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Salesforce and AdvoLogix

SUGAR LAND, Texas, Aug. 12, 2024 /PRNewswire/ — AdvoLogix, a leader in legal technology, is excited to announce its groundbreaking Legal Assistant AI, a comprehensive suite of AI tools designed specifically for the legal industry. Law firms face mounting pressure to deliver exceptional client service while managing rising costs and complexities. This innovative solution seamlessly integrates with Salesforce, automating tasks and leveraging the power of AI to streamline law firm operations while ensuring security with its Trust and Safety Layer. Our AI’s Trust and Safety Layer, ensures that law firms can trust our technology to protect sensitive information. AdvoLogix Legal Assistant AI significantly enhances daily workflows with advanced capabilities such as document automation, financial management, client and matter intake, case management, and workflow optimization. Customizable based on unique data sets, these AI agents can be tailored to meet the specific needs of any legal organization. For example, law firms can create AI agents to address the nuanced requirements of particular clients or specialized areas of practice. The AI’s Trust and Safety Layer ensures secure data retrieval, grounding, prompt defense, and compliance, providing law firms with the confidence that their sensitive information is protected. By embedding these tools directly into the Salesforce platform, AdvoLogix delivers a powerful, integrated solution that leverages the power of AI in the context of daily law firm operations. Leveraging SALI Tags for Enhanced Data Management One of the standout features of the AdvoLogix Legal Assistant AI is its integration with the SALI (Standards Advancement for the Legal Industry) taxonomy. By leveraging Salesforce workflows, attorneys can quickly and accurately tag matters with SALI tags, enabling data-driven insights and improved matter management. This seamless integration ensures that valuable data is captured and utilized effectively to inform strategic decisions. Customizable AI Models for Tailored Legal Support AdvoLogix offers fine-tuned AI models specifically trained for legal activities. These models can be easily integrated into Salesforce workflows to automate tasks such as record and document retrieval, document summarization, and system data queries. Additionally, these AI models have the capability to ask and receive answers to general or specific legal questions on any topic, all from the perspective of an attorney. By leveraging the power of AI within the familiar Salesforce environment, legal professionals can focus on higher-value activities while the AI handles routine tasks. Some features are currently available in controlled release. A Commitment to Security and Accuracy “By embedding our AI capabilities into Salesforce workflows, we’ve developed a robust solution that allows legal professionals to benefit from AI services that are safe and highly efficient during normal work activities. Our AI’s Trust and Safety Layer, featuring secure data retrieval, grounding, prompt defense, and more, ensures that law firms can trust our technology to protect sensitive information. This focus on security, accuracy, and compliance is crucial for modern legal practices,” said Jonathan Reed, CEO of AdvoLogix. Experience the Future of Legal AI at ILTACON 2024 Visit AdvoLogix at Booth #346 to see live demonstrations of our Legal Assistant AI capabilities and discover how they can transform your firm’s operational efficiency. Our experts will be available to answer your questions and provide tailored insights into how our AI solutions can enhance your legal workflows and financial management. About AdvoLogix Founded in 2006, AdvoLogix is a premier provider of AI-driven technology solutions, helping businesses in the legal technology sector and beyond streamline operations, reduce costs, and improve productivity. With a broad range of native integrations that seamlessly integrate with Salesforce, AdvoLogix delivers measurable gains in productivity and efficiency. For more information, visit www.advologix.com and follow AdvoLogix on LinkedIn @AdvoLogix. Media Contact:Marketing [email protected] 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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August 12, 2024in Salesforce
Demandbase One for Sales iFrame
09Aug

Demandbase One for Sales iFrame

Understanding the Demandbase One for Sales iFrame in Salesforce The Demandbase One for Sales iFrame (formerly known as Sales Intelligence) allows sales teams to access deep, actionable insights directly within Salesforce. This feature provides account-level and people-level details, including engagement data, technographics, intent signals, and even relevant news, social media posts, and email communications. By offering this level of visibility, sales professionals can make informed decisions and take the most effective next steps on accounts. Key Points: Overview of the Demandbase One for Sales iFrame The iFrame is divided into several key sections: Account, People, Engagement, and Insights tabs. Each of these provides critical information to help you better understand and engage with the companies and people you’re researching. Account Tab People Tab Engagement Tab Final Notes: The Demandbase One for Sales iFrame is a powerful tool that provides a complete view of account activity, helping sales teams make informed decisions and drive results. 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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August 9, 2024in Data
July Changes to Preference Center
05Aug

July Changes to Preference Center

Privacy Center Update What’s the July Changes to Preference Center? Starting in July 2024, the Privacy Center app within the core platform now supports retention features. July Changes to Preference Center introduces a new Hyperforce-based retention store, allows for retention testing in sandboxes, and offers the option to mask data during retention. The new Hyperforce-based retention store can be provisioned using the core Privacy Center app, eliminating the need for Heroku or the Privacy Center managed package. The rollout of this new retention capability will be phased across regions, initially launching in Germany, Australia, and America East. You can spin up a retention store once it’s available in your region. For more details, refer to the Privacy Center’s Hyperforce-Based Retention Store FAQ. What action do I need to take? What if I don’t take any action? You can continue using the legacy Privacy Center app (managed package version) for data retention, but it will no longer be enhanced and will remain in maintenance mode. Heroku can still be used for managing data retention policies until the end of your contract. Where can I learn more about this upcoming change? Review the Privacy Center’s Hyperforce-Based Retention Store FAQ for more information. 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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August 5, 2024in Hyperforce
Salesforce to Acquire PredictSpring
01Aug

