Knowledge - gettectonic.com - Page 10
Nature Tech Alliance
10Jun

Nature Tech Alliance

Exciting news! We are thrilled to introduce the Nature Tech Alliance, a groundbreaking initiative aimed at assisting companies in addressing pressing biodiversity challenges. Leading the charge are Planet, ERM, Salesforce, and NatureMetrics, joining forces to revolutionize how global corporations assess and manage their impact on nature. Alliance will focus on biodiversity measurement, management and disclosure, supporting businesses to get ahead of their nature impact reporting commitments. Formed during the World Economic Forum Annual Meeting in Davos, 2024, the Nature Tech Alliance is dedicated to expediting and expanding the evaluation, management, and disclosure of biodiversity impacts and dependencies on nature. Our goal is to drive a sustainable future for nature, people, and economies by providing companies with the tools and insights they need to understand and mitigate their impact on the environment. Through this alliance, companies will gain a comprehensive understanding of their business’s impact on nature and prepare to comply with new and forthcoming nature regulations and frameworks. This includes initiatives such as the Taskforce on Nature-related Financial Disclosures and the Corporate Sustainability Reporting Directive. At Planet, we are collaborating with other members of the alliance to provide industries with data-driven insights. Leveraging our satellite data and analytics alongside the expertise and tools of our partners, we are developing an integrated toolkit for biodiversity assessment. This toolkit will assist in value chain assessments, supplier engagement, and meeting reporting and compliance requirements. The powerful alliance will help businesses to overcome the common challenges faced in managing biodiversity integrity across industries. It will provide an integrated toolkit for biodiversity management and disclosure, including: Each member of the alliance brings unique knowledge and critical competencies to the table. ERM provides sustainability consulting and global delivery capabilities, Salesforce offers powerful technology solutions such as Net Zero Cloud, and NatureMetrics contributes its eDNA technology and on-the-ground biodiversity measurement expertise. Citizens of the planet are excited about the future of biodiversity and the opportunities for collaboration within this alliance. Thought leaders from each organization share their perspectives: Andrew Zolli, Chief Impact Officer at Planet: “We are at a pivotal moment in history where we have the technology and tools to quantify, monitor, and value our biodiversity. True collaboration is the next step, and we are thrilled to be part of this alliance to monitor and protect our world.” Matt Haddon, Global Leader for Biodiversity, Water & Nature at ERM: “By combining our capabilities, we can help organizations understand their nature-based risks and dependencies, enabling them to integrate nature into their business strategies and operations.” Tim Christophersen, VP, Climate Action at Salesforce: “To accelerate a successful transition to a net-zero and nature-positive future, businesses must measure, manage, and disclose their impact and reliance on nature. We are proud to form the Nature Tech Alliance and leverage our technologies to help other companies make a positive impact.” Dr. Kat Bruce, Founder of NatureMetrics: “This collaboration will provide full-spectrum biodiversity measurement, management, and disclosure for global corporations. Collaborations like this are critical for implementing solutions at scale and translating talk into real action on the ground.” About ERM As the world’s largest specialist sustainability consultancy, ERM partners with clients to operationalize sustainability at pace and scale, deploying a unique combination of strategic transformation and technical delivery capabilities. This approach helps clients to accelerate the integration of sustainability at every level of their business. With more than 50 years of experience, ERM’s diverse team of 8000+ experts in 40 countries and territories helps clients create innovative solutions to their sustainability challenges, unlocking commercial opportunities that meet the needs of today while preserving opportunity for future generations. Learn more here. About NatureMetrics NatureMetrics is a world leader in delivering nature data and intelligence. It uses cutting-edge technology to generate biodiversity data at scale using environmental DNA. NatureMetrics recently launched the world’s first Nature Intelligence Platform powered by eDNA, bringing a scalable solution to biodiversity monitoring, equipping businesses for the new nature reporting boom. NatureMetrics works with 500 plus clients in over 100 countries across a wide range of industries, including energy, extractives, food and drink, and financial services, helping them to get ahead of the emerging nature and biodiversity regulatory landscape. Visit: www.naturemetrics.com 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
June 10, 2024in Salesforce
Five9 Salesforce AI Integration
05Jun

