Generative AI - gettectonic.com - Page 9
Copado Unveils AI Agents
17Sep

Copado Unveils AI Agents

Copado Unveils AI Agents to Automate Key DevOps Tasks for Salesforce Applications Copado has introduced a suite of generative AI agents designed to automate common tasks that DevOps teams frequently encounter when building and deploying applications on Salesforce’s software-as-a-service (SaaS) platform. This announcement comes ahead of the Dreamforce 2024 conference hosted by Salesforce. These AI agents are the result of over a decade of data collection by Copado, according to David Brooks, Copado’s vice president of products. The initial AI agents will focus on code generation and test automation, with future agents tackling user story creation, deployment scripts, and application environment optimization. Unlike AI co-pilot tools that assist with code generation, Copado’s agents will fully automate tasks, Brooks explained. DevOps teams will be able to orchestrate these AI agents to streamline workflows, making best DevOps practices more accessible to a wider range of development teams. As AI continues to reshape DevOps, more tasks will be automated using agentic AI. This approach involves creating AI agents trained on a specific, narrow dataset, ensuring higher accuracy compared to general-purpose large language models (LLMs) that pull data from across the web. While it’s unclear how quickly agentic AI will transform DevOps, Brooks noted that in the future, teams will consist of both human engineers and AI agents assigned to specific tasks. DevOps engineers will still be essential for overseeing the accuracy of these tasks, but many of the repetitive tasks that often lead to burnout will be automated. As the burden of routine work decreases, organizations can expect the pace of code writing and application deployment to significantly accelerate. This could lead to a shift in how DevOps teams approach application backlogs, enabling the deployment of more applications that might have previously been sidelined due to resource constraints. In the interim, Brooks advises DevOps teams to begin identifying which routine tasks can be assigned to AI agents. Doing so will free up human engineers to manage workflows at a scale that was once unimaginable, positioning teams to thrive in the AI-driven future of DevOps. 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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September 17, 2024in Generative AI
Transformative Potential of AI in Healthcare
16Sep

Transformative Potential of AI in Healthcare

Healthcare leaders are increasingly optimistic about the transformative potential of AI and data analytics in the industry, according to a new market research report by Arcadia and The Harris Poll. The report, titled “The Healthcare CIO’s Role in the Age of AI,” reveals that 96% of healthcare executives believe AI adoption can provide a competitive edge, both now and in the future. While one-third of respondents see AI as essential today, 73% believe it will become critical within the next five years. How AI is Being Used in Healthcare The survey found that 63% of healthcare organizations are using AI to analyze large patient data sets, identifying trends and informing population health management. Additionally, 58% use AI to examine individual patient data to uncover opportunities for improving health outcomes. Nearly half of the respondents also reported using AI to optimize the management of electronic health records (EHRs). These findings align with a similar survey conducted by the University of Pittsburgh Medical Center’s Center for Connected Medicine (CCM), which highlighted AI as the most promising emerging technology in healthcare. The focus on AI stems from its ability to break down data silos and make use of the vast amount of clinical data healthcare organizations collect. “Healthcare leaders are preparing to harness AI’s full potential to reform care delivery,” said Aneesh Chopra, Arcadia’s chief strategy officer. “With secure data sharing scaling across the industry, technology leaders are focusing on platforms that can organize fragmented patient records into actionable insights throughout the patient journey.” Supporting Strategic Priorities with AI AI and data analytics are also seen as critical for maintaining competitiveness and resilience, particularly as organizations face digital transformation and financial challenges. In fact, 83% of respondents indicated that data-driven tools could help them stay ahead in these areas. Technology-related priorities, such as adopting an enterprise-wide approach to data analytics (44%) and enhancing decision-making through AI (41%), were top of mind for many healthcare leaders. Improving patient experience (40%), health outcomes (35%), and patient engagement (29%) were also highlighted as key strategic goals that AI could help achieve. Challenges in AI Adoption While most healthcare leaders are confident about adopting AI (96%), they also feel pressure to do so quickly, with the push primarily coming from data and analytics teams (82%), IT teams (78%), and executives (73%). One major obstacle is the lack of talent. Approximately 40% of respondents identified the shortage of skilled professionals as a top barrier to AI adoption. To address this, organizations are seeing increased demand for skills related to data analysis, machine learning, and systems integration. Additionally, 71% of IT leaders emphasized the growing need for data-driven decision-making skills. The Evolving Role of CIOs The rise of AI is reshaping the role of CIOs in healthcare. Nearly 87% of survey respondents see themselves as strategic influencers in setting and refining AI-related strategies, rather than just implementers. However, many CIOs feel constrained by the demands of day-to-day operations, with 58% reporting that tactical execution takes precedence over long-term AI strategy development. Leaders agree that to be effective, CIOs and their teams should focus more on strategic planning, dedicating around 75% of their time to developing and implementing AI strategies. Communication and workforce readiness are also crucial, with 75% of respondents citing poor communication between IT teams and clinical staff as a barrier to AI success, and 40% noting that clinical staff need more support to utilize data analytics effectively. “CIOs and their teams are setting the stage for an AI-driven transformation in healthcare,” said Michael Meucci, president and CEO of Arcadia. “The findings show that a robust data foundation and an evolving workforce are key to realizing AI’s full potential in patient care and healthcare operations.” 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 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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September 16, 2024in Generative AI, Salesforce Development Services, Salesforce Health and Life Sciences Solutions, Salesforce Optimization
Slack Personality Quiz
15Sep

