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Salesforce Summer 24 Data Cloud Release
02Jun

Salesforce Summer 24 Data Cloud Release

Data Cloud Ingest, harmonize, unify, and analyze streaming and batch data with Data Cloud. Then use that data to unlock meaningful and intelligent experiences across Customer 360 applications and beyond. Salesforce Summer 24 Data Cloud Release. Salesforce Summer 24 Data Cloud 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

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June 2, 2024in Salesforce
Salesforce Field Service Lightning
02Jun

Salesforce Field Service Lightning

Many companies worldwide seek quality services associated with Salesforce Field Service Lightning (FSL) to differentiate between lacking customer experiences and excellent ones. Satisfied customers associate such services with high-quality ratings, gradually building trust with the company and recommending it to others. The ability of any business to generate successful recognition and experience with clients helps establish an invaluable competitive advantage. Salesforce Field Service Lightning We are here to assist you in mapping and quoting various FSL Salesforce services such as equipment installation, repair, general customer service management, and maintenance. Field Service technicians, also known as mobile technicians, play a crucial role in delivering these tasks. They receive notifications on mobile devices and quickly find users in need of speedy solutions to their problems. What is Salesforce Field Service? Salesforce Field Service (formerly known as Field Service Lightning) is designed for the automation and optimization of work offered by dispatchers and field service agents. It ensures that no employee sacrifices any functionality of the related services when working outside the company. This system is part of the FSL Salesforce Service Cloud and aims to create a seamless workflow and avoid mistakes with the help of service technicians. Integral Parts of Salesforce Field Service After implementing Salesforce Field Service Lightning, clients can immediately see the benefits reflected in the increased efficiency of developed services. Advantages of Salesforce Field Service Lightning Bottom Line We hope this comprehensive guide on Salesforce Field Service Lightning has provided valuable insights into its aspects and benefits. Our experienced executives offer valuable advice and risk-free solutions for managing projects involving field service. You can contact Tectonic 24/7 for error removal and maintaining Salesforce FSL service deployments. Tasks such as project management and exception diagnosis are easily handled with the Service Cloud platform. We offer a strong framework for different service models and prepare reports for various service territory designs, ensuring a seamless and efficient operation. 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

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June 2, 2024in Salesforce Service Cloud
Salesforce Summer 24 Flow Release
01Jun

Salesforce Summer 24 Flow Release

Salesforce Flow Salesforce Summer 24 Flow Release. Compose intelligent workflows with Flow Builder and Flow Orchestration. Integrate across any system with Flow Integration. 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

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June 1, 2024in Mulesoft, Salesforce
Salesforce Solutions for Defense
01Jun

Salesforce Solutions for Defense

Defence Technology Solutions from Salesforce: Enabling Secure, Mission-Critical Operations Salesforce provides defense organizations with powerful technology solutions to deliver on their missions quickly and securely. By increasing IT flexibility, enhancing productivity, and safeguarding sensitive data in a secure, compliant cloud environment, Salesforce empowers defence organizations to achieve mission success with confidence. Salesforce Solutions for Defense. Modernizing Personnel Operations Salesforce streamlines workforce management and accelerates employee operations, providing a unified view of personnel and fast, digital workflows. Public sector organizations can transform hiring, recruiting, HR actions, IT requests, and employee services within a trusted operational hub. How It Works: Salesforce enhances productivity and digitizes government employee tasks throughout their lifecycle, from hire to retirement. Maximizing IT Agility Salesforce enables defence organizations to unlock data from legacy systems, cloud applications, and third-party platforms with an API-led approach, securely bridging on-premises and cloud environments. Rapid application development, consolidation, and system access become seamless with Salesforce’s low-code/no-code tools. How It Works: Salesforce compresses development cycles and increases flexibility, enabling defense organizations to deliver on mission objectives faster. Salesforce Solutions for Defense Delivering Successful Case Outcomes Salesforce supports the full case management lifecycle by integrating critical data points from multiple systems into a single, unified view. Defense organizations can empower caseworkers with purpose-built tools, ensuring successful case outcomes while reducing information silos and providing clients with the necessary support. How It Works: Salesforce creates a single source of truth for case management, enabling defense organizations to streamline workflows and improve service outcomes. By leveraging Salesforce’s defense technology solutions, organizations can modernize operations, maximize agility, and ensure successful case management outcomes, all while maintaining the highest levels of security and compliance. Salesforce Solutions for Defense from Tectonic. 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