Five9 Salesforce AI Integration

Five9 and Salesforce Enhance AI-Powered Solutions for Superior Customer Experiences Five9 (NASDAQ: FIVN), a provider of the Intelligent CX Platform, today announced the next step in its collaboration with Salesforce. Five9 Salesforce AI Integration. This partnership aims to deliver AI-powered solutions to enhance customer experiences (CX) in contact centers. The latest release, Five9 for Service Cloud Voice with Partner Telephony, integrates Salesforce Einstein with Five9’s suite of AI solutions. This empowers agents to better service customer requests, improves management’s understanding of contact center operations, and delivers customer resolutions that exceed expectations. Using Five9’s open APIs and Five9 TranscriptStream, the Einstein AI engine identifies opportunities to provide real-time solutions for agents, prompting ‘Next Best Action’ guidance. The solution also offers real-time transcription of customer conversations, ensures call recordings’ accuracy and relevance, and integrates with Salesforce Einstein Conversation Insights to enhance conversation intelligence. “Five9 understands the power of elevating the customer experience through innovative technology and seamless integrations,” said Dan Burkland, President of Five9. “Our collaboration with Salesforce pushes the boundaries of what is possible. Infusing Einstein’s AI insights into the contact center and CRM eliminates repetitive tasks while guiding agents with the next best actions to help them be more effective.” A Long-Standing Partnership The Salesforce-Five9 collaboration, now over 15 years strong, recently introduced Five9 call dispositions for agents within the Salesforce Omni-Channel widget or Voice Call page. This allows organizations to automatically update call dispositions in the Five9 call database, ensuring accurate reporting across the integration. Both companies are meeting the growing demand for AI solutions to enhance customer engagement throughout the customer journey. “Five9’s deeper integration with Salesforce Einstein offers a new level of choice for customers seeking AI capabilities that best match their contact center needs and existing technology investments,” said Sheila McGee-Smith, President & Principal Analyst at McGee-Smith Analytics. “Coupled with features like Five9 TranscriptStream, organizations can significantly reduce an agent’s workload while enhancing the customer’s overall experience. This next step in the Salesforce-Five9 relationship demonstrates each company’s commitment to their joint customer base, enabling them to leverage the latest AI innovations easily.” “Service Cloud Voice with Five9 uses AI to deliver a better customer experience,” said Ryan Nichols, Chief Product Officer of Service Cloud, Salesforce. “Our collaboration focuses on more than just a ‘single pane of glass’– we’re bringing together customer data, knowledge, and real-time conversation transcripts to help make agents more productive and delight customers.” Availability and Further Information These new enhancements to Five9 for Service Cloud Voice with Partner Telephony will be available starting June 30. For a deeper look into the Five9 integration with Service Cloud Voice and to explore common use cases, register for the webinar “Unlock Efficiency with the Power of AI: Five9 and Salesforce Service Cloud Voice” on Tuesday, July 23. An on-demand playback of the December 2023 Five9 and Salesforce joint webinar is also available, covering topics such as using data for personalization, best practices for leveraging engagement data to improve experiences, and how companies can become more customer-centric. Salesforce, Einstein, and other related marks are trademarks of Salesforce, Inc. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
June 5, 2024in Salesforce, Salesforce Einstein, Salesforce Service Cloud

AI Agents

Lessons Learned in the First Year of Developing AI Agents In the first year of working on AI agents, valuable insights emerged from direct collaboration with engineers and UX designers, as they iterated on the overall product experience. The objective was to create a platform for customers to use standard data analysis agents and build custom agents tailored to specific tasks and data structures relevant to their business. This platform integrates connectors to databases like Snowflake and BigQuery with built-in security, supports RAG over a metadata layer describing database contents, and facilitates data analysis through SQL, Python, and data visualization tools. Feedback on the effectiveness of these developments came from both internal evaluations and customer insights. Users from Fortune 500 companies utilize these agents daily to analyze their internal data. Key Insights on AI Agents Additional Insights Further insights on code and infrastructure include: These lessons underscore the importance of focusing on reasoning, iterative improvements to the agent-computer interface, understanding model limitations, and building robust supporting infrastructure to enhance AI agent performance and user satisfaction. 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 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

Read More
June 4, 2024in Salesforce Einstein
RAG Chunking Method
01Jun

RAG Chunking Method

Enhancing Retrieval-Augmented Generation (RAG) Systems with Topic-Based Document Segmentation Dividing large documents into smaller, meaningful parts is crucial for the performance of Retrieval-Augmented Generation (RAG) systems. RAG Chunking Method. These systems benefit from frameworks that offer multiple document-splitting options. This Tectonic insight introduces an innovative approach that identifies topic changes using sentence embeddings, improving the subdivision process to create coherent topic-based sections. RAG Systems: An Overview A Retrieval-Augmented Generation (RAG) system combines retrieval-based and generation-based models to enhance output quality and relevance. It first retrieves relevant information from a large dataset based on an input query, then uses a transformer-based language model to generate a coherent and contextually appropriate response. This hybrid approach is particularly effective in complex or knowledge-intensive tasks. Standard Document Splitting Options Before diving into the new approach, let’s explore some standard document splitting methods using the LangChain framework, known for its robust support of various natural language processing (NLP) tasks. LangChain Framework: LangChain assists developers in applying large language models across NLP tasks, including document splitting. Here are key splitting methods available: Introducing a New Approach: Topic-Based Segmentation Segmenting large-scale documents into coherent topic-based sections poses significant challenges. Traditional methods often fail to detect subtle topic shifts accurately. This innovative approach, presented at the International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications (ACDSA 2024), addresses this issue using sentence embeddings. The Core Challenge Large documents often contain multiple topics. Conventional segmentation techniques struggle to identify precise topic transitions, leading to fragmented or overlapping sections. This method leverages Sentence-BERT (SBERT) to generate embeddings for individual sentences, which reflect changes in the vector space as topics shift. Approach Breakdown 1. Using Sentence Embeddings: 2. Calculating Gap Scores: 3. Smoothing: 4. Boundary Detection: 5. Clustering Segments: Algorithm Pseudocode Gap Score Calculation: pythonCopy code# Example pseudocode for gap score calculation def calculate_gap_scores(sentences, n): embeddings = [sbert.encode(sentence) for sentence in sentences] gap_scores = [] for i in range(len(sentences) – n): before = embeddings[i:i+n] after = embeddings[i+n:i+2*n] score = cosine_similarity(before, after) gap_scores.append(score) return gap_scores Gap Score Smoothing: pythonCopy code# Example pseudocode for smoothing gap scores def smooth_gap_scores(gap_scores, k): smoothed_scores = [] for i in range(len(gap_scores)): start = max(0, i – k) end = min(len(gap_scores), i + k + 1) smoothed_score = sum(gap_scores[start:end]) / (end – start) smoothed_scores.append(smoothed_score) return smoothed_scores Boundary Detection: pythonCopy code# Example pseudocode for boundary detection def detect_boundaries(smoothed_scores, c): boundaries = [] mean_score = sum(smoothed_scores) / len(smoothed_scores) std_dev = (sum((x – mean_score) ** 2 for x in smoothed_scores) / len(smoothed_scores)) ** 0.5 for i, score in enumerate(smoothed_scores): if score < mean_score – c * std_dev: boundaries.append(i) return boundaries Future Directions Potential areas for further research include: Conclusion This method combines traditional principles with advanced sentence embeddings, leveraging SBERT and sophisticated smoothing and clustering techniques. This approach offers a robust and efficient solution for accurate topic modeling in large documents, enhancing the performance of RAG systems by providing coherent and contextually relevant text sections. 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 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

