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Enhance Business Communication with Accurate Email Verification in Salesforce
28Feb

Enhance Business Communication with Accurate Email Verification in Salesforce

Email is the backbone of business communication, powering client interactions, customer engagement, and marketing campaigns. However, inaccurate email data can hurt your marketing efforts, damage your sender reputation, and lead to wasted resources. Verifying email addresses in Salesforce ensures data accuracy, improves deliverability, and strengthens overall communication efficiency. This guide explores how to easily verify email addresses in Salesforce, including a seamless solution—VTM (Verify the Email)—designed to simplify the process. How to Verify User Email Addresses in Salesforce Salesforce provides a built-in feature for verifying user email addresses when setting up accounts. This ensures that the email is active and functional. Here’s how: 1️⃣ Access Salesforce Setup – Navigate to the Setup Menu in Salesforce.2️⃣ Find the User Profile – Go to the Administration page, select Users, and choose the specific user account that needs verification.3️⃣ Trigger the Verification Email – When an email address is updated, Salesforce sends an automated verification email to the user.4️⃣ Confirm the Email – The user must click the link in the email to complete verification. While this method ensures the validity of user emails, it’s limited to Salesforce accounts. What about verifying emails for leads, contacts, and accounts? That’s where VTM comes in. Why Email Verification Matters in Salesforce Before diving into how VTM enhances verification, let’s explore why email validation is crucial: ✅ Improved Deliverability – Invalid email addresses cause bounces, harming your sender reputation and lowering future email success rates. ✅ Data Accuracy – Keeping Salesforce records clean ensures your team engages with valid contacts, reducing inefficiencies and missed opportunities. ✅ Compliance & Trust – Verifying emails helps maintain compliance with GDPR, CAN-SPAM, and other regulations, protecting your business from legal risks. ✅ Cost Efficiency – Many email marketing tools charge per email sent. Verifying addresses prevents wasted spending on invalid contacts. Given these challenges, VTM offers a scalable, automated solution for seamless email verification directly within Salesforce. How VTM Streamlines Email Verification in Salesforce Verify Email Addresses Without Sending Emails VTM checks the existence, domain status, and active mailbox availability of an email address—without sending actual emails. This prevents spam filter triggers and ensures verification happens discreetly. Batch Verification for Large Datasets Managing a large database? VTM enables bulk verification, allowing users to validate thousands of email addresses at once. This ensures your Salesforce data stays accurate and reliable, improving email campaign success rates. Real-Time Email Validation VTM performs instant email verification when new addresses are added to Salesforce. This proactive approach helps sales and marketing teams avoid bad data before campaigns even begin. Ensure Compliance with Email Regulations VTM helps businesses meet email security and compliance standards, ensuring verified addresses align with GDPR, CAN-SPAM, and other email regulations. This protects your organization from potential penalties while maintaining customer trust. Boost Marketing ROI Invalid email addresses can cause even the best-planned campaigns to fail. By verifying emails with VTM, businesses increase open rates, click-through rates, and overall campaign ROI. Seamless Salesforce Integration VTM operates entirely within Salesforce, offering a user-friendly experience with no need to switch between platforms. Its intuitive interface makes email verification simple and efficient for all users. Take Control of Your Email Data in Salesforce Ensuring email accuracy is key to business success. Whether you’re looking to improve deliverability, reduce bounces, or enhance campaign efficiency, VTM provides a powerful solution to keep your Salesforce data clean and reliable. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 28, 2025in Data, Salesforce, Technology
Generative AI in Marketing
28Feb