Slack Personality Quiz

Slack has introduced a personality quiz, inspired by BuzzFeed-style formats, to understand how modern office workers interact with AI tools. Based on a survey of 5,000 full-time desk workers across six countries, the quiz categorizes users into five distinct groups based on their engagement with generative AI. From “The Rebel” to “The Maximalist,” these personas are designed to help business leaders organize teams more effectively by understanding how employees perceive and utilize AI. According to Christina Janzer, Slack’s SVP of research and analytics, the personas reflect the diverse ways workers are engaging with AI, emphasizing that there isn’t a one-size-fits-all approach. Interestingly, Slack’s recent survey revealed that while executive leadership is pushing AI adoption, two-thirds of workers have yet to use AI tools in their daily tasks. Among AI users, there’s a split between “Maximalists” (30% of respondents), who actively use AI and advocate for its benefits, and “The Underground” (20%), who also use AI regularly but more discreetly. For non-users, the personas include “Rebels” (19%), who avoid AI and remain skeptical, “Superfans” (16%), who admire AI advancements but haven’t adopted it themselves, and “Observers” (16%), who cautiously watch from the sidelines. Janzer noted demographic differences, such as a higher proportion of women and older individuals in the Rebel category, while Maximalists and Underground users tend to be younger men. Janzer emphasized that while these personas highlight current attitudes, they aren’t permanent. Businesses should take these insights into account when rolling out AI projects, ensuring they address the varied sentiments across their workforce. 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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September 15, 2024in Generative AI, Salesforce Slack
Impact of EHR Adoption
14Sep