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June 1, 2024in Public Sector Solutions, Salesforce Development Services, Salesforce Government Cloud, Salesforce Implementation Services, Salesforce Managed Services, Salesforce Public Sector Solutions
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

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June 1, 2024in Salesforce Einstein
Personalize Product Catalog Management Items with Custom Fields
31May

Personalize Product Catalog Management Items with Custom Fields

Personalize Product Catalog Management Objects with Custom Fields You can now add custom fields to multiple Product Catalog Management objects and pass the custom fields as additional fields in the Product List API and Bulk Product Details API. These APIs return values of all the custom fields to the requesting run time systems. Personalize Product Catalog Management Items with Custom Fields. Where: This change applies to Lightning Experience in Enterprise, Unlimited, and Developer editions. Why: You can add custom fields to these objects: Product Catalog Management adds standard and custom fields to some standard Salesforce objects. These fields are available only in orgs where Product Catalog Management is enabled. This object is available in API version 60.0 and later. 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

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May 31, 2024in Salesforce, Salesforce Sales Cloud
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

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May 30, 2024in Einstein 1 Platform, Generative AI, Hyperforce, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Snowflake
Did Google Dethrone ChatGPT
30May

Did Google Dethrone ChatGPT?

Google’s Bard has emerged as a contender in the realm of large language models (LLMs), sparking speculation about its potential to outshine OpenAI’s ChatGPT. This insight explores the validity of this claim and examines the tests and factors that could determine the ultimate victor in this ongoing AI rivalry. Did Google Dethrone ChatGPT? Google’s Gemini 1.5 Pro is a generational leap in terms of Multimodal Large Language Models, or MLLMs, much like GPT-4 was to LLMs back in March 2023. Did Google Dethrone ChatGPT? While initial rumors of Bard’s “dethronement” of ChatGPT surfaced from a single LinkedIn post in February 2024, substantial evidence is required to substantiate such claims. Let’s determine the potential battleground: The Testing Grounds: There’s no singular, universally recognized benchmark for evaluating LLMs. Here are some areas where Google and OpenAI may showcase their AI prowess: Generative Text Quality: Can the LLM generate various creative text formats—such as poems, code, scripts, and emails—while maintaining coherence and factual accuracy? Question Answering: How effectively can the LLM respond to open-ended, challenging, or unconventional questions, drawing on its knowledge base? Following Instructions: Can the LLM adhere to complex instructions and perform tasks requiring multi-step reasoning? Bias Mitigation: Does the LLM demonstrate impartiality in its responses, or does it exhibit traces of prejudice or social stereotypes? Beyond the Tests: While test results offer insights into LLM capabilities, other factors influence their overall impact: Accessibility: How easily can the LLM be accessed by the public? Is there a user-friendly interface or developer API? Real-World Applications: How seamlessly can the LLM be integrated into practical applications like chatbots, virtual assistants, or educational tools? Continuous Learning: How adeptly does the LLM adapt and enhance its performance over time, incorporating new data and user feedback? The Current Landscape: Declaring a definitive winner is challenging. Bard and ChatGPT excel in different domains. Here’s a speculative analysis: Generative Text Quality: Bard may have a slight advantage, leveraging Google’s extensive dataset. Question Answering: ChatGPT might excel in responding to open-ended queries with creativity, while Bard may prioritize factual accuracy. Following Instructions & Bias Mitigation: Both LLMs are continually refining their capabilities in these areas. The Future of LLMs: The landscape of LLMs is dynamic, with Google and OpenAI poised to make significant advancements. Anticipated developments include: Focus on Explainability: Efforts to understand the reasoning behind LLM responses to foster transparency and trust. Bias Mitigation: Strategies to address bias in LLMs for fairer and more inclusive interactions. Specialized LLMs: Development of domain-specific LLMs tailored to fields like medicine or law. Is Google AI better than ChatGPT? Gemini offers a better user experience, with more imagery and website links. Gemini Advanced generates better AI images than ChatGPT Plus. Gemini responses were often set out in a more readable format than ChatGPT’s responses. Gemini was better at generating spreadsheet formulas than ChatGPT. How is Bard better than ChatGPT? Bard has real-time access to the internet through Google Search, allowing it to incorporate the latest information and news into its responses. Trained on a static dataset not updated since 2021, however, ChatGPT can only access external information through plugins, and this functionality is limited. Is Google nervous about ChatGPT? It’s that the technology represents everything Google was afraid artificial intelligence would become. If ChatGPT runs rampant, the search giant fears it could ruin AI adoption for everyone. Since going viral, ChatGPT has demonstrated how generative AI can be user-friendly, practical, and productive. The narrative of ChatGPT’s dethronement may be premature. Bard and ChatGPT are evolving entities, and the ultimate victor will be determined by their ability to navigate future challenges and opportunities. As these LLMs progress, users stand to benefit from access to increasingly sophisticated and beneficial AI tools. 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