Read More
June 1, 2024in Salesforce Einstein
Einstein Personalization and Copilots
30May

Einstein Personalization and Copilots

Salesforce launched a suite of new generative AI products at Connections in Chicago, including new Einstein Copilots for marketers and merchants, and Einstein Personalization. Einstein Personalization and Copilots To gain insights into these products and Salesforce’s evolving architecture, Bobby Jania, CMO of Marketing Cloud was interviewed. Salesforce’s Evolving Architecture Salesforce has a knack for introducing new names for its platforms and products, sometimes causing confusion about whether something is entirely new or simply rebranded. Reporters sought clarification on the Einstein 1 platform and its relationship to Salesforce Data Cloud. “Data Cloud is built on the Einstein 1 platform,” Jania explained. “Einstein 1 encompasses the entire Salesforce platform, including products like Sales Cloud and Service Cloud, continuing the original multi-tenant cloud concept.” Data Cloud, developed natively on Einstein 1, was the first product built on Hyperforce, Salesforce’s new cloud infrastructure. “From the start, Data Cloud has been able to connect to and read anything within Sales Cloud, Service Cloud, etc. Additionally, it can now handle both structured and unstructured data.” This marks significant progress from a few years ago when Salesforce’s platform comprised various acquisitions (like ExactTarget) that didn’t seamlessly integrate. Previously, data had to be moved between products, often resulting in duplicates. Now, Data Cloud serves as the central repository, with applications like Tableau, Commerce Cloud, Service Cloud, and Marketing Cloud all accessing the same operational customer profile without duplicating data. Salesforce customers can also import their own datasets into Data Cloud. “We wanted a federated data model,” Jania said. “If you’re using Snowflake, for example, we virtually sit on your data lake, providing value by forming comprehensive operational customer profiles.” Understanding Einstein Copilot “Copilot means having an assistant within the tool you’re using, contextually aware of your tasks and assisting you at every step,” Jania said. For marketers, this could start with a campaign brief created with Copilot’s help, identifying an audience, and developing content. “Einstein Studio is exciting because customers can create actions for Copilot that we hadn’t even envisioned.” Contrary to previous reports, there is only one Copilot, Einstein Copilot, with various use cases like marketing, merchants, and shoppers. “We use these names for clarity, but there’s just one Copilot. You can build your own use cases in addition to the ones we provide.” Marketers will need time to adapt to Copilot. “Adoption takes time,” Jania acknowledged. “This Connections event offers extensive hands-on training to help people use Data Cloud and these tools, beyond just demonstrations.” What’s New with Einstein Personalization Einstein Personalization is a real-time decision engine designed to choose the next best action or offer for customers. “What’s new is that it now runs natively on Data Cloud,” Jania explained. While many decision engines require a separate dataset, Einstein Personalization evaluates a customer holistically and recommends actions directly within Service Cloud, Sales Cloud, or Marketing Cloud. Ensuring Trust Connections presentations emphasized that while public LLMs like ChatGPT can be applied to customer data, none of this data is retained by the LLMs. This isn’t just a matter of agreements; it involves the Einstein Trust Layer. “All data passing through an LLM runs through our gateway. Personally identifiable information, such as credit card numbers or email addresses, is stripped out. The LLMs do not store the output; Salesforce retains it for auditing. Any output that returns through our gateway is logged, checked for toxicity, and only then is PII reinserted into the response. These measures ensure data safety beyond mere handshakes,” Jania said. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 30, 2024in Einstein 1 Platform, Generative AI, Hyperforce, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Snowflake
Securing SaaS
26May