Salesforce to Acquire PredictSpring

Salesforce to Acquire PredictSpring, Enhancing Customer 360 Capabilities in Retail Salesforce has announced a definitive agreement to acquire cloud-based point-of-sale (PoS) software vendor PredictSpring, aiming to bolster its Customer 360 capabilities and strengthen its foothold in the retail industry. PredictSpring, headquartered in California, provides PoS systems that enable store associates to engage with shoppers and complete transactions from anywhere in the store using mobile devices. The software also supports store operations, including fulfillment, client profile management, and online ordering for items not immediately available. “The combined talent, resources, and innovation of Salesforce and PredictSpring will empower brands and retailers to drive frictionless and personalized engagement across all touchpoints,” said Jeff Amann, executive vice president of Salesforce Industries. PredictSpring, already a Salesforce ecosystem partner integrated with Commerce Cloud and Service Cloud, has been collaborating with Salesforce since 2019 when new tools were added to Commerce Cloud. Founded in 2013 by Nitin Mangtani, a former product manager at Google, PredictSpring has received investments from Salesforce Ventures, Felicis Ventures, Novel TMT Ventures, and Beanstalk Ventures. The company raised $16 million in a Series B funding round and $11.4 million in a Series A round. While Salesforce did not disclose the transaction value, it will retain the entire PredictSpring team, consisting of approximately 31 employees. The acquisition is expected to close in the third quarter of Salesforce’s fiscal year 2025, which runs from February to January. Earlier this year, Salesforce attempted to acquire enterprise data management software provider Informatica, but the talks fell through. Notable past acquisitions by Salesforce include Slack, MuleSoft, Tableau, and Troops.ai. 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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August 1, 2024in Mulesoft
Snowpark Container Services
01Aug

Snowpark Container Services

Snowflake announced on Thursday the general availability of Snowpark Container Services, enabling customers to securely deploy and manage models and applications, including generative AI, within Snowflake’s environment. Initially launched in preview in June 2023, Snowpark Container Services is now a fully managed service available in all AWS commercial regions and in public preview in all Azure commercial regions. Containers are a software method used to isolate applications for secure deployment. Snowflake’s new feature allows customers to use containers to manage and deploy any type of model, optimally for generative AI applications, by securely integrating large language models (LLMs) and other generative AI tools with their data, explained Jeff Hollan, Snowflake’s head of applications and developer platform. Mike Leone, an analyst at TechTarget’s Enterprise Strategy Group, noted that Snowpark Container Services’ launch builds on Snowflake’s recent efforts to provide customers with an environment for developing generative AI models and applications. Sridhar Ramaswamy became Snowflake’s CEO in February, succeeding Frank Slootman, who led the company through a record-setting IPO. Under Ramaswamy, Snowflake has aggressively added generative AI capabilities, including launching its own LLM, integrating with Mistral AI, and providing tools for creating AI chatbots. “There has definitely been a concerted effort to enhance Snowflake’s capabilities and presence in the AI and GenAI markets,” Leone said. “Offerings like Snowpark help AI stakeholders like data scientists and developers use the languages they prefer.” As a result, Snowpark Container Services is a significant new feature for Snowflake customers. “It’s a big deal for the Snowflake ecosystem,” Leone said. “By enabling easy deployment and management of containers within the Snowflake platform, it helps customers handle complex workloads and maintain consistency across development and production stages.” Despite the secure environment provided by Snowflake Container Services, it was revealed in May that the login credentials of potentially 160 customers had been stolen and used to access their data. However, Snowflake has stated there is no evidence that the breach resulted from a vulnerability or misconfiguration of the Snowflake platform. Prominent customers affected include AT&T and Ticketmaster, and Snowflake’s investigation is ongoing. New Capabilities Generative AI can transform business by enabling employees to easily work with data to inform decisions and making trained experts more efficient. Generative AI, combined with an enterprise’s proprietary data, allows users to interact with data using natural language, reducing the need for coding and data literacy training. Non-technical workers can query and analyze data, freeing data engineers and scientists from routine tasks. Many data management and analytics vendors are focusing on developing generative AI-powered features. Enterprises are building models and applications trained on their proprietary data to inform business decisions. Among data platform vendors, AWS, Databricks, Google, IBM, Microsoft, and Oracle are providing environments for generative AI tool development. Snowflake, under Slootman, was less aggressive in this area but is now committed to generative AI development, though it still has ground to cover compared to its competitors. “Snowflake has gone as far as creating their own LLM,” Leone said. “But they still have a way to go to catch up to some of their top competitors.” Matt Aslett, an analyst at ISG’s Ventana Research, echoed that Snowflake is catching up to its rivals. The vendor initially focused on traditional data warehouse capabilities but made a significant step forward with the late 2023 launch of Cortex, a platform for developing AI models and applications. Cortex includes access to various LLMs and vector search capabilities, marking substantial progress. The general availability of Snowpark Container Services furthers Snowflake’s effort to foster generative AI development. The feature provides users with on-demand GPUs and CPUs to run any code next to their data. This enables the deployment and management of any type of model or application without moving data out of Snowflake’s platform. “It’s optimized for next-generation data and AI applications by pushing that logic to the data,” Hollan said. “This means customers can now easily and securely deploy everything from source code to homegrown models in Snowflake.” Beyond security, Snowpark Container Services simplifies model management and deployment while reducing associated costs. Snowflake provides a fully integrated managed service, eliminating the need for piecing together various services from different vendors. The service includes a budget control feature to reduce operational costs and provide cost certainty. Snowpark Container Services includes diverse storage options, observability tools like Snowflake Trail, and streamlined DevOps capabilities. It supports deploying LLMs with local volumes, memory, Snowflake stages, and configurable block storage. Integrations with observability specialists like Datadog, Grafana, and Monte Carlo are also included. Aslett noted that the 2020 launch of the Snowpark development environment enabled users to use their preferred coding languages with their data. Snowpark Container Services takes this further by allowing the use of third-party software, including generative AI models and data science libraries. “This potentially reduces complexity and infrastructure resource requirements,” Aslett said. Snowflake spent over a year moving Snowpark Container Services from private preview to general availability, focusing on governance, networking, usability, storage, observability, development operations, scalability, and performance. One customer, Landing AI, used Snowpark Container Services during its preview phases to develop LandingLens, an application for training and deploying computer vision models. “[With Snowflake], we are increasing access to AI for more companies and use cases, especially given the rapid growth of unstructured data in our increasingly digital world,” Landing AI COO Dan Maloney said in a statement Thursday. Future Plans With Snowpark Container Services now available on AWS, Snowflake plans to extend the feature to all cloud platforms. The vendor’s roadmap includes further improvements to Snowpark Container Services with more enterprise-grade tools. “Our team is investing in making it easy for companies ranging from startups to enterprises to build, deliver, distribute, and monetize next-generation AI products across their ecosystems,” Hollan said. Aslett said that making Snowpark Container Services available on Azure and Google Cloud is the logical next step. He noted that the managed service’s release is significant but needs broader availability beyond AWS regions. “The next step will be to bring Snowpark Container Services to general