Generative AI in Marketing

Generative Artificial Intelligence (GenAI) continues to reshape industries, providing product managers (PMs) across domains with opportunities to embrace AI-focused innovation and enhance their technical expertise. Over the past few years, GenAI has gained immense popularity. AI-enabled products have proliferated across industries like a rapidly expanding field of dandelions, fueled by abundant venture capital investment. From a product management perspective, AI offers numerous ways to improve productivity and deepen strategic domain knowledge. However, the fundamentals of product management remain paramount. This discussion underscores why foundational PM practices continue to be indispensable, even in the evolving landscape of GenAI, and how these core skills can elevate PMs navigating this dynamic field. Why PM Fundamentals Matter, AI or Not Three core reasons highlight the enduring importance of PM fundamentals and actionable methods for excelling in the rapidly expanding GenAI space. 1. Product Development is Inherently Complex While novice PMs might assume product development is straightforward, the reality reveals a web of interconnected and dynamic elements. These may include team dependencies, sales and marketing coordination, internal tooling managed by global teams, data telemetry updates, and countless other tasks influencing outcomes. A skilled product manager identifies and orchestrates these moving pieces, ensuring product growth and delivery. This ability is often more impactful than deep technical AI expertise (though having both is advantageous). The complexity of modern product development is further amplified by the rapid pace of technological change. Incorporating AI tools such as GitHub Copilot can accelerate workflows but demands a strong product culture to ensure smooth integration. PMs must focus on fundamentals like understanding user needs, defining clear problems, and delivering value to avoid chasing fleeting AI trends instead of solving customer problems. While AI can automate certain tasks, it is limited by costs, specificity, and nuance. A PM with strong foundational knowledge can effectively manage these limitations and identify areas for automation or improvement, such as: 2. Interpersonal Skills Are Irreplaceable As AI product development grows more complex, interpersonal skills become increasingly critical. PMs work with diverse teams, including developers, designers, data scientists, marketing professionals, and executives. While AI can assist in specific tasks, strong human connections are essential for success. Key interpersonal abilities for PMs include: Stakeholder management remains a cornerstone of effective product management. PMs must build trust and tailor their communication to various audiences—a skill AI cannot replicate. 3. Understanding Vertical Use Cases is Essential Vertical use cases focus on niche, specific tasks within a broader context. In the GenAI ecosystem, this specificity is exemplified by AI agents designed for narrow applications. For instance, Microsoft Copilot includes a summarization agent that excels at analyzing Word documents. The vertical AI market has experienced explosive growth, valued at .1 billion in 2024 and projected to reach .1 billion by 2030. PMs are crucial in identifying and validating these vertical use cases. For example, the team at Planview developed the AI Assistant “Planview Copilot” by hypothesizing specific use cases and iteratively validating them through customer feedback and data analysis. This approach required continuous application of fundamental PM practices, including discovery, prioritization, and feedback internalization. PMs must be adept at discovering vertical use cases and crafting strategies to deliver meaningful solutions. Key steps include: Conclusion Foundational product management practices remain critical, even as AI transforms industries. These core skills ensure that PMs can navigate the challenges of GenAI, enabling organizations to accelerate customer value in work efficiency, time savings, and quality of life. By maintaining strong fundamentals, PMs can lead their teams to thrive in an AI-driven future. AI Agents on Madison Avenue: The New Frontier in Advertising AI agents, hailed as the next big advancement in artificial intelligence, are making their presence felt in the world of advertising. Startups like Adaly and Anthrologic are introducing personalized AI tools designed to boost productivity for advertisers, offering automation for tasks that are often time-consuming and tedious. Retail brands such as Anthropologie are already adopting this technology to streamline their operations. How AI Agents WorkIn simple terms, AI agents operate like advanced AI chatbots. They can handle tasks such as generating reports, optimizing media budgets, or analyzing data. According to Tyler Pietz, CEO and founder of Anthrologic, “They can basically do anything that a human can do on a computer.” Big players like Salesforce, Microsoft, Anthropic, Google, and Perplexity are also championing AI agents. Perplexity’s CEO, Aravind Srinivas, recently suggested that businesses will soon compete for the attention of AI agents rather than human customers. “Brands need to get comfortable doing this,” he remarked to The Economic Times. AI Agents Tailored for Advertisers Both Adaly and Anthrologic have developed AI software specifically trained for advertising tasks. Built on large language models like ChatGPT, these platforms respond to voice and text prompts. Advertisers can train these AI systems on internal data to automate tasks like identifying data discrepancies or analyzing economic impacts on regional ad budgets. Pietz noted that an AI agent can be set up in about a month and take on grunt work like scouring spreadsheets for specific figures. “Marketers still log into 15 different platforms daily,” said Kyle Csik, co-founder of Adaly. “When brands in-house talent, they often hire people to manage systems rather than think strategically. AI agents can take on repetitive tasks, leaving room for higher-level work.” Both Pietz and Csik bring agency experience to their ventures, having crossed paths at MediaMonks. Industry Response: Collaboration, Not Replacement The targets for these tools differ: Adaly focuses on independent agencies and brands, while Anthrologic is honing in on larger brands. Meanwhile, major holding companies like Omnicom and Dentsu are building their own AI agents. Omnicom, on the verge of merging with IPG, has developed internal AI solutions, while Dentsu has partnered with Microsoft to create tools like Dentsu DALL-E and Dentsu-GPT. Havas is also developing its own AI agent, according to Chief Activation Officer Mike Bregman. Bregman believes AI tools won’t immediately threaten agency jobs. “Agencies have a lot of specialization that machines can’t replace today,” he said. “They can streamline processes, but

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February 28, 2025in AI Tools, Artificial Intelligence, Data, Generative AI, Google, Laws, Salesforce, Technology
The Coalition for Sustainable AI
28Feb

The Coalition for Sustainable AI

The Coalition for Sustainable AI: Aligning AI Development with Environmental Responsibility The rapid rise of artificial intelligence (AI) presents both groundbreaking opportunities and significant environmental challenges. Recognizing the need for responsible AI development, France, the United Nations Environment Programme (UNEP), and the International Telecommunication Union (ITU) have established the Coalition for Sustainable AI—a global, multi-stakeholder initiative dedicated to ensuring AI supports sustainability rather than exacerbating environmental harm. A Shared Vision for Sustainable AI The Coalition for Sustainable AI, launched at the Paris AI Action Summit 2025, brings together public and private sector leaders to align AI advancements with environmental goals. The initiative seeks to: Why This Coalition Matters As AI infrastructure becomes as fundamental as water, energy, and transport, its environmental implications must be addressed proactively. AI technologies have the potential to redefine entire industries—just as the Industrial Revolution once did—while offering unprecedented capabilities to tackle climate change, optimize resource management, and enhance environmental decision-making. By bringing together a diverse network of stakeholders, the Coalition recognizes that the digital and AI revolution and the environmental crisis are two defining challenges of our time. Mission and Leadership The Coalition operates under two core principles: Founding Leaders: Driving Global Collaboration The Coalition’s role extends beyond advocacy. It serves as a platform to: This initiative will also maintain momentum through major global forums such as AI Summits, COP conferences, and other international policy discussions, ensuring AI remains at the forefront of sustainability efforts. Industry Leaders Join the Movement The Coalition for Sustainable AI has already attracted a diverse group of corporations, research institutions, NGOs, investors, and public sector organizations committed to this mission. Corporate Members Include: Salesforce, Nvidia, IBM, Hugging Face, Capgemini, Thales, Schneider Electric, Philips, TotalEnergies, Baidu, Orange, L’Oréal Groupe, Mistral AI, AMD, Dassault Systèmes, and more. Research Institutions and NGOs: Stockholm Environment Institute, Mila, Vrije Universiteit Amsterdam, Università di Pavia, Climate Change AI, The Shift Project, Royal Academy of Engineering, and others. Investors and Public Sector Representatives: Ardian, Crédit Agricole, Eurazeo, Mirova, BPI France, the Republic of Serbia’s Ministry of Science, and more. Salesforce’s Commitment to AI Sustainability Boris Gamazaychikov, Head of AI Sustainability at Salesforce, emphasized the importance of this initiative, stating: “I’m proud that Salesforce is one of the initial members, and I hope that many more join on this critical journey. Thanks to the French Government, UNEP, and ITU for organizing this important initiative.” Looking Ahead: The Future of Sustainable AI The Coalition for Sustainable AI marks a critical step toward ensuring that AI serves as a force for climate action, biodiversity preservation, and sustainable development. As AI continues to reshape the global economy, initiatives like this will help balance technological progress with environmental responsibility. With momentum building and more organizations joining the effort, the Coalition aims to drive lasting impact—paving the way for a future where AI and sustainability go hand in hand. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 28, 2025in Artificial Intelligence
The Rise of AI Agents: 2024 and Beyond
28Feb