Securing SaaS

Obsidian Security recently discussed the complexity of enforcing Single Sign-On (SSO) within Salesforce and frequently encountering misconfigurations. Notably, 60% of Obsidian’s customers initially have local access without Multi-Factor Authentication (MFA) configured for Salesforce, highlighting a significant security gap that Obsidian diligently works to secure. Securing SaaS. The Hidden Vulnerability Application owners who manage Salesforce daily often remain unaware of this misconfiguration. Despite their deep knowledge of Salesforce management, local access without MFA presents an overlooked vulnerability. This situation raises concerns about the security of other SaaS applications, especially those without developed expertise or knowledge. If you have concerns about your configuration, Tectonic can help. Attacker Focus and Trends Attackers have historically targeted the Identity Provider (IdP) space, focusing on providers like Okta, Microsoft Entra, and Ping. This strategy offers maximal impact, as compromising an IdP grants broad access across multiple applications. Developing expertise to breach a few IdPs is more efficient than learning the diverse local access pathways of numerous SaaS vendors. Over the past 12 months, nearly 100% of the breaches that required Obsidian’s intervention through CrowdStrike or other incident response partners were IdP-focused. Notably, 70% of these breaches involved subverting MFA, often through methods like SIM swapping. In instances where local access bypasses the IdP, 95% of the time it lacks MFA. Recent discussions around Snowflake have brought attention to “shadow authentication,” defined as unsanctioned means to authenticate a user within an application. Obsidian Security has observed an increase in brute force attacks against SaaS applications via local access pathways over the last two weeks, indicating a growing awareness of this attack vector. Future Expectations Attackers continually seek easy and efficient pathways. Over the next 12 months, local access or shadow authentication is expected to become a major attack vector. Organizations must proactively secure these pathways as attackers shift their focus. What You Can Do How Obsidian Helps Salesforce Security partners offers robust solutions to address these challenges: By leveraging partner capabilities, organizations can enhance their security posture, protecting against evolving threats targeting local access and shadow authentication. The post “The Growing Importance of Securing Local Access in SaaS Applications” appeared first on Obsidian Security. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 26, 2024in Salesforce, Salesforce Einstein, Snowflake
Copilot A Step Up For Merchandising
23May

Copilot A Step Up For Merchandising

A Leap Forward in Merchandising Merchants face the ongoing challenge of enhancing loyalty, conversion rates, and shopper lifetime value. Enter Einstein Copilot, ushering in automation to boost productivity and inject intelligence for an elevated customer experience in unprecedented ways. Salesforce asserts that early AI adopters are saving an average of 6.4 hours per week. Copilot A Step Up For Merchandising. Einstein Copilot empowers merchants to swiftly craft personalized product promotions to attract new customers and target slow-moving stock based on inventory insights. Additionally, it optimizes site traffic with search engine optimization (SEO) content, generates product descriptions, and enhances checkout conversion with AI recommendations tailored to specific objectives. Copilot A Step Up For Merchandising Prior to Einstein Copilot, other generative AI copilot solutions operated as separate applications, disconnected from the workflow, and lacked the ability to securely leverage trusted company data for generating relevant or consistent results from large language models. Einstein Copilot integrates seamlessly within the world’s leading AI CRM and harnesses data from any Salesforce application to deliver more precise AI-powered recommendations and content. Through natural language prompts, Einstein Copilot facilitates a range of tasks, including: Sales: Conducting account research, preparing for meetings, and automatically updating account information in Salesforce. Summarizing highlights, gauging customer sentiment, and extracting next steps from video calls. Searching for specific details in customer calls and auto-generating sales emails to match tone and style while aligning with customer context. Drafting clauses and embedding them directly within customer contracts. Service: Automatically responding to customers with personalized, relevant answers sourced from trusted company knowledge across various channels like email, SMS, live chat, or social media. Empowering service teams to resolve customer issues swiftly using generative answers integrated seamlessly into their workflow. Automating tasks like summarizing support cases and field work orders. Marketing: Generating email copy for marketing campaigns, refining campaign segmentation with Data Cloud, creating website landing pages based on personalized consumer preferences, and auto-populating contact forms with each customer’s unified profile in Salesforce. Generating surveys following online actions to enhance long-term engagement and purchasing. Commerce: Assisting in building high-converting digital storefronts, automating complex tasks like managing multi-product catalog data, crafting product descriptions in multiple languages, generating personalized product promotions, and optimizing SEO metadata for conversion. Customizing and designing storefront components using natural language prompts. Developers: Converting natural language prompts into Apex code, offering suggestions for more effective and accurate code, and proactively scanning for code vulnerabilities within the developer environment. Tableau: Transitioning swiftly from raw data to actionable insights through a conversational interface, enhancing data analyst productivity with a natural language assistant for faster data exploration, building relevant visualizations, automating repetitive tasks, and facilitating efficient data curation. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 23, 2024in Einstein 1 Platform, Generative AI, Salesforce
Generative AI and Service Cloud
23May