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May 30, 2024in Generative AI, Salesforce Einstein
Digital Experience Enhancement Via Commerce and Content
29May

Digital Experience Enhancement Via Commerce and Content

Businesses need robust solutions to enhance their digital experiences and streamline operations. Digital Experience Enhancement Via Commerce and Content can be addressed in multiple ways. When considering different systems, the approach to implementation and integration is crucial, especially with incumbent commerce platforms like Salesforce Commerce Cloud or Shopify Plus. The choice of integration method can significantly impact both customer engagement and operational efficiency. Traditional Monolithic Integration Approaches Traditional commerce systems typically fall into two categories: CMS/DXP-oriented and commerce-oriented platforms. Each has distinct characteristics but faces limitations inherent to a monolithic structure. CMS / DXP-oriented Platforms Platforms like Acquia Drupal, Adobe Experience Manager, and Sitecore, known for their strong digital experience capabilities, have evolved to include integrated and embedded commerce functionalities. Integrated Approach Platforms like Drupal Commerce for Acquia and Sitecore Experience Commerce exemplify an integrated approach where commerce capabilities are built directly into the DXP. This allows for a unified administrative and development experience, enabling business users to manage both content and commerce features seamlessly. While this approach offers benefits, it also presents challenges. The primary issue is adaptability. Commerce capabilities tightly coupled with the CMS can make customizing or scaling specific functionalities complex and restrictive. Additionally, without dedicated investment in the commerce platform as a standalone solution, it may lack many capabilities required for effective enterprise deployments. Performance issues can also arise as the system scales, with content management and commerce functionalities managed through the same monolithic architecture, leading to slower website performance and longer load times under heavy traffic conditions. Commerce Behind Content Some businesses use an embedded approach, integrating standalone or home-grown commerce capabilities, product information, and pricing data through batch or event-based synchronizations. This method allows the CMS’s presentation layer to dynamically display product information and transactions while maintaining core content management functionality. However, this approach also has downsides, impacting system efficiency and customer experience. Batch or event-based synchronizations can lead to data update delays, causing discrepancies between actual inventory and what’s displayed to customers. This can frustrate customers due to order issues like out-of-stock items appearing available. Additionally, the embedded method often requires complex integrations and middleware to sync data between the commerce platform and the CMS, increasing technical issues and complicating troubleshooting. This approach may also limit dynamic handling of commerce data within the CMS, restricting advanced features like real-time personalization and dynamic pricing. Maintaining such a system can require significant developer resources, leading to higher operational costs. Commerce-Oriented Platforms Commerce-centric platforms such as Salesforce Commerce Cloud and Shopify Plus focus on delivering comprehensive commerce solutions. These platforms have adapted to integrate with other technologies like headless CMS and search and product discovery tools to enable brands to deliver improved digital experiences. Content Behind Commerce Even when incorporating a headless CMS for easier content creation and management, commerce-centric platforms often feed this content back into their own presentation layer. This has been a popular approach for Salesforce Commerce Cloud (formerly Demandware) for over a decade. While this setup may improve operational efficiencies, it can limit overall performance and customer experience due to potential bottlenecks at the commerce platform’s presentation layer. Moreover, it does not provide the performance or customer experience benefits of a modern headless commerce frontend. Cartridges, Modules, and Plugins Using cartridges, modules, or plugins for functionalities like search and product discovery can enhance the onsite customer experience. However, these integrations can face limitations in supporting more complex capabilities, such as combining content from a headless CMS, product information from a PIM, and product data from the commerce platform, or managing merchandising that accounts for inventory levels across various distribution centers and store fulfillment locations. These limitations can restrict the ability to fully leverage integrated data to enhance customer interactions and operational insights. Digital Experience Enhancement Via Commerce and Content, as businesses seek to enhance their digital experiences and streamline operations, choosing the right integration approach for their commerce platform is critical. Balancing the benefits and challenges of traditional monolithic and commerce-oriented platforms will be key to optimizing customer engagement and operational 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 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 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 CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more