Impact of EHR Adoption

Fueled by the availability of chatbot interfaces like Chat-GPT, generative AI has become a key focus across various industries, including healthcare. Many electronic health record (EHR) vendors are integrating the technology to streamline administrative workflows, allowing clinicians to focus more on patient care. Whether you see EHR adoption as easy or challenging, the Impact of EHR Adoption will be positive. Generative AI and EHR Efficiency As defined by the Government Accountability Office (GAO), generative AI is “a technology that can create content, including text, images, audio, or video, when prompted by a user.” Generative AI systems learn patterns from vast datasets, enabling them to generate new, similar content using machine learning algorithms and statistical models. One of the areas where generative AI shows promise is in automating EHR workflows, which could alleviate the burden on clinicians. Epic’s AI-Driven Innovations Phil Lindemann, vice president of data and analytics at Epic, noted that generative AI is ideal for automating repetitive tasks. One application under testing allows the technology to draft patient portal message responses for clinicians to review and send. This could save time and let doctors spend more time with patients. Another project focuses on summarizing updates to a patient’s record since their last visit, offering a quick synopsis for the provider. Epic is also exploring how generative AI could help patients better understand their health records by translating complex medical terms into more accessible language. Additionally, the system can translate this information into various languages, enhancing patient education across diverse populations. However, Lindemann emphasized that while AI offers valuable tools, it is not a cure-all for healthcare’s challenges. “We see it as a translation tool,” he said, acknowledging the importance of targeted use cases for successful implementation. Oracle Health’s Clinical Digital Assistant Oracle Health is beta-testing a generative AI chatbot aimed at reducing administrative tasks for healthcare professionals. The Clinical Digital Assistant summarizes patient information and generates automated clinical notes by listening to patient-provider conversations. Physicians can interact with the tool during consultations, asking for relevant patient data without breaking eye contact with the patient. The assistant can also suggest actions based on the discussion, which providers must review before finalizing. Oracle plans to make this tool widely available by the second quarter of 2024, with the goal of easing clinician workloads and improving the patient experience. eClinicalWorks and Ambient Listening Technology In partnership with sunoh.ai, eClinicalWorks is utilizing generative AI-powered ambient listening technology to assist with clinical documentation. This tool automatically drafts clinical notes based on patient conversations, which clinicians can then review and edit as necessary. Girish Navani, CEO of eClinicalWorks, highlighted the potential for generative AI to become a personal assistant for doctors, streamlining documentation tasks and reducing cognitive load. The integration is expected to be available to customers in early 2024. MEDITECH’s AI-Powered Discharge Summaries MEDITECH is collaborating with Google to develop a generative AI tool focused on automating hospital discharge summaries. These summaries, which are crucial for care coordination, are often time-consuming for clinicians to create, especially for patients with longer hospital stays. The AI system generates draft summaries that clinicians can review and edit, aiming to speed up discharges and reduce clinician burnout. MEDITECH is working with healthcare organizations to validate the technology before a general release. Helen Waters, executive vice president and COO of MEDITECH, stressed the importance of careful implementation. The goal is to ensure accuracy and build trust among clinicians so that generative AI can be successfully integrated into clinical workflows. The Impact of EHR Adoption EHR systems have transformed healthcare, improving care coordination and decision support. However, EHR-related administrative burdens have also contributed to clinician burnout. A 2019 study found that 40% of physician burnout was linked to EHR use. By automating time-consuming EHR tasks, generative AI could help reduce this burden and improve clinical 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 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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September 14, 2024in Data, Generative AI, Google, Salesforce Health and Life Sciences Solutions, Salesforce Optimization, Technology
Acceptable AI Use Policies
14Sep

Acceptable AI Use Policies

With great power comes—when it comes to generative AI—significant security and compliance risks. Discover how AI acceptable use policies can safeguard your organization while leveraging this transformative technology. AI has become integral across various industries, driving digital operations and organizational infrastructure. However, its widespread adoption brings substantial risks, particularly concerning cybersecurity. A crucial aspect of managing these risks and ensuring the security of sensitive data is implementing an AI acceptable use policy. This policy defines how an organization handles AI risks and sets guidelines for AI system usage. Why an AI Acceptable Use Policy Matters Generative AI systems and large language models are potent tools capable of processing and analyzing data at unprecedented speeds. Yet, this power comes with risks. The same features that enhance AI efficiency can be misused for malicious purposes, such as generating phishing content, creating malware, producing deepfakes, or automating cyberattacks. An AI acceptable use policy is essential for several reasons: Crafting an Effective AI Acceptable Use Policy An AI acceptable use policy should be tailored to your organization’s needs and context. Here’s a general guide for creating one: Essential Elements of an AI Acceptable Use Policy A robust AI acceptable use policy should include: An AI acceptable use policy is not just a document but a dynamic framework guiding safe and responsible AI use within an organization. By developing and enforcing this policy, organizations can harness AI’s power while mitigating its risks to cybersecurity and data integrity, balancing innovation with risk management as AI continues to evolve and integrate into our digital landscapes. 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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September 14, 2024in Generative AI
E-Commerce Platform Improvement
13Sep