Generative AI and Service Cloud

Salesforce Service Cloud users are set to receive more Einstein 1 generative AI tools in June and October. A key development is the expansion of automated customer conversations across more sales and marketing platforms. Generative AI and Service Cloud family of tools is growing. This insight aims to uncover the numerous use cases of generative AI in the modern contact center. We’ll help you understand how generative AI can fast track your contact center’s efficiency, improve data analysis capabilities, streamline QA and coaching processes, and make customers’ experiences better.  Today, Salesforce launched Unified Conversations for WhatsApp, which automates bot responses to customer inquiries related to targeted marketing messages on the popular messaging app. Additionally, Salesforce plans to extend support to Line, a messaging app popular in Japan, later this year. These services are built on Salesforce’s Einstein 1 generative AI platform. The platform’s bots aggregate structured and unstructured CRM, product, service, and other data through Salesforce Data Cloud to generate personalized responses. These new features enable conversations to be routed to the digital channels where a Salesforce user’s customers are the most active. And to move omnichannel as customers needs change. Salesforce is also introducing a “bring your own channel” connector to support digital channels not natively covered by the platform. Current examples might include TikTok, Discord, and South Korea’s KakaoTalk, according to Ryan Nichols, Chief Product Officer for Salesforce Service Cloud. Generative AI and Service Cloud “It’s about getting data from all your conversations with customers from Service Cloud into Data Cloud and using that to not just deliver excellent customer service, but also grow your business,” Nichols said. Salesforce Einstein Conversation Mining, a Service Cloud feature currently in beta, aggregates conversations across customer channels to surface insights on the topics customers need help with. This aims to turn inbound customer service from a cost center into a revenue center, a goal long pursued at conferences like Dreamforce and ICMI. This massive change drives more than revenue, it drives ROI. Performance metrics such as time-to-answer and hold-time reduction have traditionally pressured agents to minimize call duration to retain their jobs. Now Salesforce is going to help them. While some skeptics question if generative AI can achieve this ambitious goal, Constellation Research analyst Liz Miller suggests it might be possible. Having previously managed a contact center herself, Miller recognizes the transformative potential of generative AI. With the aid of data, bots, and copilot counterparts assisting humans, agents could save time and access the right information to upsell customers during service engagements. Here are some of the ways Generative AI will change customer service forever. 1. Monitor and Ensure Compliance Maintaining compliance is crucial for fostering customer trust, preserving a positive brand image, and avoiding hefty privacy and compliance fines. In a contact center, compliance mistakes can quickly escalate into costly lawsuits and revenue losses. Generative AI allows your compliance team to proactively manage compliance by quickly identifying trends and addressing issues in real time. Instead of waiting for a compliance issue to escalate, you can fine-tune your AI model to provide compliance insights whenever necessary. For instance, you can ask: This approach offers more comprehensive insights than scorecards, which often lack context and accuracy. Generative AI’s analytical capabilities provide actionable insights to improve compliance across your contact center. 2. Get Insights About Your Call Center Performance at a Glance Generative AI language models make it easier than ever to gain insights into your contact center’s performance. Simply ask the model for the information you need. For example, you can inquire about the real-time average handling time (AHT) by asking, “What is the average handling time today?” But that’s just the beginning. With an advanced language model, you can compare metrics across different quarters or generate ideas for coaching plans by asking for each agent‘s strengths and weaknesses and suggestions for improvement. 3. Automate Post-Call Work Generative AI assistants can act as real-time notetakers, summarizing 100% of calls and freeing agents from manual note-taking. This automation makes after-call work effortless, generating comprehensive and compliant notes with a single click. 4. Capture Coachable Moments Easily Incorporating real-world coachable moments into your sessions is essential for tangible performance improvements. Generative AI can identify areas where agents typically struggle without requiring hours of call listening and note-checking. Traditional methods mean compromising on the specificity of coaching due to time constraints, especially when managing large teams. Generative AI solutions, however, enable call center managers to obtain detailed insights about each agent’s performance quickly. This allows for personalized coaching plans that address individual shortcomings efficiently. You can ask: 5. Improve Decision Making With Efficient Root-Cause Analysis Effective decision-making can transform your contact center. However, many managers struggle to identify the root causes of performance issues. Generative AI algorithms can analyze vast amounts of data and customer interactions, uncovering patterns and trends in customer and agent behavior. These insights help pinpoint the issues most impacting performance and customer satisfaction, allowing you to make informed decisions. The process is nearly fully automated, freeing your team from time-consuming data collection tasks. 6. Reduce Manual Work and Focus on Improvement Improving contact center performance requires extensive data, which is resource-intensive to collect manually. Generative AI simplifies this by analyzing customer interactions and providing actionable insights on demand. This saves time and money, allowing you to focus on improvements that deliver a higher ROI. 7. Scale What Works Discovering and scaling best practices is essential for team-wide success. Generative AI and Natural Language Processing (NLP) models can analyze customer interactions to identify effective strategies and coaching opportunities. For example, if a representative handles challenging situations well, AI can generate tips for other team members based on these successful interactions. Generative AI can identify top-performing agents and analyze their calls to extract best practices, providing a more comprehensive approach than focusing on a single agent. Queries you might use include: 8. Generate Agent Scripts Generative AI enables you to draft and fine-tune agent scripts for various customer interactions. Instead of relying

Read More
May 23, 2024in Generative AI, Salesforce Data Cloud, Salesforce Einstein, Salesforce Service Cloud
Salesforce Summer 24 Service Release
20May

Salesforce Summer 24 Service Release

Service Salesforce Summer 24 Service Release. Check out new features that enable customer service agents to work faster and more productively across customer service channels. Salesforce Summer 24 Service Release 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 20, 2024in Salesforce Service Cloud, Unified Knowledge
Use Cases for Retrieval-Augmented Generation
19May

Use Cases for Retrieval-Augmented Generation

The applications of Retrieval-Augmented Generation (RAG) are diverse and expanding rapidly. Use Cases for Retrieval-Augmented Generation. Here are some key examples of how and where RAG is being utilized: Search Engines Search engines have implemented RAG to deliver more accurate and up-to-date featured snippets in their search results. RAG is particularly useful for applications of large language models (LLMs) that need to stay current with constantly updated information. Question-Answering Systems RAG enhances the quality of responses in question-answering systems. The retrieval-based model identifies relevant passages or documents containing the answer through similarity search, then generates a concise and relevant response based on that information. E-Commerce In e-commerce, RAG can improve the user experience by offering more relevant and personalized product recommendations. By retrieving and integrating information about user preferences and product details, RAG generates more accurate and helpful suggestions for customers. Healthcare RAG has significant potential in the healthcare industry, where access to accurate and timely information is critical. By retrieving and incorporating relevant medical knowledge from external sources, RAG can provide more precise and context-aware responses in healthcare applications, supporting clinicians with augmented information. Legal In the legal field, RAG can be effectively applied in scenarios such as mergers and acquisitions (M&A). By providing context for queries through complex legal documents, RAG allows for rapid navigation through regulatory issues, aiding legal professionals in their work. Use Cases for Retrieval-Augmented Generation 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 19, 2024in Salesforce
AI Misconceptions Dispelled
19May

