerating data curation, enabling predictive analytics, and delivering regulatory-grade evidence at scale. This Viewpoint outlines how AI is transforming the RWE landscape across six domains: drug discovery, clinical trials, manufacturing, commercialization, pharmacovigilance, and regulatory affairs. It also explores emerging models such as insights-as-a-service and autonomous evidence networks, which offer scalable, modular engagement approaches for AI-powered RWE. The report provides practical recommendations for both enterprises and providers, covering capability investments, infrastructure modernization, governance models, and partnership strategies. It aims to help stakeholders reimagine their data-to-evidence journeys and build future-ready ecosystems for continuous, AI-enabled insight generation. Scope Industry: life sciences Geography: global Contents In this report, we examine: RWE’s current landscape and growing importance in life sciences AI’s role in addressing foundational RWE challenges AI-enabled key RWD/RWE use cases across the product life cycle Emerging engagement models such as BPaaS, AaaS, and IaaS Future-forward models, including autonomous evidence networks and modular AI-enabled partnerships Strategic considerations to operationalize AI-powered RWE for enterprises and providers
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June 09, 2025The life sciences industry is undergoing rapid digital transformation, fueled by the need for greater agility, regulatory compliance, and patient-centric operations. Enterprise platforms such as SAP, Oracle, and Salesforce have evolved from back-end systems of record to strategic innovation enablers, powering R&D, strengthening supply chains, and enhancing commercial effectiveness. However, challenges remain, as many organizations still operate fragmented legacy systems, struggle with complex migrations, and navigate the trade-offs between global standardization and local compliance. To address these needs, providers are investing in industry-specific accelerators, compliance-ready architectures, and intelligent automation capabilities. They are strengthening their expertise across SAP, Oracle, and Salesforce platforms, while also expanding AI/ML offerings to drive more proactive, insights-led operations. In this report, we assess 20 life sciences enterprise platform providers and position them on Everest Group’s PEAK Matrix®, a composite index of distinct metrics related to the providers’ capabilities and market impact. The study will enable buyers to choose the best-fit provider based on their sourcing considerations, while providers will be able to benchmark their performances against each other. Scope Industry: life sciences Geography: global Services: life sciences enterprise platform services Contents In this report, we examine: The provider landscape for life sciences enterprise platform services Life sciences enterprise platform providers on several capabilities and market success-related dimensions
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June 02, 2025Life sciences enterprises are embracing digital technologies to navigate the growing complexities in drug development, commercialization, and regulatory compliance. As economic pressures and competitive dynamics intensify, organizations are turning to digital services to improve operational resilience and achieve faster time-to-market. Providers are responding with targeted investments in AI / generative AI, data platforms, and industry-specific solutions to meet enterprise demands across the life sciences value chain. This PEAK Matrix® report offers a detailed evaluation of 35 providers delivering digital services in the life sciences sector, including biopharmaceutical, medical device, and others. It examines how these providers are enabling transformation through scalable solutions, co-innovation models, and differentiated capabilities. By assessing providers across dimensions such as market adoption, innovation, and delivery footprint, the report helps enterprise buyers identify the right strategic partners for their digital agendas. Scope Industry: life sciences (biopharmaceutical, medical devices, and others) Service: digital services Geography: global Contents In this report, we offer: Providers’ evaluations The evaluation scope Market trends Provider landscape analysis Key buyer considerations and takeaways Memberships Life Sciences Information Technology Sourcing and Vendor Management
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April 09, 2025In today’s dynamic talent market, organizations must actively monitor key roles and skills, both in-demand and emerging, to enable strategic workforce planning. Higher demand may indicate more significant competition for talent or a higher risk of attrition, making it vital to analyze talent demand trends to anticipate external competition and identify leading industries for talent acquisition. Everest Group’s half-yearly report offers insights into monthly IT services talent demand trends across India, highlighting top industries, roles, and skills based on H2 2024 demand. Leveraging data from our Talent Genius™ tool, this report comprehensively analyzes the current talent market, empowering organizations to stay competitive, plan for future workforce needs, and make informed talent acquisition decisions. Scope Industry: IT services Geography: India Contents In this report, we analyze talent demand trends in India's IT services sector on a national scale. Additionally, we provide detailed profiles of 15 major Tier-1 and Tier-2 cities, offering insights into talent demand trends, top industries, key roles, and essential skills in each location.
