Salesforce vs Veeva

Salesforce Signs Definitive Agreement to Acquire Braze

Salesforce has signed a definitive agreement to acquire Braze, a New York-based customer engagement platform, for approximately $5.66 billion. Braze shareholders will receive $47.50 in cash per Class A share. The acquisition aims to enhance Salesforce's AI-powered marketing capabilities by integrating Braze's real-time customer engagement technology with Marketing Cloud, Data 360, Customer 360, and Agentforce. Braze processes real-time customer data from mobile apps, websites, and other digital channels, enabling personalized communications via email, SMS, WhatsApp, and mobile apps. The platform handles trillions of messages annually and includes BrazeAI for optimizing content, offers, channels, and send times. The deal, expected to close in Salesforce's fiscal year 2028, is part of Salesforce's recent buying spree, including Qualified Inc., Contentful, and Intercom. Braze, co-founded by Bill Magnuson and Jon Hyman, serves about 2,770 enterprise customers, including Canva, Dairy Queen, Equinox, Instacart, Urban Outfitters, and Venmo. Salesforce intends to maintain Braze as a separate brand and continue existing customer and partner relationships.

• Salesforce signs definitive agreement to acquire Braze for approximately $5.66 billion.
• Braze shareholders will receive $47.50 in cash per Class A share.
• Acquisition expected to close in Salesforce's fiscal year 2028.

Salesforce announces $5.66B deal for Braze, stock soars 50%

Salesforce has announced a definitive agreement to acquire customer engagement platform Braze for approximately $5.7 billion in cash, translating to $47.50 per share, a roughly 58% premium over Braze's last closing price of $30.04. The deal, expected to close in fiscal 2028, is a strategic move to accelerate the time between customer signals and marketing actions, integrating Braze with Salesforce's Marketing Cloud, Data 360, Customer 360, and Agentforce. Braze, with about 2,770 customers including Canva and Venmo, reported strong growth. The acquisition aims to strengthen Salesforce's AI marketing capabilities, though integration risks remain. Following the announcement, Braze shares surged while Salesforce shares dipped slightly.

• Salesforce agreed to acquire Braze for approximately $5.7 billion in cash at $47.50 per share.
• The deal price is a 58% premium over Braze's closing price of $30.04 on Monday.
• The transaction is expected to close in fiscal 2028, subject to shareholder and regulatory approvals.

Salesforce Accelerates European AI Leadership with $1 Billion Investment in Spain

Salesforce announces a $1 billion investment in Spain to accelerate European AI leadership, alongside other recent news including the acquisition of Loops and Listen Labs, and the launch of AIforce and Koa.

IQVIA Expands Veeva Partnership with Clinical Operations Applications

IQVIA and Veeva Systems announced an expansion of their partnership, with IQVIA selecting Veeva CTMS, eTMF, Study Startup, and Site Connect as enterprise standard applications for its clinical development studies. This extends the previously announced EDC partnership. The collaboration aims to increase trial speed and efficiency, strengthen site centricity, and improve decision-making for clinical research customers. All Veeva clinical solutions will also be available through IQVIA for sponsors seeking a full Veeva technology stack. Executives from both companies emphasized the benefits of integrated technologies and customer flexibility in choosing EDC, RTSM, and eCOA solutions. The announcement was made on October 13, 2026, ahead of the Veeva R&D and Quality Summit scheduled for October 20-21 in Boston.

• IQVIA selected Veeva CTMS, eTMF, Study Startup, and Site Connect as enterprise standard applications.
• Partnership expansion extends the previously announced EDC partnership.
• All Veeva clinical solutions will be available through IQVIA for sponsors.

Servier Adopts Veeva OpenData Globally for AI

Servier, a French pharmaceutical company, is standardizing its customer reference data across more than 80 countries with Veeva OpenData, part of Veeva Data Cloud. This initiative builds on Servier's use of Veeva Link Key People and aims to create an AI-ready data foundation by harmonizing fragmented data silos. The centralized data will help commercial and medical teams gain faster insights and improve efficiency. Liam Hanrahan, Director of Global Operations Excellence at Servier, highlighted that the centralized data will improve processes and enable a semantic layer for better engagement with key healthcare professionals. Veeva's president, Kilian Weiss, emphasized that 89% of AI initiatives fail due to data challenges, and Servier's data-first approach demonstrates industry leadership. The adoption replaces fragmented silos and ensures consistency for scaling advanced analytics and AI.

• Servier standardizes customer reference data with Veeva OpenData across more than 80 countries.
• The initiative builds on Servier's use of Veeva Link Key People.
• Veeva OpenData is part of Veeva Data Cloud, which also includes Veeva Link and Veeva Compass.

Stop Anthropomorphizing LLMs, Treat Them as Tools

This article argues that marketers and tech professionals fundamentally misunderstand large language models (LLMs) by treating them as conscious entities. It explains that LLMs are statistical pattern engines that predict the next token based on probability, not logical reasoning. This leads to common failures like miscounting letters or clinging to incorrect answers. The author advises abandoning implicit logic by breaking tasks into single steps, providing tight constraints to reduce hallucinations, and not arguing with erroneous outputs. By reframing LLMs as tools rather than coworkers, marketing workflows can be made more effective and efficient.

• LLMs are predictive text engines based on statistical probability, not human logic.
• LLMs break text into tokens, which can obscure letter-level details and cause miscounting.
• Users should break tasks into single-purpose steps to improve LLM output accuracy.