AI Misconceptions Dispelled

The recent launch of GPT-4o (“o” for “omni”) has captivated everyone with its seamless human-computer interaction. Capable of solving math problems, translating languages in real-time, and even answering queries in a human voice with emotions, GPT-4o is a game-changer. Within hours of its debut, shares of Duolingo, the popular language EdTech platform, plummeted by 26% as investors perceived GPT-4o as a potential threat. But what AI Misconceptions Dispelled, would prevent this? Fears about AI are widespread. Many believe it will become so advanced and efficient that employing humans will be too costly, potentially leading to mass unemployment. Over the past year, it has become clear that artificial intelligence (AI) is among the most disruptive forces in business. AI promises efficiency and speed but also raises concerns about bias and ethics. In a candid conversation on Mint’s new video series All About AI, Arundhati Bhattacharya, Chairperson and CEO of Salesforce India, dispels these fears and discusses bridging the generation gap and making Salesforce a Great Place to Work. Forging Unity and Vision “When I came in, there were disparate groups—sales and distribution, technology and products, support and success. Each group had its leaders, but nobody was bringing them together to create one Salesforce vision and ensure that each group developed the Salesforce DNA,” Arundhati reflects on her April 2020 arrival. She underscored Salesforce’s values-driven approach, highlighting the significance of Trust, Customer Success, Innovation, Equality, and Sustainability. Under Arundhati’s leadership, Salesforce India has risen from 36th to 4th on the Great Places to Work list. Navigating AI Skepticism AI advancements are profoundly shaping industries and humanity’s future. According to Frost & Sullivan’s “Global State of AI, 2022” report, 87% of organizations see AI and machine learning as catalysts for revenue growth, operational efficiency, and better customer experiences. A 2023 IBM survey found that 42% of large businesses have integrated AI, with another 40% considering it. Furthermore, 38% of organizations have adopted generative AI, with an additional 42% contemplating its implementation. Despite the excitement around AI, skepticism remains. Arundhati offers insights on addressing this skepticism and using AI to benefit society. She suggests a balanced approach, noting that every significant technological change has sparked similar fears. Arundhati argues that AI won’t necessarily lead to massive unemployment, given humanity’s ability to adapt and evolve. Amidst India’s socio-economic challenges, Arundhati sees AI as a potent tool for positive change. She cites examples like the Prime Minister’s Jan Dhan Yojana, where AI-enabled solutions facilitated broader financial inclusion. “Similarly, AI can greatly improve services in state hospitals where doctors are overworked. AI can gather patient symptoms and present an initial diagnosis, allowing doctors to focus on more critical aspects. The technology is also being used to check sales conversations for accuracy in insurance, ensuring compliance and reducing mis-selling,” she elaborates. Driving Productivity through AI Integration Improving productivity in India is a pressing issue, and AI can effectively bridge this gap. However, the term “AI” is often overused and misunderstood. People need to approach AI initiatives with intentionality and focus. First, determine the use cases for AI, such as improving productivity, gaining customer mindshare, or enhancing customer experience. Once that is clear, ensure your organization is structured to provide the right inputs for AI, which involves having a robust data strategy. Tools like Data Cloud can help by integrating various data sources without copying the data and extracting intelligence from them. Lastly, securing buy-in from employees is crucial for successful AI implementation. Addressing their concerns, communicating the potential risks, and aligning everyone toward the same goal is essential. Securing the Future: Addressing AI Security Concerns As AI technologies advance, concerns about their security and potential misuse also rise. Threat actors can exploit sophisticated AI tools intended for positive purposes to carry out scams and fraud. As businesses rely more on AI, it is vital to recognize and protect against these security risks. These risks include data manipulation, automated malware, and abuse through impersonation and hallucination. To tackle AI security challenges, consider prioritizing cybersecurity measures for AI systems. Salesforce makes substantial investments in cybersecurity daily to stay ahead of potential threats. “We use third-party infrastructure with additional security layers on top. Public cloud infrastructure provides multiple layers of security, much like a compound with perimeter, building, and apartment security,” Arundhati explains. Empowering the Next Generation Workforce and Fostering Innovation Transitioning from her previous role as Chairperson of the State Bank of India to leading Salesforce India, Arundhati acknowledges the generational shift in workforce dynamics. She emphasizes understanding and catering to the evolving needs and aspirations of a younger workforce, focusing on engagement and fulfillment beyond monetary incentives. “Salesforce has a strong giving policy called one by one by one, where we give 1% of our profit, products, and time to the nonprofit sector. This resonates with the younger workforce, making them feel engaged and fulfilled.” Through a dedicated startup program, Salesforce fosters a collaborative ecosystem where startups can leverage resources, tools, and connections to thrive and succeed. Arundhati’s stewardship of Salesforce India epitomizes a transformative leadership approach anchored in values, innovation, and community empowerment. Under her leadership, Salesforce India continues to chart a course toward sustainable growth and inclusive prosperity, poised to redefine the paradigm of corporate success in the digital age. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 19, 2024in Generative AI, Salesforce Einstein
Summer 24 The AI Release
17May