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August 1, 2024in Snowflake
Standards in Healthcare Cybersecurity
27Jul

Standards in Healthcare Cybersecurity

The Change Healthcare cyberattack was a significant incident with widespread ramifications across the healthcare industry, with effects that are likely to persist for months or even longer. Standards in Healthcare Cybersecurity will change as a result. Since the ransomware attack on UnitedHealth Group’s (UHG) subsidiary, Change Healthcare, providers have faced financial and operational challenges due to disruptions in claims processing and other essential services. Change Healthcare, which processes 15 billion transactions annually and interacts with one in every three patient records in the U.S., is undergoing a complex and lengthy recovery process, with long-term implications for the industry. The attack was first reported on February 21st when Optum, another UHG subsidiary, alerted customers about the unavailability of some applications due to a cybersecurity issue. It was later confirmed that the BlackCat ransomware gang was responsible for the attack, which led to a $22 million ransom payment by UHG. The scale of the attack caused significant operational disruptions across the healthcare system, affecting entities ranging from large pharmacy chains to small, independently owned practices. In the weeks following the attack, UHG began restoring services, but the recovery process remains ongoing. UHG CEO Andrew Witty testified before Congress that the cybercriminals had gained access to Change Healthcare systems nine days before deploying the ransomware, using compromised credentials to access a Citrix portal without multi-factor authentication. The decision to pay the ransom was described as one of the hardest Witty has ever had to make. The incident has highlighted the vulnerabilities in healthcare cybersecurity, particularly for large organizations like UHG that handle vast amounts of sensitive data. It has also fueled the debate over whether ransomware payments should be made illegal, with arguments on both sides regarding the implications for victims and the broader cybersecurity landscape. The attack has prompted a strong response from industry groups and the federal government. The American Hospital Association (AHA) and the American Medical Association (AMA) have been vocal about the impact on providers, with the AHA calling it “the most significant and consequential cyberattack on the U.S. healthcare system in American history.” The federal government, through the Department of Health and Human Services (HHS), has provided guidance to Medicare providers and launched a formal investigation into the breach. As the healthcare industry continues to recover, the long-term impacts of the Change Healthcare cyberattack are expected to shape future cybersecurity strategies. The incident has underscored the importance of robust third-party risk management, the implementation of security measures like multi-factor authentication, and the potential need for more stringent regulatory standards in healthcare cybersecurity. The full extent of the breach, including the number of individuals affected, remains to be seen, but it is already clear that this event will have lasting repercussions for the industry. 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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July 27, 2024in Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Optimization
Implementing Salesforce Education Cloud
25Jul