E-Commerce Platform Improvement

Section I: Problem Statement CVS Health is continuously exploring ways to improve its e-commerce platform, cvs.com. One potential enhancement is the implementation of a complementary product bundle recommendation feature on its product description pages (PDPs). For instance, when a customer browses for a toothbrush, they could also see recommendations for related products like toothpaste, dental floss, mouthwash, or teeth whitening kits. A basic version of this is already available on the site through the “Frequently Bought Together” (FBT) section. Traditionally, techniques such as association rule mining or market basket analysis have been used to identify frequently purchased products. While effective, CVS aims to go further by leveraging advanced recommendation system techniques, including Graph Neural Networks (GNN) and generative AI, to create more meaningful and synergistic product bundles. This exploration focuses on expanding the existing FBT feature into FBT Bundles. Unlike the regular FBT, FBT Bundles would offer smaller, highly complementary recommendations (a bundle includes the source product plus two other items). This system would algorithmically create high-quality bundles, such as: This strategy has the potential to enhance both sales and customer satisfaction, fostering greater loyalty. While CVS does not yet have the FBT Bundles feature in production, it is developing a Minimum Viable Product (MVP) to explore this concept. Section II: High-Level Approach The core of this solution is a Graph Neural Network (GNN) architecture. Based on the work of Yan et al. (2022), CVS adapted this GNN framework to its specific needs, incorporating several modifications. The implementation consists of three main components: Section III: In-Depth Methodology Part 1: Product Embeddings Module A: Discovering Product Segment Complementarity Relations Using GPT-4 Embedding plays a critical role in this approach, converting text (like product names) into numerical vectors to help machine learning models understand relationships. CVS uses a GNN to generate embeddings for each product, ensuring that relevant and complementary products are grouped closely in the embedding space. To train this GNN, a product-relation graph is needed. While some methods rely on user interaction data, CVS found that transaction data alone was not sufficient, as customers often purchase unrelated products in the same session. For example: Instead, CVS utilized GPT-4 to identify complementary products at a higher level in the product hierarchy, specifically at the segment level. With approximately 600 distinct product segments, GPT-4 was used to identify the top 10 most complementary segments, streamlining the process. Module B: Evaluating GPT-4 Output To ensure accuracy, CVS implemented a rigorous evaluation process: These results confirmed strong performance in identifying complementary relationships. Module C: Learning Product Embeddings With complementary relationships identified at the segment level, a product-relation graph was built at the SKU level. The GNN was trained to prioritize pairs of products with high co-purchase counts, sales volume, and low price, producing an embedding space where relevant products are closer together. This allowed for initial, non-personalized product recommendations. Part 2: User Embeddings To personalize recommendations, CVS developed user embeddings. The process involves: This framework is currently based on recent purchases, but future enhancements will include demographic and other factors. Part 3: Re-Ranking Scheme To personalize recommendations, CVS introduced a re-ranking step: Section IV: Evaluation of Recommender Output Given that CVS trained the model using unlabeled data, traditional metrics like accuracy were not feasible. Instead, GPT-4 was used to evaluate recommendation bundles, scoring them on: The results showed that the model effectively generated high-quality, complementary product bundles. Section V: Use Cases Section VI: Future Work Future plans include: 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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September 13, 2024in Generative AI
AI-Driven Chatbots in Education
11Sep