Summer 24 The AI Release

Salesforce Unveils Summer 2024 Release with Generative AI at the Forefront Salesforce has announced its Summer 2024 release, featuring generative AI (GenAI) as a key highlight. Set to be generally available on June 17, 2024, this release promises enhanced productivity and access to large language models (LLMs) on an open platform. Read on to see why we call Summer 24 the AI release. Key Features of the Summer 2024 Release 1. Bring Your Own LLM Expansion 2. Slack AI 3. Zero Copy Integration with Amazon Redshift 4. Vector Database 5. Data Cloud for Commerce 6. Digital Wallet Enhanced Security with Einstein Trust Layer The Einstein Trust Layer ensures enhanced protection for customer and company data, making the new features more secure. Upcoming Pre-Summer Releases In addition to the major features coming in June, Salesforce has already introduced several innovations: Unified Knowledge Solution Salesforce and Vonage Partnership Conclusion Salesforce’s Summer 2024 release is packed with generative AI enhancements, robust integrations, and new tools aimed at boosting productivity, security, and data insights. With features gradually rolling out and pre-summer innovations already available, Salesforce continues to lead in delivering cutting-edge AI solutions to its users. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 17, 2024in Einstein Insights, Generative AI, Salesforce, Salesforce Einstein, Unified Knowledge
Google Search Goes AI
15May

Google Search Goes AI

For the past 25 years, Google Search has evolved through numerous technological advancements. They’ve refined their core information quality systems to help you find the best content on the web, building a knowledge base of billions of facts about people, places, and things. This ensures you receive reliable information instantly. And now, Google Search Goes AI. If you experienced it before reading this insight, it might have taken you a bit by surprise. Generative AI enhances Search beyond what you ever imagined. Whether you’re researching, planning, or brainstorming, Google takes care of the heavy lifting. This innovation is driven by Google’s new custom Gemini model, which combines multi-step reasoning, planning, and multimodality with Google premier Search systems. Quick Answers with AI Overviews For those times when you need quick information without piecing everything together, AI Overviews can help. Users have already utilized AI Overviews billions of times through Google’s Search Labs experiment. They appreciate the concise topic overviews and links for further learning. Google has observed that AI Overviews increase Search usage and satisfaction. Starting today, AI Overviews are rolling out to all U.S. users, with plans to reach over a billion people worldwide by the end of the year. AI Overviews lead users to a broader range of websites for complex questions. The links within these overviews receive more clicks than traditional web listings. As we expand this feature, we’ll focus on driving valuable traffic to publishers and creators. Ads will remain clearly labeled and distinct from organic results. One can only imagine how this might change the world of SEO. Customizable AI Overviews Soon, you can customize AI Overviews to simplify the language or provide more detail. This is particularly useful for newcomers to a topic or for simplifying explanations for children. This feature will be available in Search Labs for English queries in the U.S. soon. Tackling Complex Questions With the Gemini model’s multi-step reasoning, AI Overviews can handle complex questions in a single search. For example, if you’re looking for a yoga or Pilates studio that’s popular with locals, convenient for your commute, and offers new member discounts, you’ll soon be able to ask, “Find the best yoga or Pilates studios in Boston and show me details on their intro offers and walking time from Beacon Hill.” These capabilities are coming soon to AI Overviews in Search Labs for English queries in the U.S. Planning Ahead Beyond answering questions, Search can help with planning. Search’s planning capabilities assist in creating plans for meals and vacations. For instance, search “create a 3-day meal plan for a group that’s easy to prepare,” and you’ll receive a variety of recipes. You can customize your plan, such as swapping a meal for a vegetarian option, and export it to Docs or Gmail. Meal and trip planning features are currently available in Search Labs in English in the U.S., with more customization options and categories coming later this year. Exploring AI-Organized Results When seeking inspiration, it can be challenging to sift through numerous options. Soon, Search will use generative AI to brainstorm with you, organizing results under unique AI-generated headlines, showcasing diverse perspectives and content types. This AI-organized results page will be available soon for English searches in the U.S., starting with dining and recipes, followed by movies, music, books, hotels, shopping, and more. Video Search Assistance Search is not just limited to text. Often, your questions involve visual elements. Advancements in video understanding allow you to search using videos. For instance, if you bought a record player at a thrift shop and it’s malfunctioning, searching with a video can save you the effort of describing the issue in words. You’ll receive an AI Overview with troubleshooting steps. Video search capabilities will be available soon for Search Labs users in English in the U.S., with plans to expand to more regions over time. This is a glimpse of how Google is reimagining Google Search, blending today’s best features with the advanced capabilities of the Gemini model. Soon, Google will handle the searching, simplifying, researching, planning, brainstorming, and more. Sign up for Search Labs to be among the first to try out these features and more. Like Related Posts Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