Implementing Salesforce Education Cloud

Client OverviewThe client is a leading educational institution offering a wide array of programs, from undergraduate degrees to continuing education. With around 15,000 students and a global alumni network of over 50,000, they are dedicated to delivering a holistic educational experience while nurturing lifelong relationships with their alumni. ChallengesBefore implementing Salesforce Education Cloud, the client faced several large challenges: ObjectivesThe institution sought to achieve the following with Salesforce Education Cloud: Solution: Salesforce Education Expertise Strategy and Planning Design and Wireframing Development Testing Deployment Results: Before and After Aspect Before After Data Management Fragmented across multiple systems Centralized in Salesforce Education Cloud Communication Disjointed communication processes Streamlined internal and external channels Alumni Engagement Outdated tools for managing alumni relationships Modern tools for enhanced engagement Before and after Salesforce Education Cloud Quantifiable OutcomesWith Salesforce Education Cloud, the client achieved: Implementing Salesforce Education CloudBy implementing Salesforce Education Cloud, the Salesforce partner delivered a transformative solution that surpassed the institution’s objectives. The integration of centralized data, enhanced communication processes, and modern alumni management tools led to: These impressive results highlight Tectonic’s commitment to providing expert Salesforce solutions that aid education clients achieve their strategic goals. Contact us today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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July 25, 2024in Data, Salesforce Education Cloud, Salesforce Implementation Services
Salesforce Workday Partnership
24Jul

Salesforce Workday Partnership

Salesforce and Workday Partner to Launch AI-Powered Employee Service Agent Salesforce (NYSE: CRM), the leading AI CRM platform, and Workday, Inc. (NASDAQ: WDAY), a leader in enterprise cloud applications for finance and HR, today announced a strategic partnership to develop a new AI-powered employee service agent. This solution will enhance employee experiences by automating routine tasks, providing personalized support, and delivering data-driven insights across Salesforce and Workday platforms. A Unified Data Foundation for Enhanced Employee Services The partnership will integrate HR and financial data from Workday with CRM data from Salesforce, creating a unified data foundation. This integration will enable the development of AI-driven use cases that increase productivity, reduce costs, and improve the employee experience. A key feature will be the seamless incorporation of Workday into Slack, allowing for enhanced automation and collaboration around HR and financial records, using AI. The new AI employee service agent, built on Salesforce’s Agentforce Platform and Einstein AI, alongside Workday AI, will cater to various employee service needs, such as onboarding, health benefits management, and career development. This agent will utilize a company’s data to interact with employees in natural language, offering personalized support and executing tasks based on trusted business rules and permissions. Enhancing Employee and Customer Success “The AI opportunity lies in augmenting employees and delivering exceptional customer experiences. Our collaboration with Workday will empower businesses to create remarkable experiences using generative and autonomous AI, allowing employees to efficiently find answers, learn new skills, solve problems, and take actions.” Marc Benioff, Chair and CEO of Salesforce Carl Eschenbach, CEO of Workday, highlighted the integration’s benefits: “By combining our platforms, data, and AI capabilities, we empower customers to deliver unmatched AI-powered employee experiences, leading to happier customers and substantial business value.” Key Features of the Partnership Benefits for Employees and Employers For Employees: For Employers: Sal Companieh, Chief Digital and Information Officer at Cushman & Wakefield, noted the strategic advantage: “The integration of Workday and Salesforce will streamline workflows and deliver more personalized, AI-powered employee experiences, significantly enhancing our operational efficiency.” “The shared data foundation between Workday and Salesforce will enable these partners to deliver transformative AI capabilities, enhancing employee experiences and driving business performance.” R “Ray” Wang, CEO of Constellation Research, Inc. About Workday Workday is a leading enterprise platform that helps organizations manage their most important assets – their people and money. The Workday platform is built with AI at the core to help customers elevate people, supercharge work, and move their business forever forward. Workday is used by more than 10,500 organizations around the world and across industries – from medium-sized businesses to more than 60% of the Fortune 500. For more information about Workday, visit workday.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

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July 24, 2024in Einstein 1 Platform, Salesforce Data Cloud, Salesforce Einstein, Salesforce Implementation Services, Salesforce Slack
AI in Drug Research
23Jul