The Rise of AI Agents: 2024 and Beyond

In 2024, we witnessed major breakthroughs in AI agents. OpenAI’s o1 and o3 models demonstrated the ability to deconstruct complex tasks, while Claude 3.5 showcased AI’s capacity to interact with computers like humans—navigating interfaces and running software. These advancements, alongside improvements in memory and learning systems, are pushing AI beyond simple chat interactions into the realm of autonomous systems. AI agents are already making an impact in specialized fields, including legal analysis, scientific research, and technical support. While they excel in structured environments with defined rules, they still struggle with unpredictable scenarios and open-ended challenges. Their success rates drop significantly when handling exceptions or adapting to dynamic conditions. The field is evolving from conversational AI to intelligent systems capable of reasoning and independent action. Each step forward demands greater computational power and introduces new technical challenges. This article explores how AI agents function, their current capabilities, and the infrastructure required to ensure their reliability. What is an AI Agent? An AI agent is a system designed to reason through problems, plan solutions, and execute tasks using external tools. Unlike traditional AI models that simply respond to prompts, agents possess: Understanding the shift from passive responders to autonomous agents is key to grasping the opportunities and challenges ahead. Let’s explore the breakthroughs that have fueled this transformation. 2024’s Key Breakthroughs OpenAI o3’s High Score on the ARC-AGI Benchmark Three pivotal advancements in 2024 set the stage for autonomous AI agents: AI Agents in Action These capabilities are already yielding practical applications. As Reid Hoffman observed, we are seeing the emergence of specialized AI agents that extend human capabilities across various industries: Recent research from Sierra highlights the rapid maturation of these systems. AI agents are transitioning from experimental prototypes to real-world deployment, capable of handling complex business rules while engaging in natural conversations. The Road Ahead: Key Questions As AI agents continue to evolve, three critical questions for us all emerge: The next wave of AI innovation will be defined by how well we address these challenges. By building robust systems that balance autonomy with oversight, we can unlock the full potential of AI agents in the years ahead. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 28, 2025in AI Tools
Agentforce Redefines Generative AI
27Feb

Agentforce and Commerce Cloud

SharkNinja, a global product design and technology company, is implementing Salesforce’s Agentforce and Commerce Cloud to enhance its global customer service operations. The company, known for its Shark and Ninja brands of household products, aims to scale support across more than 30 markets using autonomous agents. Agentforce will create an AI-powered digital workforce available 24/7 to assist customers with buying processes, product inquiries, troubleshooting, and returns management. This implementation will allow human agents to focus on high-impact interactions while providing tailored support based on customer data and purchase history. The integration of Commerce Cloud will enable SharkNinja to consolidate customer data from multiple sources into a unified view, facilitating more personalized shopping experiences and better tracking of customer engagement across their global customer base. Salesforce (NYSE: CRM), the world’s #1 AI CRM, today announced that SharkNinja, a global product design and technology company, is implementing Agentforce and other Salesforce products, including Commerce Cloud, to drive global growth by scaling its personalized customer service approach with autonomous agents. SharkNinja is a global leader in indoor and outdoor household products, transforming how people cook, clean, and live in homes around the world. As the innovation powerhouse behind two multi-billion-dollar brands — Shark and Ninja — SharkNinja is renowned for its diversified portfolio of cutting-edge products, including Shark vacuum cleaners and beauty tools, as well as Ninja kitchen appliances, such as blenders, air fryers, and ice cream makers. To support its rapid, global growth, SharkNinja is embracing solutions that will scale support and service more efficiently across more than 30 markets while delivering a seamless consumer shopping experience. Agentforce, a new layer on the Salesforce Platform, will enable SharkNinja to easily build and deploy AI agents that can autonomously take action across any business function. With Agentforce, SharkNinja will have an always-on, digital workforce available 24/7 to guide customers through the buying process, answer product questions, troubleshoot issues, and manage returns — streamlining human agent workloads so they can focus on meaningful, high-impact interactions. “Innovation is the driver behind every product SharkNinja creates across our vast portfolio, so it was really important to find a tool that could give us the capabilities needed to be just as innovative across every consumer interaction,” said Velia Carboni, CIO, SharkNinja. “We believe Agentforce is this key to helping us build a community that keeps consumers coming back as we continue to grow and develop new problem-solving innovations that positively impact people’s lives in homes around the world.” “SharkNinja prioritizes quality, innovation, and an exceptional customer experience,” said Adam Evans, EVP & GM of Salesforce AI Platform. “By integrating customer data with service and support functions, Agentforce enables SharkNinja to deliver an exceptional experience at every touchpoint — building customer loyalty and keeping them coming back time and time again.” Agentforce will also help SharkNinja enhance brand loyalty through tailored support interactions that deliver targeted solutions and recommendations based on insights from customer data from previous purchases and service history. SharkNinja will also leverage Commerce Cloud, enabling the company to consolidate customer data from multiple sources into a single, unified view. This integration will enable the delivery of more personalized shopping experiences for each customer. At the same time, having unified touchpoints will allow SharkNinja to more effectively track engagement across its global customer base. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 27, 2025in Agentforce Platform, Data, Salesforce, Salesforce Commerce Cloud, Technology
Make Forecasting Your Competitive Advantage
27Feb