AI-Driven Chatbots in Education

As AI-driven chatbots enter college courses, the potential to offer students 24/7 support is game-changing. However, there’s a critical caveat: when we customize chatbots by uploading documents, we don’t just add knowledge — we introduce biases. The documents we choose influence chatbot responses, subtly shaping how students interact with course material and, ultimately, how they think. So, how can we ensure that AI chatbots promote critical thinking rather than merely serving to reinforce our own viewpoints? How Course Chatbots Differ from Administrative Chatbots Chatbot teaching assistants have been around for some time in education, but low-cost access to large language models (LLMs) and accessible tools now make it easy for instructors to create customized course chatbots. Unlike chatbots used in administrative settings that rely on a defined “ground truth” (e.g., policy), educational chatbots often cover nuanced and debated topics. While instructors typically bring specific theories or perspectives to the table, a chatbot trained with tailored content can either reinforce a single view or introduce a range of academic perspectives. With tools like ChatGPT, Claude, Gemini, or Copilot, instructors can upload specific documents to fine-tune chatbot responses. This customization allows a chatbot to provide nuanced responses, often aligned with course-specific materials. But, unlike administrative chatbots that reference well-defined facts, course chatbots require ethical responsibility due to the subjective nature of academic content. Curating Content for Classroom Chatbots Having a 24/7 teaching assistant can be a powerful resource, and today’s tools make it easy to upload course documents and adapt LLMs to specific curricula. Options like OpenAI’s GPT Assistant, IBL’s AI Mentor, and Druid’s Conversational AI allow instructors to shape the knowledge base of course-specific chatbots. However, curating documents goes beyond technical ease — the content chosen affects not only what students learn but also how they think. The documents you select will significantly shape, though not dictate, chatbot responses. Combined with the LLM’s base model, chatbot instructions, and the conversation context, the curated content influences chatbot output — for better or worse — depending on your instructional goals. Curating for Critical Thinking vs. Reinforcing Bias A key educational principle is teaching students “how to think, not what to think.” However, some educators may, even inadvertently, lean toward dictating specific viewpoints when curating content. It’s critical to recognize the potential for biases that could influence students’ engagement with the material. Here are some common biases to be mindful of when curating chatbot content: While this list isn’t exhaustive, it highlights the complexities of curating content for educational chatbots. It’s important to recognize that adding data shifts — not erases — inherent biases in the LLM’s responses. Few academic disciplines offer a single, undisputed “truth.” AI-Driven Chatbots in Education. Tips for Ethical and Thoughtful Chatbot Curation Here are some practical tips to help you create an ethically balanced course chatbot: This approach helps prevent a chatbot from merely reflecting a single perspective, instead guiding students toward a broader understanding of the material. Ethical Obligations As educators, our ethical obligations extend to ensuring transparency about curated materials and explaining our selection choices. If some documents represent what you consider “ground truth” (e.g., on climate change), it’s still crucial to include alternative views and equip students to evaluate the chatbot’s outputs critically. Equity Customizing chatbots for educational use is powerful but requires deliberate consideration of potential biases. By curating diverse perspectives, being transparent in choices, and refining chatbot content, instructors can foster critical thinking and more meaningful student engagement. AI-Driven Chatbots in Education AI-powered chatbots are interactive tools that can help educational institutions streamline communication and improve the learning experience. They can be used for a variety of purposes, including: Some examples of AI chatbots in education include: While AI chatbots can be a strategic move for educational institutions, it’s important to balance innovation with the privacy and security of student data.  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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September 11, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Generative AI, Salesforce Education Cloud, Salesforce Education Solutions
Salesforce Healthcare and AI
11Sep

Salesforce Healthcare and AI

The Healthcare Industry’s Digital Transformation: An Opportunity Unveiled – Salesforce Healthcare and AI Historically, the healthcare sector has lagged behind in technology adoption, particularly software. It consistently invests less in IT and software compared to other industries, relying heavily on manual processes and outdated tools like faxes and phone calls. Unlike other sectors where platforms like Salesforce, Slack, JIRA, and Notion dominate, healthcare has yet to see similar technological integration. Salesforce Healthcare and AI Future While this low adoption of software has previously been seen as a drawback, it now presents a significant opportunity. Unlike industries burdened by extensive investments in legacy systems, healthcare is not encumbered by sunk costs. This freedom allows it to embrace cutting-edge AI innovations without the hesitation of overhauling existing, expensive software infrastructures. Addressing the Staffing Crisis The healthcare industry is grappling with a severe staffing crisis, with a shortfall of over 100,000 doctors and nurses projected over the next five years. The increasing complexity of medical care, driven by advancements in diagnostics, continuous monitoring, and new treatments, contributes to an overwhelming amount of information for clinicians. To manage this, healthcare requires new tools capable of processing complex data in real-time to support critical decisions for an aging population with more complex health needs. The most valuable asset in healthcare is clinical judgment, which is currently exclusive to human practitioners. A major challenge is to extend this clinical judgment beyond the existing workforce and physical locations, making it accessible to all who need it. Additionally, ensuring that every clinician performs at the highest level is crucial. The Role of Administrative and Clinical AI Administrative AI is essential for reducing the overhead of healthcare delivery, allowing for better resource management and efficiency. Clinical AI products, though challenging to develop due to their high-stakes nature, are uniquely positioned to address these needs. They must integrate seamlessly into existing environments, adding a layer of sophistication to healthcare processes. Regulatory Advantages for Clinical AI One of healthcare’s advantages in adopting AI is its well-established regulatory framework. The FDA has approved numerous clinical AI products and is developing processes to keep pace with advancements in machine learning and generative AI. This rigorous approval process ensures that only the most reliable and clinically sound products make it to market, creating a higher barrier to entry but also a stronger competitive advantage for those that succeed. The Scale of Opportunity The healthcare industry is a massive $4 trillion+ market, predominantly driven by human labor rather than technology. Historically, enterprise software companies have struggled to penetrate this sector, as IT budgets represent just 3.5% of revenue—less than half of that in financial services. However, with AI tools advancing rapidly, they are increasingly seen as “AI staff” rather than mere software. This shift opens up opportunities not just in software but in transforming service delivery, potentially disrupting a market valued in trillions rather than billions. The scale of this opportunity far exceeds past software ventures, as reflected in the significant capital and valuations flowing into AI-driven healthcare companies. Whether you’re launching a new clinic, developing infrastructure for the healthcare system, or creating innovative payment or insurance models, now is an unprecedented time to enter the healthcare space. The transformative power of AI is poised to redefine how healthcare companies are built, scaled, and brought to market. 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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September 11, 2024in Generative AI, Life Sciences Cloud, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Managed Services, Salesforce Optimization
Oracle Fusion Cloud
11Sep