AI in Drug Research

Insights on Leveraging AI in Biopharmaceutical R&D: A Discussion with Kailash Swarna Last month, Accenture released a report titled “Reinventing R&D in the Age of AI,” which explores how biopharmaceutical companies can harness artificial intelligence (AI) and other advanced technologies to enhance drug and therapeutic research and development. AI in Drug Research. Kailash Swarna, managing director and Accenture Life Sciences Global Research and Clinical lead, spoke with PharmaNewsIntelligence about the report’s findings and how AI can address ongoing challenges in research and development (R&D), while offering a return on technological investments. “Data and analytics are crucial in advancing drug development, from early research to late-stage clinical trials,” said Swarna. “The industry still faces significant challenges, including the time and cost required to bring a medicine to market. As a leading technology firm, it’s our role to leverage the best in data analytics and technology for drug discovery and development.” AI in Drug Research Accenture conducted detailed interviews with leaders from biopharma companies to explore AI’s role in drug development and discovery. These interviews were part of a CEO forum held just before the JP Morgan conference, where technology emerged as a major area of opportunity and concern. Key Challenges in R&D Understanding the challenges in the drug R&D landscape is crucial for identifying how AI can be effectively utilized. Swarna highlighted several significant challenges: 1. Scientific Growth “The rapid advances in biology and disease understanding present both opportunities and challenges,” Swarna noted. “While our knowledge of human disease has greatly improved, keeping pace with scientific progress in terms of executing and reducing the time and cost of bringing new therapeutics to market remains a major challenge.” He described the clinical trial process as “fraught with complexities,” including data management issues. Despite industry efforts to accelerate drug development, it often still takes over a decade and billions of dollars. 2. Macroeconomic Factors Drug R&D companies also face challenges from macroeconomic conditions, such as reimbursement issues and the Inflation Reduction Act in the US. “These factors are reshaping how companies approach their portfolios and the disease areas they target,” Swarna explained. “The industry is undergoing a retooling to address these economic impacts.” 3. Technology Optimization Many companies have made substantial technology investments, but integrating and systematically utilizing these technologies across the entire R&D process remains a challenge. “While individual technology investments have been valuable, there is a significant opportunity to unify these efforts and streamline data usage from early research through late-stage development,” Swarna said. Reinventing R&D with AI The report emphasizes that technological advancements, particularly generative AI and analytics, can revolutionize the R&D pipeline. “This isn’t about a single technology but about a comprehensive rethinking of processes, data flows, and technology investments across the entire R&D spectrum,” Swarna stated. He stressed that the reinvention of R&D processes requires an enterprise-wide strategy and implementation. Responsible AI Swarna also highlighted the importance of addressing potential challenges associated with AI. “At Accenture, we have a robust responsible AI framework,” he said. Responsible AI encompasses managing issues like bias and security. Accenture’s framework considers factors such as choosing appropriate patient populations and understanding how bias might impact research data. It also addresses security concerns, including intellectual property protection and patient privacy. “Protecting patient privacy and complying with global regulations is crucial when utilizing AI technology,” Swarna emphasized. “Without proper safeguards, we risk data loss or breaches.” Measuring ROI of AI in Drug Research To ensure that AI technologies positively impact the R&D lifecycle, Swarna described a framework for measuring return on investment (ROI). “Given the long cycle of our industry, we’ve developed objective measures to evaluate the impact of these technologies on cost and time,” he explained. Companies can use quantitative measures to track interim milestones, such as recruitment costs and speeds. “These metrics allow us to observe progress in smaller increments rather than waiting for end-to-end results,” Swarna said. “The approach varies by company and their stage in implementing these technologies.” Benefits of AI in Clinical Trials Incorporating AI into clinical trials has the potential to reduce research times and costs. While Swarna and Accenture cannot predict policy impacts on drug pricing, he offered a theoretical benefit: optimizing technology could lower development costs, potentially making medicines more affordable and accessible. Swarna noted that reducing R&D spending could lead to more effective drugs being available to larger populations without placing an excessive burden on the healthcare system. For further details, the original report and discussion were published by Accenture and can be accessed on their official site. AI in Drug Research. 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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July 23, 2024in Generative AI
Metadata and Salesforce
14Jul

Metadata and Salesforce

How do I manage metadata in Salesforce? Search Setup for Custom Metadata Types. On the All Custom Metadata Types page, click Manage Records next to the custom metadata type for which you want to add or modify records. On the list of custom metadata records, click New, or click Edit to modify an existing custom metadata record. Fill out the fields. Use Metadata API to retrieve, deploy, create, update or delete customization information, such as custom object definitions and page layouts, for your org. This API is intended for managing customizations and for building tools that can manage the metadata model, not the data itself. Understanding Metadata Metadata encompasses various elements such as database objects and fields, screen layouts, automation rules, reporting structures, and access permissions. These elements, among others, form the overall configuration of an application for an organization. In large organizations, there can be over 100,000 metadata configurations with numerous dependencies between them. The Importance of Metadata Management As configurations grow, effective metadata management becomes crucial. Without it, the ability to make swift changes diminishes. Forrester describes this challenge as the “Salesforce@scale dilemma,” highlighting the complexities organizations face when scaling their use of Salesforce. This issue isn’t unique to Salesforce but applies to any metadata-driven enterprise application: “Every app change risks breaking one of hundreds of data and process customizations, integration links, and third-party add-ons. The result: Every change requires long and expensive impact-analysis and regression testing projects—killing the responsiveness that made Salesforce attractive at the start.” The Change Intelligence Report Series from Elements.cloud quantified Forrester’s observations: 50% of custom databases are never used, and 41% of custom-created fields are never populated. This leads to wasted effort and increased technical debt. Reducing this debt requires better metadata control. Establishing a Metadata Dictionary At the core of any metadata-driven app is a metadata dictionary, which AI can significantly enhance. A metadata dictionary is a comprehensive list of all metadata, grouped by type, with detailed attributes for each item such as version, usage, and dependencies. It can also include third-party content like business analysis, design specifications, and training materials. Managing applications without a metadata dictionary can be inefficient and risky. The common alternative, using spreadsheets, is hard to maintain and lacks support for impact analysis. Enterprise application vendors should include a metadata dictionary in their platforms, though many do not, often leaving it to third parties to create one via APIs. Steps to Establish a Metadata Dictionary Creating a metadata dictionary involves several actionable steps that streamline data management and boost productivity. Salesforce Metadata Salesforce metadata defines how objects and records behave and the “look and feel” of your Salesforce org. It includes: Metadata and Salesforce It’s essential to distinguish between metadata and data: For example, metadata can define schema properties (e.g., fields in a standard object like Address) and how business data is presented and processed. Metadata API Functionality The Metadata API allows you to manage and move metadata between Salesforce orgs during development. It supports: Use Metadata API for the final stages of development, and source push and pull commands for intermediate stages. These methods ensure efficient and accurate metadata management, enhancing the overall agility and scalability of your Salesforce environment. By effectively managing metadata, organizations can minimize technical debt, streamline operations, and maintain the flexibility and responsiveness that make platforms like Salesforce valuable. 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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July 14, 2024in Salesforce
Generative AI for Tableau
11Jul