Make Forecasting Your Competitive Advantage

Tired of Guessing Your Sales Pipeline? Make Forecasting Your Competitive Advantage Does forecasting your sales pipeline feel like more guesswork than strategy? You’re not alone. But what if you could transform your sales forecasts into a dependable guide for closing more deals? That’s exactly what Salesforce Forecasting Tools can do. Tectonic is your Salesforce partner for forecasting success! Why Salesforce Forecasting Stands Out Salesforce’s forecasting tools provide clarity, accuracy, and actionable insights to help you make smarter decisions. Here’s what makes them so powerful: Customizable Forecast Categories – Organize your pipeline into meaningful stages like “Pipeline,” “Best Case,” and “Committed” to match your sales process. Real-Time Updates – Stay on top of changes as opportunities progress. When a deal moves to “Closed Won,” your forecast reflects it instantly. Team Collaboration – Managers can fine-tune forecasts with input from their team, ensuring accuracy while maintaining transparency. How Forecasting Helps You Close More Deals Sales forecasting isn’t just about tracking numbers—it’s about taking action where it matters most. Here’s how: 🔹 Prioritize High-Value Deals – Filter opportunities based on their likelihood to close, so your team focuses on the deals with the highest probability of success. 🔹 Spot Risks Before They Derail Deals – Identify stalled opportunities early and take proactive steps to reengage prospects or remove roadblocks. 🔹 Empower Your Sales Reps – Give your team clear, achievable targets. A well-defined forecast removes guesswork and motivates reps to hit their goals. 🔹 Improve Customer Relationships – Forecasting helps you anticipate deal closings, so you can time follow-ups perfectly and keep customers engaged. Quick Tips to Master Salesforce Forecasting Leverage Historical Data – Use past trends to make more accurate sales projections.Customize Your Forecast Layouts – Align forecasting views with your unique sales stages for instant insights.Encourage Team Participation – Regular updates from sales reps lead to more reliable forecasts.Tap Into AI with Einstein Forecasting – Unlock predictive insights by letting AI analyze sales patterns and trends. Take Control of Your Sales Pipeline Whether you’re refining your current forecasting process or just getting started, now is the time to take action. Begin by reviewing your pipeline or explore advanced AI-driven forecasting. Need expert guidance? Contact us today! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 27, 2025in Data, Salesforce
is it real or is it gen-r-x
27Feb

Is it Real or is it Gen-r-X?

The Rise of AI-Generated Content: A Double-Edged Sword It began with a viral deepfake video of a celebrity singing an unexpected tune. Soon, political figures appeared to say things they never uttered. Before long, hyper-realistic AI-generated content flooded the internet, blurring the line between reality and fabrication. While AI-driven creativity unlocks endless possibilities, it also raises an urgent question: How can society discern truth in an era where anything can be convincingly fabricated? Enter SynthID, Google DeepMind’s pioneering solution designed to embed imperceptible watermarks into AI-generated images, offering a reliable method to verify authenticity. What Is SynthID, and Why Does It Matter? At its core, SynthID is an AI-powered watermarking tool that embeds and detects digital signatures in AI-generated images. Unlike traditional watermarks, which can be removed or altered, SynthID’s markers are nearly invisible to the human eye but detectable by specialized AI models. This innovation represents a significant step in combating AI-generated misinformation while preserving the integrity of creative AI applications. How SynthID Works SynthID’s technology operates in two critical phases: This method ensures that even if an image is slightly edited, resized, or filtered, the SynthID watermark remains intact—making it far more resilient than conventional watermarking techniques. SynthID for AI-Generated Text Large language models (LLMs) generate text one token at a time, where each token may represent a single character, word, or part of a phrase. The model predicts the next most likely token based on preceding words and probability scores assigned to potential options. For example, given the phrase “My favorite tropical fruits are __,” an LLM might predict tokens like “mango,” “lychee,” “papaya,” or “durian.” Each token receives a probability score. When multiple viable options exist, SynthID can adjust these probability scores—without compromising output quality—to embed a detectable signature. (Source: DeepMind) SynthID for AI-Generated Music SynthID converts an audio waveform—a one-dimensional representation of sound—into a spectrogram, a two-dimensional visualization of frequency changes over time. The digital watermark is embedded into this spectrogram before being converted back into an audio waveform. This process leverages audio properties to ensure the watermark remains inaudible to humans, preserving the listening experience. The watermark is robust against common modifications such as noise additions, MP3 compression, or tempo changes. SynthID can also scan audio tracks to detect watermarks at different points, helping determine if segments were generated by Lyria, Google’s advanced AI music model. (Source: DeepMind) The Urgent Need for Digital Watermarking in AI AI-generated content is already disrupting multiple industries: In this chaotic landscape, SynthID serves as a digital signature of truth, offering journalists, artists, regulators, and tech companies a crucial tool for transparency. Real-World Impact: How SynthID Is Being Used Today SynthID is already integrated into Google’s Imagen, a text-to-image AI model, and is being tested across industries: By embedding SynthID into digital content pipelines, these industries are fostering an ecosystem where AI-generated media is traceable, reducing misinformation risks. Challenges & Limitations: Is SynthID Foolproof? While groundbreaking, SynthID is not without challenges: Despite these limitations, SynthID lays the foundation for a future where AI-generated content can be reliably traced. The Future of AI Content Verification Google DeepMind’s SynthID is just the beginning. The battle against AI-generated misinformation may involve: As AI reshapes the digital world, tools like SynthID ensure innovation does not come at the cost of authenticity. The Thin Line Between Trust & Deception AI is a powerful tool, but without safeguards, it can become a weapon of misinformation. SynthID represents a bold step toward transparency, helping society navigate the blurred boundaries between real and artificial content. As the technology evolves, businesses, policymakers, and users must embrace solutions like SynthID to ensure AI enhances reality rather than distorting it. The next time an AI-generated image appears, one might ask: Is it real, or does it carry the invisible signature of SynthID? Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 27, 2025in AI Tools, Artificial Intelligence, Generative AI Tools, Google, Technology
The Future of AI in Salesforce
27Feb