Read More
May 15, 2024in Generative AI, Salesforce Einstein
Salesforce AI
09May

Salesforce AI

Salesforce AI is the cornerstone of our Einstein 1 Platform, offering reliable and adaptable AI solutions seamlessly integrated into your customer data. With Einstein, you can craft tailored, predictive, and generative AI experiences to address all your business requirements securely. Einstein brings conversational AI to every facet of your operations, from workflows and users to departments and industries. Here’s what Einstein can do for you: Sales AI: Accelerate sales cycles with trusted AI capabilities. Einstein can compose emails enriched with customer insights, summarize sales calls, and provide real-time predictions to guide sellers towards successful deals. Customer Service AI: Enhance customer service experiences while boosting agent efficiency. Einstein surfaces relevant information during support interactions, automates case resolutions, and empowers agents with a knowledge base. Marketing AI: Drive personalized and efficient marketing campaigns at scale. Einstein provides insights to enhance engagement, create personalized customer journeys, and automate outreach efforts. Commerce AI: Personalize every buyer and merchant interaction with flexible ecommerce AI tools. Einstein generates product descriptions, recommends relevant products, and optimizes buying experiences. Einstein 1 Studio: Customize and extend AI for CRM with ease. Configure actions, prompts, and models to tailor Einstein Copilot to your specific business needs. Copilot Builder: Extend Einstein Copilot with familiar platform features to streamline workflows and monitor interactions seamlessly. Prompt Builder: Create prompt templates to expedite tasks and generate content grounded in your business data, ensuring relevance across Einstein Copilot, Lightning pages, and flows. Model Builder: Build or import predictive AI models into Salesforce and the Einstein Trust Layer, seamlessly managing AI models in a unified control plane. Deploy AI you can trust with the Einstein Trust Layer, ensuring privacy, security, and responsible use across your organization. Features like Dynamic Grounding, Sensitive Data Masking, and Ethics and Inclusivity policies uphold ethical AI principles while optimizing accuracy and relevance. Join companies like General Mills and Riley Children’s Health in leveraging the power of Salesforce AI to drive personalized experiences and optimize operations for greater impact and efficiency. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 9, 2024in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Einstein
MuleSoft Certifications Now Unified with Salesforce Certifications
09May

MuleSoft Certifications Now Unified with Salesforce Certifications

MuleSoft Certifications Now Unified with Salesforce Certifications As of May 6, 2024, MuleSoft certifications have been officially integrated into the Salesforce Certification program, with management now handled through Webassessor. This move simplifies the certification process, enabling professionals to manage both their Salesforce and MuleSoft credentials within a single platform, streamlining maintenance and tracking. This article delves into the merging of MuleSoft certifications with Salesforce’s Trailhead platform, highlighting what this means for professionals in both ecosystems. The update offers a significant improvement in managing certifications, particularly for those working across both platforms, as Salesforce has owned MuleSoft since 2018. We’ll cover what this change entails for current certification holders, key dates in the transition, and the new opportunities this unified platform brings—including new certifications. What is MuleSoft? MuleSoft is a leading integration platform that enables businesses to connect applications, data, and devices seamlessly. As an Integration Platform as a Service (iPaaS), MuleSoft facilitates the integration of cloud-based and on-premise applications, ensuring smooth workflows across various systems. Acquired by Salesforce in 2018, MuleSoft powers the integration layer of the Salesforce ecosystem, playing a crucial role in enabling businesses to unify their systems and create connected experiences. With the increasing demand for digital transformation and connected systems, MuleSoft expertise is becoming ever more valuable in the job market. MuleSoft Certifications and Training MuleSoft certifications validate expertise in designing, building, and managing integrations using the Anypoint Platform. Prior to this transition, MuleSoft certifications were handled through the MuleSoft Training portal, which was separate from Salesforce’s broader certification system. While this independent platform was functional, it required separate accounts and processes, making exam registration and certification management more cumbersome. By integrating MuleSoft certifications into Trailhead, Salesforce has simplified this process, offering a unified, more user-friendly experience for managing certifications. Transition Timeline The following key dates marked the transition: What This Means for Current MuleSoft Certification Holders For those already certified through MuleSoft, the migration to Salesforce’s certification system should have occurred automatically. MuleSoft credentials were transferred to their Trailblazer profiles for anyone with existing Webassessor accounts. A confirmation email was sent to ensure that the transition was successful. For those without a Webassessor account, one was created on their behalf, with login details provided via email by April 2024. Certification Maintenance MuleSoft certification holders with maintenance pending as of January 1, 2024, are not required to complete additional tasks through the old system. The expectation is that certification holders will have ample time to familiarize themselves with the new Trailhead process before maintenance requirements are introduced in 2025. New Certifications on Trailhead With the migration, certifications such as the MuleSoft Certified Catalyst Specialist and MuleSoft Certified Hyperautomation Specialist have also been integrated into Trailhead. Though not entirely new, these certifications were part of the legacy MuleSoft program, originally launched in late 2022 and early 2023. Summary The integration of MuleSoft certifications into Salesforce’s Trailhead platform marks a significant step towards a unified, more efficient credentialing process. This transition simplifies certification management, making it easier for professionals to stay current across both platforms. By merging these certifications, Salesforce is empowering professionals to fully leverage the combined capabilities of Salesforce and MuleSoft, further enhancing their skill sets in an increasingly interconnected digital landscape. Content updated September 2024. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
May 9, 2024in Data, Mulesoft, Salesforce

Subscribe to our mailing list. Join our mail list to receive our newsletter

We'll keep you up to date with our latest news, insights, free resources, and much more.
Don't worry, we won't spam you.
gettectonic.com