Generative AI for Tableau

Tableau’s first generative AI assistant is now generally available. Generative AI for Tableau brings data prep to the masses. Earlier this month, Tableau launched its second platform update of 2024, announcing that its first two GenAI assistants would be available by the end of July, with a third set for release in August. The first of these, Einstein Copilot for Tableau Prep, became generally available on July 10. Tableau initially unveiled its plans to develop generative AI capabilities in May 2023 with the introduction of Tableau Pulse and Tableau GPT. Pulse, an insight generator that monitors data for metric changes and uses natural language to alert users, became generally available in February. Tableau GPT, now renamed Einstein Copilot for Tableau, moved into beta testing in April. Following Einstein Copilot for Tableau Prep, Einstein Copilot for Tableau Catalog is expected to be generally available before the end of July. Einstein Copilot for Tableau Web Authoring is set to follow by the end of August. With these launches, Tableau joins other data management and analytics vendors like AWS, Domo, Microsoft, and MicroStrategy, which have already made generative AI assistants generally available. Other companies, such as Qlik, DBT Labs, and Alteryx, have announced similar plans but have not yet moved their products out of preview. Tableau’s generative AI capabilities are comparable to those of its competitors, according to Doug Henschen, an analyst at Constellation Research. In some areas, such as data cataloging, Tableau’s offerings are even more advanced. “Tableau is going GA later than some of its competitors. But capabilities are pretty much in line with or more extensive than what you’re seeing from others,” Henschen said. In addition to the generative AI assistants, Tableau 2024.2 includes features such as embedding Pulse in applications. Based in Seattle and a subsidiary of Salesforce, Tableau has long been a prominent analytics vendor. Its first 2024 platform update highlighted the launch of Pulse, while the final 2023 update introduced new embedded analytics capabilities. Generative AI assistants are proliferating due to their potential to enable non-technical workers to work with data and increase efficiency for data experts. Historically, the complexity of analytics platforms, requiring coding and data literacy, has limited their widespread adoption. Studies indicate that only about one-quarter of employees regularly work with data. Vendors have attempted to overcome this barrier by introducing natural language processing (NLP) and low-code/no-code features. However, NLP features have been limited by small vocabularies requiring specific business phrasing, while low-code/no-code features only support basic tasks. Generative AI has the potential to change this dynamic. Large language models like ChatGPT and Google Gemini offer extensive vocabularies and can interpret user intent, enabling true natural language interactions. This makes data exploration and analysis accessible to non-technical users and reduces coding requirements for data experts. In response to advancements in generative AI, many data management and analytics vendors, including Tableau, have made it a focal point of their product development. Tech giants like AWS, Google, and Microsoft, as well as specialized vendors, have heavily invested in generative AI. Einstein Copilot for Tableau Prep, now generally available, allows users to describe calculations in natural language, which the tool interprets to create formulas for calculated fields in Tableau Prep. Previously, this required expertise in objects, fields, functions, and limitations. Einstein Copilot for Tableau Catalog, set for release later this month, will enable users to add descriptions for data sources, workbooks, and tables with one click. In August, Einstein Copilot for Tableau Web Authoring will allow users to explore data in natural language directly from Tableau Cloud Web Authoring, producing visualizations, formulating calculations, and suggesting follow-up questions. Tableau’s generative AI assistants are designed to enhance efficiency and productivity for both experts and generalists. The assistants streamline complex data modeling and predictive analysis, automate routine data prep tasks, and provide user-friendly interfaces for data visualization and analysis. “Whether for an expert or someone just getting started, the goal of Einstein Copilot is to boost efficiency and productivity,” said Mike Leone, an analyst at TechTarget’s Enterprise Strategy Group. The planned generative AI assistants for different parts of Tableau’s platform offer unique value in various stages of the data and AI lifecycle, according to Leone. Doug Henschen noted that the generative AI assistants for Tableau Web Authoring and Tableau Prep are similar to those being introduced by other vendors. However, the addition of a generative AI assistant for data cataloging represents a unique differentiation for Tableau. “Einstein Copilot for Tableau Catalog is unique to Tableau among analytics and BI vendors,” Henschen said. “But it’s similar to GenAI implementations being done by a few data catalog vendors.” Beyond the generative AI assistants, Tableau’s latest update includes: Among these non-Copilot capabilities, making Pulse embeddable is particularly significant. Extending generative AI capabilities to work applications will make them more effective. “Embedding Pulse insights within day-to-day applications promises to open up new possibilities for making insights actionable for business users,” Henschen said. Multi-fact relationships are also noteworthy, enabling users to relate datasets with shared dimensions and informing applications that require large amounts of high-quality data. “Multi-fact relationships are a fascinating area where Tableau is really just getting started,” Leone said. “Providing ways to improve accuracy, insights, and context goes a long way in building trust in GenAI and reducing hallucinations.” While Tableau has launched its first generative AI assistant and will soon release more, the vendor has not yet disclosed pricing for the Copilots and related features. The generative AI assistants are available through a bundle named Tableau+, a premium Tableau Cloud offering introduced in June. Beyond the generative AI assistants, Tableau+ includes advanced management capabilities, simplified data governance, data discovery features, and integration with Salesforce Data Cloud. Generative AI is compute-intensive and costly, so it’s not surprising that Tableau customers will have to pay extra for these capabilities. Some vendors are offering generative AI capabilities for free to attract new users, but Henschen believes costs will eventually be incurred. “Customers will want to understand the cost implications of adding these new capabilities,”