The Future of AI in Salesforce

The Future of AI in Salesforce: Smarter, Predictive, and Deeply Integrated Artificial Intelligence (AI) is revolutionizing the Salesforce ecosystem, reshaping customer interactions, automating workflows, and driving revenue growth. As we move into 2025 and beyond, AI within Salesforce will become even more intelligent, predictive, and seamlessly embedded across the platform. Let’s explore the key advancements defining the next era of AI in Salesforce. 1. Next-Gen Einstein AI: A Smarter CRM Assistant Salesforce Einstein continues to evolve, equipping businesses with powerful AI-driven capabilities: 2. AI-Powered Revenue Intelligence & Forecasting AI is transforming revenue intelligence, helping sales teams make data-driven decisions: 3. AI-Driven Sales & Service Automation AI-powered automation will streamline workflows and improve efficiency: 4. Hyper-Personalization with AI & Data Cloud Salesforce Data Cloud and AI will power personalized customer experiences at scale: 5. AI-Optimized Lead Generation & Marketing Automation AI will continue to enhance lead generation and marketing strategies: 6. AI & Low-Code/No-Code Innovation Salesforce is democratizing AI with accessible low-code and no-code tools: 7. Ethical AI & Governance: Building Trust in AI Salesforce remains committed to ethical, transparent, and bias-free AI: Conclusion As AI becomes deeply embedded in every Salesforce cloud, businesses will experience faster automation, smarter decision-making, and hyper-personalized customer engagement. From AI-powered sales forecasting to generative AI-driven content, the future of Salesforce AI is set to redefine CRM strategies in 2025 and beyond. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 27, 2025in AI Tools, Artificial Intelligence, Data, Generative AI, Marketing Automation, Salesforce, Salesforce Data Cloud, Salesforce Einstein
Salesforce Data Cloud
27Feb

Data Cloud March 2025 Release

Cross Cloud Updates for Data Cloud March 2025 Release Enhanced Marketing Cloud Integration Multi-Instance Event Routing Key Marketing Features: Expanded Data Sharing & Collaboration Real-Time Data Processing Event-Triggered Flows (Beta) Server-to-Server Connections Enterprise Tools Sandbox Migration External Data Connectivity Analytics & Security Key Details Feature Availability Editions Notes Multi-Instance Event Routing March 2025 Enterprise+ Action rules required 250-Object Data Shares March 2025 Enterprise+ AI/ML use cases Event-Triggered Flows March 2025 Enterprise+ Beta, add-on required This release delivers:✅ Precision marketing with cross-instance event routing✅ Scalable collaboration via expanded data sharing✅ Instant automation through real-time triggers Note: Beta features governed by Salesforce Beta Terms. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 27, 2025in Data, Enterprise, Google, Salesforce, Salesforce Data Cloud, Snowflake
Salesforce Lightning
27Feb

Salesforce Lightning vs. Classic

Salesforce Lightning vs. Classic: The 2025 Decision Guide The Critical Choice for Modern Businesses As Salesforce phases out Classic (no updates since 2023), Lightning emerges as the only future-proof option with AI, mobile optimization, and superior analytics. Here’s what you need to know to make the right decision. Key Differences at a Glance Feature Lightning (2015+) Classic (Legacy) Interface Modern, component-based, drag-and-drop Text-heavy, tab-based Performance 50% faster load times, single-page app Slows with large datasets AI Integration Einstein AI for predictions & automation None Mobile Support Fully responsive design Limited functionality Customization Lightning App Builder, LWC components Rigid, requires coding (Visualforce) Security LockerService for component isolation Basic security protocols Analytics Interactive dashboards, real-time filters Static reports Why Lightning Dominates in 2025 1. Productivity Boost 2. AI-Powered Insights 3. Future-Proof Architecture 4. Cost Efficiency When Classic Might Still Work Consider Classic only if: Migration Made Simple Salesforce provides: The Verdict ✅ Choose Lightning if: You want AI, mobile access, and a scalable platform.⚠ Avoid Classic: It’s outdated, unsupported, and hampers growth. Next Steps: Pro Tip: Use Lightning Adoption Dashboards to track migration progress. Need help transitioning?  Contact Tectonic. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 27, 2025in Data, Marketing Automation, Public Sector Solutions, Salesforce Anywhere, Salesforce Development Services, Salesforce Education Solutions, Salesforce Financial Services Solutions, Salesforce for Nonprofits, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Technology
Granular Locking in Salesforce
26Feb