Oracle Fusion Cloud

Oracle has unveiled over 50 role-based AI agents in the Oracle Fusion Cloud Applications Suite as of Wednesday. This suite offers a range of applications designed to help enterprises manage various functions. The newly introduced AI agents aim to assist employees and managers by automating business processes. According to Oracle executives at the CloudWorld 2024 conference in Las Vegas, these agents are tailored to improve efficiency across different functions. In Oracle Fusion Cloud Human Capital Management, the AI agents support shift scheduling, assist with hiring, manage requests to fill or create new positions, and help employees understand their benefits. In Oracle Fusion Cloud Supply Chain, Manufacturing AI Agents provide contextual insights and recommendations for handling order requests and suggest maintenance and repair actions for various assets. The AI agents within Oracle Fusion Cloud Customer Experience assist with planning and research tasks, automate contract workflow and approval processes, and facilitate communication with sales representatives. Oracle has yet to announce the release date for these AI agents. The Next Stage of GenAIThe introduction of AI agents represents an evolution of generative AI, moving beyond chatbots to technology that performs tasks autonomously. “These AI agents are engineered to automate routine tasks and offer personalized insights and recommendations,” noted Sid Nag, Gartner Research analyst. This development underscores a shift in the generative AI market from ideation to practical implementation. “These are very pragmatic and practical ideas,” said Mark Beccue, an analyst at TechTarget’s Enterprise Strategy Group. “It’s a use case we’ve been anticipating, where AI helps complete tasks effectively.” Oracle’s AI Agents for its Fusion Cloud Applications Suite align with the vision for enterprise software vendors, Beccue added. ServiceNow AI AgentsOracle is not alone in embedding AI agents into business applications. On September 10, ServiceNow announced plans to integrate agentic workflows into its platform. The initial AI Agent applications from ServiceNow will focus on Customer Service Management and IT Service Management. These agents are designed to identify and resolve issues independently while still being overseen by human operators. ServiceNow’s AI Agents are expected to launch in November 2024 as part of a limited release. The company also introduced the Now Assist Skill Kit, enabling enterprises to develop custom generative AI skills tailored to specific business needs. Single Task vs. Multitask AgentsA key consideration with AI agents is whether they can handle single tasks or multitask across multiple applications. Mark Beccue suggests that the ability to perform tasks across various applications could lead to a new user interface where AI agents manage tasks seamlessly across different systems. “It’s a vision for the future of AI agents,” Beccue remarked. It remains to be seen how these AI agents will address industry-specific regulations and compliance requirements, particularly in highly regulated sectors such as finance. Additional AI FeaturesOracle has also introduced new AI capabilities in other applications. Oracle Cloud ERP now includes predictive cash forecasting, narrative reporting, and automated transaction records within Oracle Fusion Cloud Sustainability. In Oracle Cloud CX, new features include assisted authoring to help sales teams engage buyers with AI-generated content and advanced AI capabilities in Oracle CX Unity for detecting signals based on role, title, and topic engagement. 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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September 11, 2024in Generative AI
Salesforce Industries AI
10Sep