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Tech Launch Perspective
Telecommunications – Review of NetoAI’s TSLAM 1.5B Product Launch
March 12, 2025Telecom-specific AI-powered solutions will be vital in optimizing telecom infrastructure and delivering next-generation connectivity as 5G, Open RAN, and network disaggregation gain momentum. The industry is significantly transforming, with Large Language Models (LLMs) and Small Language Models (SLMs) being increasingly adopted to automate, optimize, and enhance network operations, customer service, and infrastructure planning. Unlike generic AI models, industry-specific LLMs and SLMs are designed to understand, process, and generate telecom-relevant insights, making them more efficient and accurate for domain-specific applications. SLMs are particularly valuable for low-power, real-time AI applications, making AI-driven network optimization and diagnostics more scalable. This LLM integration offers numerous benefits, including improved efficiency, personalized customer interactions, and advanced network optimization. In this report, we explore NetoAI’s SLM product TSLAM 1.5B's transformative potential, examining its key features and impact on network management, customer support, and security assistance. We also provide insights into its market positioning, key benefits, and broader implications for telecom enterprises as they cost-effectively adapt to sustainable standards. Scope All industries and geographies Contents In this report, we: Provide insights into the global telecommunications industry Examine NetoAI’s current positioning and alignment among telecommunication enterprises Explore the features, benefits, and challenges of NetoAI’s product TSLAM 1.5B Membership(s) Application Services Artificial Intelligence (AI) Banking and Financial Services Information Technology Cloud and Infrastructure Services Clinical Development Technology Cybersecurity Data & Analytics Digital Services Digital Workplace Enterprise Platform Services (EPS) Healthcare Payer and Provider Information Technology Insurance Information Technology Marketing and Interactive Experience Life Sciences Information Technology Retail and CPG Sustainability Technology and Services Sourcing and Vendor Management
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Jan. 29, 2025This breaking viewpoint provides Everest Group’s view on how AI infusion – integrating AI into existing enterprise workflows – will outpace full AI replacement in key industries. It explores AI's role in financial services, healthcare, and regulatory compliance, where real-time fraud detection, anomaly identification, and instant diagnostics are driving transformation. The viewpoint highlights the advantages of embedding AI within current systems to enhance efficiency, reduce latency, and optimize decision-making. It provides insights into market trends, enterprise adoption strategies, and the evolving regulatory landscape, helping businesses navigate AI-driven innovation while maintaining operational continuity. Membership(s) Available to all membership areas
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Tech Launch Perspective
Life Sciences Real World Evidence (RWE) / Real World Data (RWD) Platforms – Review of Oracle Analytics Intelligence for Life Sciences
Jan. 27, 2025Life sciences enterprises are increasingly focusing on Real-world Evidence / Real-world Data (RWE/RWD) to promote patient centricity, identify the next opportunity, and demonstrate value for their investments. Enterprises are seeking next-generation solutions to address interoperability and data access challenges. This shift compels providers to innovate their offerings and introduce advanced solutions that enhance analytics and insights, enable interoperability, and enhance data security. Following suit, Oracle has launched its Analytics Intelligence for Life Sciences offering, which provides AI-enabled workflows, enhanced data interoperability, and pre-integrated datasets. In this report, we examine Oracle’s current market position, key product announcements, and industry objectives. We also review Oracle’s RWE/RWD technology and cover essential RWE/RWD issues and objectives for life sciences enterprises. Scope Industry: life sciences Geography: global Segment: RWE/RWD platforms Contents In this report, we examine: Key enterprise RWE/RWD issues and objectives Oracle’s Analytics Intelligence for Life Sciences announcement Memberships Life Sciences Information Technology Sourcing and Vendor Management
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Jan. 24, 2025Generative AI can potentially revolutionize the life sciences industry, driving innovation across key areas of the value chain. By streamlining drug discovery, optimizing clinical trials, and enhancing decision-making, it can significantly reduce the time and cost required to bring new medicines to market, setting a new benchmark for industry efficiency and innovation. However, adopting generative AI presents challenges including concerns about data privacy, model accuracy, training resource demands, and ethical implications. As providers work toward addressing these challenges and generative AI becomes a key industry innovation driver, the focus is slowly moving beyond experimental pilot projects to full-scale implementations. This report examines generative AI’s value promise across the life sciences value chain, its market adoption within the industry, and the capabilities of 15 leading providers driving this innovation from pilots to scaled deployment. Scope Industry: life sciences Geography: global The assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with leading life sciences providers, client references, and Everest Group’s ongoing analysis of the life sciences market Contents In this report, we examine Generative AI’s value promise across different segments of the life sciences value chain Its market adoption in the life sciences industry 15 leading providers’ profiles Membership(s) Life Sciences Business Process Life Sciences Information Technology Sourcing and Vendor Management