Granular Locking in Salesforce

Granular Locking in Salesforce: Enhancing Performance & Reducing Contention Granular locking in Salesforce is a powerful feature designed to minimize record lock contention, particularly in high-data-volume environments or those with complex automation processes. By refining traditional locking constraints, this mechanism allows Salesforce to manage simultaneous updates more efficiently, improving system performance and reducing errors. What is Granular Locking? Granular locking is an advanced record-locking mechanism that applies locks at a more detailed level, preventing unnecessary locking of parent or related records. This is especially useful in scenarios where multiple records are updated concurrently, reducing row lock contention in parent-child relationships. Key Features: ✅ Fine-Grained Locks – Prevents excessive locking of parent or related records.✅ Enhanced Concurrency – Allows multiple simultaneous updates to child records without conflicts.✅ Improved Performance – Minimizes errors like “Unable to lock row” by reducing contention. Why is Granular Locking Important? 1️⃣ Concurrent Record Updates 2️⃣ Optimized Automation 3️⃣ Scaling High-Volume Transactions How Granular Locking Works Granular locking ensures that:🔹 Parent records remain unlocked when child records are updated.🔹 Locks apply only to the specific records being modified instead of affecting entire datasets. Example: 🚫 Without Granular Locking: Updating an Opportunity record locks the parent Account and all related child records.✅ With Granular Locking: Only the specific Opportunity record is locked, allowing the Account and other child records to remain accessible. When Does Granular Locking Apply? 🔹 Master-Detail Relationships – Prevents parent records from being unnecessarily locked during child record updates.🔹 Campaign Hierarchies – Ensures that updates to child campaigns don’t lock parent campaigns.🔹 Sharing Recalculations – Reduces locking issues when Salesforce recalculates sharing rules for parent-child data relationships. Benefits of Granular Locking 🚀 Reduced Lock Contention – Minimizes conflicts in multi-user environments.📉 Fewer Errors – Decreases “Unable to obtain exclusive access to this record” errors.⚡ Faster Automation – Improves workflow and trigger execution speed.📊 Better Scalability – Enhances performance in high-transaction environments. Best Practices for Using Granular Locking ✅ Optimize Relationship Design: Avoid complex parent-child structures that could lead to unnecessary locking.✅ Minimize Simultaneous Updates: Reduce concurrent updates on the same parent record.✅ Use Asynchronous Processing: Implement Batch Apex or Queueable Apex for large data operations.✅ Test in High-Volume Scenarios: Simulate real-world data loads in a sandbox environment.✅ Monitor Locking Issues: Use debug logs and Event Monitoring to track and resolve locking conflicts. Common Issues & Solutions ❌ Error: “Unable to Lock Row”🔹 Cause: Simultaneous updates to related records.🔹 Solution: Redesign workflows or use asynchronous processing to reduce contention. ❌ Slow Performance in Campaign Updates🔹 Cause: Hierarchical campaign relationships triggering excessive locks.🔹 Solution: Ensure campaigns are structured to take advantage of granular locking. ❌ Automation Conflicts🔹 Cause: Multiple automation tools acting on the same records.🔹 Solution: Consolidate triggers and workflows to minimize overlaps. How to Enable Granular Locking for Campaign Hierarchies Although granular locking is enabled by default for most Salesforce operations, certain features (like hierarchical campaign locking) require manual activation. 🔹 Steps to Enable Granular Locking in Campaign Hierarchies:1️⃣ Navigate to Setup.2️⃣ Go to Campaign Settings.3️⃣ Check the box for Enable Improved Campaign Management (Granular Locking).4️⃣ Save your changes. Conclusion Granular locking is a vital feature in Salesforce that optimizes record management by reducing contention, minimizing errors, and improving system performance in high-transaction environments. By implementing best practices and leveraging fine-grained locks, organizations can scale efficiently while ensuring smooth automation and record updates. For teams handling complex data relationships, granular locking provides the flexibility, scalability, and reliability needed to maintain a high-performing Salesforce environment. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 26, 2025in Data, Salesforce