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July 11, 2024in Generative AI, Salesforce Data Cloud
Data Protection Improvements from Next DLP
11Jul

Data Protection Improvements from Next DLP

Insider risk and data protection company Next DLP has unveiled its new Secure Data Flow technology, designed to enhance data protection for customers. Integrated into the company’s Reveal Platform, Secure Data Flow monitors the origin, movement, and modification of data to provide comprehensive protection. Data Protection Improvements from Next DLP. This technology can secure critical business data flow from any SaaS application, including Salesforce, Workday, SAP, and GitHub, to prevent accidental data loss and malicious theft. “In modern IT environments, intellectual property often resides in SaaS applications and cloud data stores,” said John Stringer, head of product at Next DLP. “The challenge is that identifying high-impact data in these locations based on its content is difficult. Secure Data Flow, through Reveal, ensures that firms can confidently protect their most critical data assets, regardless of their location or application.” Next DLP argues that legacy data protection technologies are inadequate, relying on pattern matching, regular expressions, keywords, user-applied tags, and fingerprinting, which only cover a limited range of text-based data types. The company highlights that recent studies indicate employees download an average of 30 GB of data each month from SaaS applications to their endpoints, such as mobile phones, laptops, and desktops, emphasizing the need for advanced data protection measures. Secure Data Flow tracks data as it moves through both sanctioned and unsanctioned channels within an organization. By complementing traditional content and sensitivity classification-based approaches with origin-based data identification, manipulation detection, and data egress controls, it effectively prevents data theft and misuse. This approach results in an “all-encompassing, 100 percent effective, false-positive-free solution that simplifies the lives of security analysts,” claims Next DLP. “Secure Data Flow represents a novel approach to data protection and insider risk management,” said Ken Buckler, research director at Enterprise Management Associates. “It not only enhances detection and protection capabilities but also streamlines data management processes. This improves the accuracy of data sensitivity recognition and reduces endpoint content inspection costs in today’s diverse technological environments.” 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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July 11, 2024in Generative AI, Salesforce Data Cloud, Salesforce Optimization
Salesforce Data and AI Prevent Food Waste
05Jul