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May 29, 2024in Salesforce Commerce Cloud
AI in Marketing
29May

AI in Marketing

John Dutton recently posted in his blog about AI “representatives” who talk to you. It’s an interesting look into the “creep” factor potentially in artificial intelligence and certainly provides plenty of food for thought on robots and AI in marketing. Read it here. Summarized below. When the media or the internet shares a look at this wierd generated image talking, its easy to spot. When not flagged, it is getting a little harder to know for sure-is it real or is it Memorex. Unveiling AI in Ukraine Last week, Ukraine’s Ministry of Foreign Affairs introduced Victoriya Shi, a “digital representative” and AI-produced avatar. Shi delivers official statements in videos shared on the Ministry’s online social channels. According to Ukrainian Foreign Minister Dmytro Kuleba, Shi was created to “save time and resources” for diplomats. Given the ongoing conflict in Ukraine, this rationale seems reasonable. However, the introduction of such an AI avatar raises questions about the future and the potential for dystopian developments. A key concern is the ease of deepfaking an already artificial persona. This challenge has been addressed by the MFA through a smart yet simple solution: a QR code in the corner of each video that directs viewers to the official text version of the announcement on the Ministry’s website. It’s worth noting that the official statements themselves are not AI-generated, which could set a worrying precedent. While the Ukrainian version’s reception is unknown, the English version of Victoriya Shi struggles to escape the “uncanny valley” of artificial humans. Her sign-off, “I look forward to our fruitful cooperation,” has an eerie, robotic undertone. This unsettling impression might not be entirely negative. Navigating the Age of AI We are deeply entrenched in the Age of AI, where trust has become a scarce commodity. The concept of “fake news” emerged well before generative AI, gaining prominence in late 2016 with the rise of certain political figures. A search on Google Trends reveals the sudden spike in terms like “fake news” and “post-truth” during that period. With AI’s potential to create convincing deepfakes, the challenge of distinguishing real from fake is intensifying. A recent incident in Hong Kong saw an employee deceived by an AI-generated video, leading to a $25 million fraud. This highlights the need for secure credentialing, especially in large organizations and potential metaverse meetings. However, in-person meetings remain immune to such digital deceptions. AI’s Role in Authenticity Ironically, AI might help combat its own deceptions. OpenAI’s recent collaboration with the Coalition for Content Provenance and Authenticity (C2PA) aims to develop tools for identifying AI-generated content. As deepfakes become more sophisticated, the absence of C2PA authentication could become a red flag. If this leads to a heightened skepticism towards digital media, it might not be entirely negative. AI could bolster our defenses against scams, encouraging a healthy suspicion of the digital content we consume. The Balance of Authenticity and Truth The distinction between authenticity and truth is crucial. A government-created AI avatar can be fake in its artificiality but still deliver authentic, official statements. As generative AI advances, we must fine-tune our skepticism. Victoriya Shi’s name reflects Ukraine’s hope for “victory” and the integration of AI (“Shi” in Ukrainian). The war may ultimately hinge on intelligent tech use rather than sheer military might. Update and Reflections Following the newsletter’s release, it was revealed that WPP, the world’s largest ad agency network, nearly fell victim to a deepfake scam, with the CEO’s voice being replicated by AI. The Dystopia/Utopia Dichotomy The generative AI revolution has begun, and its trajectory could lead to either a utopian or dystopian future. My novel, “2084,” explores a world where life appears superficially perfect, masking underlying issues. Artistic AI Innovations One of my book’s main characters is a sculptor, a profession I initially believed immune to AI. However, Monumental Labs, founded in 2022, uses “sensors and AI” to produce sculptures at a fraction of traditional costs. This reality mirrors the AI-driven world imagined in “2084.” Genetic Modifications and Luxury Fresh Del Monte’s Rubyglow® pineapple, an ultra-premium, genetically modified fruit, exemplifies the future of designer foods. My novel envisions similar advancements with patented food items and drone-pollinated plants. The Challenger Mindset Adam Morgan, an expert in the challenger brand mindset, emphasizes the importance of maintaining a challenger attitude regardless of market position. Companies like Netflix exemplify this, adapting and thriving in a competitive landscape by retaining a challenger’s drive. The Right to Repair and Brand Identity The US Government Accountability Office highlights the “softwareification” of cars, making independent repairs difficult. Similarly, Apple’s restrictive policies on iPhone repairs underline the broader trend of manufacturers controlling repair markets. Cult of Brand Identity The Gray Area podcast discusses how modern consumers interact with brands, focusing on identity over product quality. This shift underscores the evolving landscape of commercial competition and consumer behavior. 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 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 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