Data Cloud Billable Usage

Data Cloud Billable Usage Overview Usage of certain Data Cloud features impacts credit consumption. To track usage, access your Digital Wallet within your Salesforce org. For specific billing details, refer to your contract or contact your Account Executive. Important Notes ⚠️ Customer Data Platform (CDP) Licensing – If your Data Cloud org operates under a CDP license, refer to Customer Data Platform Billable Usage Calculations instead.⚠️ Sandbox Usage – Data Cloud sandbox consumption affects credits, with usage tracked separately on Data Cloud sandbox cards. Understanding Usage Calculations Credit consumption is based on the number of units used multiplied by the multiplier on the rate card for that usage type. Consumption is categorized as follows: 1. Data Service Usage Service usage is measured by records processed, queried, or analyzed. Billing Category Description Batch Data Pipeline Based on the volume of batch data processed via Data Cloud data streams. Batch Data Transforms Measured by the higher of rows read vs. rows written. Incremental transforms only count changed rows after the first run. Batch Profile Unification Based on source profiles processed by an identity resolution ruleset. After the first run, only new/modified profiles are counted. Batch Calculated Insights Based on the number of records in underlying objects used to generate Calculated Insights. Data Queries Based on records processed, which depends on query structure and total records in the queried objects. Unstructured Data Processed Measured by the amount of unstructured data (PDFs, audio/video files) processed. Streaming Data Pipeline Based on records ingested through real-time data streams (web, mobile, streaming ingestion API). Streaming Data Transforms Measured by the number of records processed in real-time transformations. Streaming Calculated Insights Usage is based on the number of records processed in streaming insights calculations. Streaming Actions (including lookups) Measured by the number of records processed in data lookups and enrichments. Inferences Based on predictive AI model usage, including one prediction, prescriptions, and top predictors. Applies to internal (Einstein AI) and external (BYOM) models. Data Share Rows Shared (Data Out) Based on the new/changed records processed for data sharing. Data Federation or Sharing Rows Accessed Based on records returned from external data sources. Only cross-region/cross-cloud queries consume credits. Sub-second Real-Time Events & API Based on profile events, engagement events, and API calls in real-time processing. Private Connect Data Processed Measured by GB of data transferred via private network routes. 🔹 Retired Billing Categories: Accelerated Data Queries and Real-Time Profile API (no longer billed after August 16, 2024). 2. Data Storage Allocation Storage usage applies to Data Cloud, Data Cloud for Marketing, and Data Cloud for Tableau. Billing Category Description Storage Beyond Allocation Measured by data storage exceeding your allocated limit. 3. Data Spaces Billing Category Description Data Spaces Usage is based on the number of data spaces beyond the default allocation. 4. Segmentation & Activation Usage applies to Data Cloud for Marketing customers and is based on records processed, queried, or activated. Billing Category Description Segmentation Based on the number of records processed for segmentation. Batch Activations Measured by records processed for batch activations. Activate DMO – Streaming Based on new/updated records in the Data Model Object (DMO) during an activation. If a data graph is used, the count is doubled. 5. Ad Audiences Service Usage Usage is calculated based on the number of ad audience targets created. Billing Category Description Ad Audiences Measured by the number of ad audience targets generated. 6. Data Cloud Real-Time Profile Real-time service usage is based on the number of records associated with real-time data graphs. Billing Category Description Sub-second Real-Time Profiles & Entities Based on the unique real-time data graph records appearing in the cache during the billing month. Each unique record is counted only once, even if it appears multiple times. 📌 Example: If a real-time data graph contains 10M cached records on day one, and 1M new records are added daily for 30 days, the total count would be 40M records. 7. Customer Data Platform (CDP) Billing Previously named Customer Data Platform orgs are billed based on contracted entitlements. Understanding these calculations can help optimize data management and cost efficiency. Track & Manage Your Usage 🔹 Digital Wallet – Monitor Data Cloud consumption across all categories.🔹 Feature & Usage Documentation – Review guidelines before activating features to optimize cost.🔹 Account Executive Consultation – Contact your AE to understand credit consumption and scalability options. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 26, 2025in Data, Salesforce, Salesforce Data Cloud
Salesforce Unified Knowledge
26Feb

AI Through a Unified Platform

Maximizing AI Potential Through a Unified Platform In today’s interconnected business landscape, siloed teams are a thing of the past—especially for organizations aiming to harness the full power of AI. With businesses leveraging an average of 991 applications across various platforms, disconnected systems are all too common, resulting in suboptimal experiences for both employees and customers. A unified platform eliminates these barriers, enabling teams to collaborate effortlessly across departments. By centralizing data on one platform, organizations unlock AI’s true potential, delivering more meaningful and actionable results. But what does a unified platform approach look like? And how does it enable AI agents to transform business processes? Let’s dive in. How AI Agents Perform Better on Unified Platforms Traditional rule-based systems often bombard teams with irrelevant updates triggered by static field values, causing critical information to be overlooked. By contrast, AI agents, guided by human-defined frameworks, operate based on context rather than rigid rules, making them more effective at managing complex workflows. However, for AI agents to succeed, they require seamless access to data and systems. Without a unified platform, they can’t function cohesively across departments. This is where Salesforce’s platform approach stands out—it allows businesses to create both custom and out-of-the-box AI solutions that integrate effortlessly, thanks to a shared metadata foundation. Real-World AI Applications: Smarter Hiring with AI Agents Let’s consider a scenario where a company builds a custom AI agent for its recruiting app to streamline hiring: This approach highlights the value of connecting systems. By enabling seamless data sharing across HR, Legal, and Finance, the AI agent ensures an efficient, collaborative hiring process. Unlike rule-based automation, which follows rigid “if-then” logic, AI agents incorporate context and intelligence into workflows. This makes them more adaptive and impactful, driving real results for businesses. Extending AI’s Reach with Platform Login Licenses While AI agents can transform workflows, not every team member needs full-time access to them. Some employees use these tools daily, while others engage with them occasionally. Platform Login Licenses offer a cost-effective solution by granting temporary, on-demand access. For instance, an employee eligible for a referral bonus might only need to check the HR platform occasionally to track their status. A Platform Login License lets them interact with the AI agent when necessary, without requiring a full-time account. This flexibility ensures companies can extend AI-driven productivity to more users without overspending on unused licenses. Why a Unified Platform Is Essential Salesforce’s unified platform provides the consistency and scalability organizations need, whether using custom-built AI agents or ready-made solutions. By sharing a common metadata foundation, these tools access richer data, leading to smarter decision-making and improved workflows. Seamless data flow between agents and apps enhances collaboration and unlocks the full potential of AI. Teams can work smarter, not harder, with tools tailored to their specific needs, whether they use them daily or occasionally. Start Building Your AI-Driven Future Today AI’s transformative potential lies not just in the technology but in the foundation it’s built upon. A unified platform equips businesses to create powerful, interconnected AI solutions that streamline processes and foster collaboration. With Salesforce’s Platform Login Licenses, you can extend the benefits of AI agents to the right people at the right time—without unnecessary costs. Discover AgentforceLearn how Agentforce AI agents provide continuous support to employees and customers, helping your organization succeed. Explore the Benefits Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 26, 2025in Data, Salesforce, Technology
salesforce service assistant
26Feb