Salesforce Data and AI Prevent Food Waste

FareShare’s Tech-Driven Fight Against Food Waste and Insecurity Every year, around 10 million tons of perfectly edible surplus food goes to waste in the UK, while millions struggle to afford to have enough to eat. This waste not only exacerbates food poverty but also has a significant environmental impact, with greenhouse gases from rotten or wasted food accounting for about half of all global food system emissions. Salesforce Data and AI Prevent Food Waste. Charity FareShare is acutely aware of the severity of the situation. CEO George Wright emphasizes, “If food waste was a country, it would be the third biggest producer of global greenhouse gas emissions behind America and China.” Globally, 30% of food is wasted, and in the UK, it’s 25%, encompassing food thrown away at home, ploughed back into the ground, or wasted in the hospitality and retail industries. FareShare, which started 30 years ago, originally aimed to tackle this issue by redistributing surplus food that would otherwise go to waste. Now, FareShare operates 35 warehouses across the United Kingdom, employing around 600 people and 15,000 volunteers. They collect surplus food from 700 food companies and work with 8,500 charities to redistribute it to school clubs, community centers, and faith groups. Growth Amid Crisis Although FareShare had grown into a national organization, it was still relatively small when COVID-19 hit. Wright explains, “FareShare was about £3 million in terms of fundraising. COVID came and everything boomed.” During the pandemic, demand for FareShare’s services skyrocketed. Collaborations with high-profile figures like footballer Marcus Rashford brought more focus and support. The charity’s fundraising surged from £3 million to as high as £75 million before stabilizing at around £23 million. The amount of food distributed increased from 5,000 tons in the early days to 55,000 tons. The cost-of-living crisis has further exacerbated food insecurity, with the number of people in need more than doubling from six million to 13 million. Wright notes, “The bottom 20% of our society is economically cut adrift. Therefore, we’ve seen demand explode for more and more food. Last year, we did 55,000 tons, that’s 130 million meals. We could easily double or treble that if we had access to the food and the finance.” Salesforce Data and AI Prevent Food Waste To meet this growing demand, FareShare is ramping up its use of technology, particularly Salesforce. Over the past seven years, FareShare has utilized Salesforce’s Sales and Service Cloud to manage customer contacts and some food offers. Recently, FareShare conducted a full review of its operations and technology use, deciding to significantly increase its investment in Salesforce. FareShare is now exploring how Nonprofit Cloud and Data Cloud can benefit the organization. Wright explains, “Why reinvent the wheel? If there’s something great out there, use it and use it quickly.” Nonprofit Cloud provides FareShare with a unified view of its supporters, enabling better management of food and monetary donors. Data Cloud offers a centralized data source, replacing disparate spreadsheets, to improve data management. The aim is to have a holistic view of supporters, including donation history and preferences, to enhance their experience and demonstrate the impact of their contributions. AI components within Salesforce further boost productivity by suggesting tailored communications, drastically reducing the time required for tasks like crafting donor emails. Future Prospects FareShare is in the early stages of integrating Nonprofit Cloud and Data Cloud, aiming to establish these key systems before expanding into the full Salesforce ecosystem. Wright emphasizes the broader benefits of this partnership: “We’re not just getting the tools, we’re getting ways of working.” The primary objective for the additional Salesforce technology is improving fundraising. FareShare needs enhanced tech to scale its supporter base, generate more income, and effectively communicate the impact of donations. Wright envisions leveraging the wider Salesforce ecosystem to connect surplus food with charities in need, optimizing logistics to maximize social impact and minimize costs. The Bigger Picture FareShare sees AI playing a crucial role in tackling food waste and sustainability, potentially linking food sources and surplus across the country to charities in need. Wright concludes, “There’s more food wasted than we tackle and more charities that need more food. If we could connect those with a logistics solution, we could optimize for maximum use of food, minimum use of miles to get it to them. Maximum social impact, minimal cost. There’s a big tech opportunity there.” By harnessing the power of technology and strategic partnerships, FareShare aims to continue its mission to reduce food waste and food insecurity, creating a more sustainable and equitable future. Salesforce Data and AI Prevent Food Waste 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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July 5, 2024in Salesforce for Nonprofits
RevOps Sute for Salesforce Data Management
03Jul

RevOps Suite for Salesforce Data Management

Traction Complete Launches Revolutionary “RevOps Data Management Suite for Salesforce” In an era where artificial intelligence (AI) is revolutionizing business, Traction Complete is proud to announce the launch of “The RevOps Data Management Suite for Salesforce.” This groundbreaking suite is the first data management solution designed specifically for Revenue Operations professionals, empowering users to fully leverage their data by ensuring it is clean, connected, and ready for AI adoption. RevOps Sute for Salesforce Data Management. Importance of Data Integrity “The importance of clean and connected data can’t be stressed enough, especially in the age of AI. Without a solid foundation of reliable data, businesses are navigating in the dark, unable to make strategic decisions.” David Nelson, CEO of Traction Complete RevOps Suite for Salesforce Data Management Stephen Daniels, Vice President of Revenue Operations at Cresta, echoes this sentiment: “There is a cost to bad data. If we didn’t have a solution like Traction Complete in the first place to scale off, we would be building on a bad foundation that would cause hundreds of thousands of dollars of headaches in the future.” The Impact of Poor Data Poor data is more than just a nuisance; it’s a significant barrier to success. And it is expensive. It leads to distrust in CRM systems and lost productivity, ultimately impacting business revenue. Traction Complete’s mission is to tackle these challenges head-on, ensuring that data is accurate and seamlessly integrated across the Salesforce platform. This foundation enables businesses to adopt the latest technology seamlessly. Recent findings from McKinsey highlight the critical role of data quality in AI adoption: “Fifty-six percent of companies say ‘inaccuracy’ is the biggest risk posed by adopting generative AI. Yet only 32% of companies have systems in place for mitigating such inaccuracies.” Expertise and Innovation Traction Complete, born from the recently Salesforce-acquired Traction on Demand, draws on over 1.4 million hours of consulting experience to build trusted data management solutions that improve data quality. “At the pace that AI and machine learning are expanding and changing how we operate, businesses can’t afford to overlook the importance of data quality. Any businesses not setting their data foundation right now will be left behind,” adds Nelson. The Future of Data Management As organizations continue to navigate the complexities of digital transformation, the message is clear: the time to invest in data management is now. With the RevOps Data Management Suite for Salesforce, Traction Complete is leading the way, providing the tools necessary for businesses to thrive in the age of AI and beyond. 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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July 3, 2024in Generative AI, Salesforce, Salesforce Tableau

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