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May 29, 2024in Generative AI, Salesforce Einstein
Salesforce Revenue Lifecycle
28May

Salesforce Revenue Lifecycle

Revenue Lifecycle Management (RLM) with Revenue Cloud empowers businesses to drive profitable growth by automating the entire product-to-cash process. From managing product catalogs and pricing to order fulfillment and billing, RLM streamlines operations and accelerates revenue generation. Salesforce Revenue Lifecycle. Here’s how businesses can leverage RLM for efficient revenue lifecycle management: Additionally, RLM is available in Lightning Experience and requires a Revenue Lifecycle Management license in Sales Cloud and Service Cloud for Enterprise, Unlimited, and Developer editions. Key features of RLM include: As businesses navigate the subscription economy, RLM offers a scalable, flexible, and efficient omni-channel platform for transacting revenue. By addressing growth, churn reduction, and profitability gains, RLM empowers organizations to scale and grow, leveraging modular components and APIs to support various sales motions and use cases. With ongoing innovation and industry expertise, Salesforce and partners like Tectonic are committed to helping subscription companies achieve profitable and efficient growth with Revenue Cloud and Revenue Lifecycle Management. 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

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May 28, 2024in Salesforce, Salesforce Sales Cloud
Growing Family of Einstein Copilots
27May

Growing Family of Einstein Copilots

Salesforce made several announcements this month, regarding the Growing Family of Einstein Copilots. By unveiling AI-powered Einstein Copilots for marketing and merchants. These new Copilots build on the previously announced Copilots for retailers and shoppers and are integrated into the Einstein 1 platform. They can communicate with each other, effectively bridging marketing and commerce, and have full access to Salesforce Data Cloud. “Welcome to the AI enterprise,” said Ariel Kelman, Salesforce President and CMO, during his keynote at Salesforce Connections in Chicago. Kelman outlined four waves of AI: Predictive (e.g., lead scoring), Generative, Autonomous, and AI General Intelligence. “We are starting to enter the third wave,” he stated, where AI will begin to take actions independently. Copilots are a step in that direction, although for now, a human remains in control. The Path to the AI Enterprise Kelman described five steps towards creating an AI enterprise: Regarding the last point, new Slack AI tools were demonstrated for summarizing interactions and importing actionable data from Data Cloud into Slack. The strategy for Einstein Copilots aims to empower business users in marketing, commerce, and other functions to execute complex tasks, such as creating personalized customer journeys, using natural language prompts. Einstein Copilots for Marketing and Merchants The marketing Copilot can generate marketing briefs and content, and create email campaigns. Through Data Cloud, it can ingest and execute a brand’s datasets, including customer data from repositories like AWS, Snowflake, and Databricks. By automating routine tasks and time-consuming projects like data connection and analysis, the Copilot aims to free up marketers to engage more thoughtfully with their audiences. The commerce Copilot, part of Salesforce’s commerce offerings, responds to natural language prompts to create online storefronts, improve product discoverability, write product descriptions, and make product recommendations. Other Announcements Availability 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

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May 27, 2024in Einstein 1 Platform
analytics 360 and journey builder
27May

Summer 24 Analytics Release

Analytics Analytics enhancements include new and updated features for Lightning reports and dashboards, Data Cloud reports and dashboards, CRM Analytics, Intelligent apps, and Tableau. Summer 24 Analytics Release. Summer 24 Analytics 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