Salesforce Service Assistant

Salesforce Service Assistant is an AI-powered tool that helps service representatives resolve cases faster. It’s available on Service Cloud and is designed to save time for agents. How it works Benefits Helps agents resolve cases faster, Saves time for service representatives, Grounded in the organization’s knowledge base and data, and Adheres to company policies. Additional information Alongside agent guidance, the Service Assistant provides two other notable features. The first enables agents to create conversation summaries with “just a click” after using the solution to complete a case. The second allows agents to request that the assistant auto-crafts a new knowledge article when its guidance proved insufficient, based on how they resolved the query. Thanks to this second feature, the Service Assistant may get better with time, aiding agent proficiency, customer satisfaction, and – ultimately – average handling time (AHT). However, despite this capability, Salesforce has pledged to advance the solution further. Indeed, during a recent webinar, Kevin Qi, Associate Product Manager at Salesforce, teased what will come in June. Pointing to Service Cloud’s Summer ‘25 release wave, Qi said: The next phase of Service Assistant involves actionable plans. So, not only will it help guide the service rep, but it’ll also take actions to automate various steps, so it can look up orders, check eligibilities, and more to help speed up the efficiency of tackling that case. Beyond the summer, Salesforce plans to have the Assistant blend modalities, guiding customer conversations across channels to further streamline the interaction. “The Service Assistant will become even more adaptive, support more channels, including messaging and voice, being able to adapt to changes in case context,” concluded Qi. The Latest AI Solutions on Service Cloud Alongside the Service Assistant, Salesforce has released several other AI and Agentforce capabilities, embedded across Service Cloud. Qi picked out the “Freeform Instructions in Service Email Assistant” feature for special reference. “If the agent doesn’t have a template already made for a particular instance, they can type – in natural language – the sort of email they’d want to generate and have Agentforce create that email in the flow of work,” he said. That capability may prove highly beneficial in helping agents piece their thoughts together when resolving a tricky case. After all, they can note some key points – in natural language – and the feature will create a coherent customer response. Alongside this comes a solution to quickly summarize case activity for wrap-up in beta. Yet, most new features focus on improving the knowledge that feeds into AI solutions, like the Service Assistant. For starters, there’s a flow orchestrator in beta that helps contact center leaders build a process for approving new knowledge articles and updates. Additionally, there’s an “Update Knowledge Content with AI” feature. This ingests prompts and – as it says on the tin – updates the tone, style, and length of particular knowledge articles. Last comes the “Knowledge Sync to Data Cloud” tool that pulls contact center knowledge into the Salesforce customer data platform (CDP). Not only does this democratize service insights, but it also supports contact centers in grounding the Service Assistant and other AI agents. Both of these final knowledge capabilities are now generally available. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 26, 2025in Data, Salesforce

Five9 Deepens Salesforce Partnership

Five9 Deepens Salesforce Partnership to Advance AI-Powered Contact Centers Five9 is strengthening its collaboration with Salesforce to help mutual customers streamline service environments and implement AI-powered agents that enhance customer interactions. A Strategic Partnership in AI & Customer Service The announcement comes as Five9 celebrates a 17% year-over-year (YoY) revenue growth, with Chairman & CEO Mike Burkland crediting the company’s expanding partner network for driving success. While acknowledging partnerships with Microsoft, Google, ServiceNow, and Verint, Burkland highlighted Five9’s deepening relationship with Salesforce, emphasizing: “Salesforce and Five9 share a vision where AI agents and human agents work together to elevate customer experiences.” A key focus of this partnership is enhancing integration between Five9 and Agentforce, Salesforce’s platform for autonomous AI agents. This marks the first CCaaS vendor integration with Agentforce, opening up new opportunities for intelligent, industry-specific AI applications. Industry-Specific AI Agents: A Game Changer By embedding Agentforce capabilities within the Five9-Salesforce CCaaS-CRM ecosystem, businesses can automate critical customer service workflows. Some examples include: These are just a few use cases demonstrating how AI-driven automation can transform customer engagement across industries. CCaaS vs. CRM: Who Will Lead AI in Contact Centers? As AI reshapes customer service, industry analysts have questioned whether businesses will favor their CRM provider over their CCaaS vendor for AI-driven automation. Burkland dismissed this as a false choice, explaining: “It’s going to be a mix. Even if an organization chooses Salesforce for their AI, they still need access to all the contextual data in our platform. Salesforce knows they need us, and we welcome that relationship. Our goal is to do what’s best for the customer.” The Future of AI-Powered Customer Engagement By deepening its Salesforce integration and leading the way in AI-driven service automation, Five9 is positioning itself as a key player in the evolution of intelligent contact centers. As businesses increasingly seek to blend human expertise with AI efficiency, this partnership paves the way for seamless, personalized, and automated customer experiences at scale. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 26, 2025in Data, Google, Salesforce

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