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May 27, 2024in Salesforce, Salesforce Tableau
Patterns for AI Security
27May

Patterns for AI Security

Supporting the development of AI design patterns that demonstrate trustworthiness not only enhances user experiences but also serves as an enabling tool for informing more effective policy and compliance measures. Patterns for AI Security. By prototyping patterns, teams can effectively communicate complex policies, illustrating how they could function within industries and for users. This approach also facilitates the testing of patterns, enabling teams to swiftly identify trade-offs and challenge assumptions, thereby accelerating the establishment of industry standards for best practices. Ultimately, this iterative process leads to the creation of better policies and services that yield superior outcomes for both individuals and organizations. Patterns for AI Security For instance, consider the pattern of “watermarking,” mandated by China’s Cyberspace Administration and poised to be adopted by the USA and EU. Through exploration of this pattern, the team at IF highlighted the inherent challenges associated with implementing watermarking for users and businesses. Another design pattern is the AI query router. A user inputs a query, that query is sent to a router, which is a classifier that categorizes the input. A recognized query routes to small language model, which tends to be more accurate, more responsive, & less expensive to operate. If the query is not recognized, a large language model handles it. LLMs much more expensive to operate, but successfully returns answers to a larger variety of queries. In this way, an AI product can balance cost, performance, & user experience. Moreover, investing in trustworthy solutions not only addresses immediate challenges but also positions businesses for long-term success. As reliance on AI systems becomes ubiquitous, the complexities of trust, collaboration, and robustness will only intensify. Stakeholders, both in the private and public sectors, increasingly expect organizations to deliver responsible solutions that prioritize user value without compromising on privacy. This is particularly evident among Gen Z individuals, who demand technology that understands and anticipates their needs while upholding privacy standards. Gen Alpha will be even moreso inclined. Organizations that recognize the significance of trustworthiness and proactively invest in differentiating their products and services accordingly stand to gain a competitive advantage in the evolving landscape. By prioritizing trustworthiness, businesses can not only meet the expectations of their stakeholders but also foster lasting relationships built on transparency, reliability, and integrity. We all anchor to some tried and tested methods, approaches and patterns when building something new. This statement is very true for those in software engineering, however for generative AI and artificial intelligence itself this may not be the case. With emerging technologies such as generative AI we lack well documented patterns to ground our solution’s. Here are a handful of approaches and patterns for generative AI, based on evaluation of countless production implementations of LLM’s in production. The goal of these patterns is to help mitigate and overcome some of the challenges with generative AI implementations such as cost, latency and hallucinations. List of Patterns Like Related Posts 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 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

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May 27, 2024in Generative AI
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

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May 26, 2024in Salesforce, Salesforce Einstein, Snowflake

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