Salesforce Industries AI

Salesforce has introduced Industries AI, a suite of foundational, pre-built, and customizable AI capabilities designed to address specific industry needs and challenges. This innovation aims to help customers quickly realize value by automating tasks such as matching patients to clinical trials, providing proactive maintenance alerts for vehicles and machinery, streamlining inventory management, and enhancing services for citizens and program beneficiaries. Industries AI is integrated into all 15 of Salesforce’s industry clouds, offering ready-to-use solutions for a range of sector-specific tasks. To assist customers in getting started, Salesforce has launched the AI Use Case Library, which features over 100 Industries AI capabilities. This library includes dedicated resources and use case guides for each industry cloud. The library will be regularly updated with new capabilities, such as Complaint Summaries, Patient Services & Benefits Verification, and Vehicle Telemetry Summary. Industries AI also lays the groundwork for industry-specific Agentforce agents, which will transform workflows across various roles and scales. These agents, available soon in every industry cloud, can be set up in minutes to autonomously handle business tasks, drawing on CRM data, external data, and metadata. They adhere to privacy and security guidelines and can seamlessly transfer complex cases to human agents with relevant context. As organizations increasingly recognize the urgency of adopting AI—up 700% in the last six months—Industries AI addresses the challenge of building and training AI models, which can be costly and time-consuming. By offering AI capabilities tailored to specific industry needs, Salesforce provides a cost-effective solution that delivers immediate value. Industries AI combines the robustness of an enterprise-grade platform with Salesforce’s deep industry expertise. Built on the Salesforce platform, supported by Data Cloud and the Einstein Trust Layer, it ensures safety and security. Customers can leverage pre-built prompts and industry-specific data models to achieve relevant and contextual insights. Here are some of the new capabilities announced: Jeff Amann, EVP & GM of Salesforce Industries, emphasized the mission to provide practical AI solutions across all industries, enabling organizations to harness AI’s potential efficiently. Most of these features will be generally available between October 2024 and February 2025, with ongoing updates through Salesforce’s three annual releases. Generally Available Today: Available in October 2024: Available in Beta in October 2024: Generally Available in February 2025: 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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September 10, 2024in Generative AI, Life Sciences Cloud, Public Sector Solutions
Should AI Bug Us?
09Sep

Should AI Bug Us?

Today marks the 77th anniversary of the first computer bug, which occurred when a moth became lodged in the 25-ton Harvard Mark II. The incident led programmer Grace Hopper to file what is now recognized as the first bug report. Wait, you weren’t even alive yet? Which begs the question. Should AI Bug Us? If asked what the most popular topic on the internet is today, one might confidently answer: AI. This year has seen a variety of perspectives on the subject. Data scientist Stephanie Kirmer reminded readers that generative AI still hasn’t become profitable. Margaret Efron highlighted words that give away AI-generated content (such as the overuse of “robust”). Meanwhile, Jim the AI Whisperer addressed a quirky tendency of ChatGPT to overuse the word “delve” due to its reliance on British English in its training data. Beyond these discussions, a deeper conversation is emerging about what AI means for humanity on an existential level. Writers are increasingly considering how AI impacts our perception of ourselves. Paul Siemers, PhD, who focuses on the philosophy of technology, explores this topic in his essay The Ontological Shock of AI. Ontology, the study of existence, traces how humans have categorized the world over millennia. Siemers notes that over the last two centuries, humanity has split existence into living and non-living categories. However, AI is starting to blur those lines. He argues that humanity needs to reconsider this dualistic view and accept new forms of existence. As unsettling as this may seem, it could explain part of society’s current discomfort with AI. Katharine Esty, PhD, who celebrated her 90th birthday this summer, published a guide for navigating life in your 80s. Her reflections on life and reinvention offer inspiration to readers of all ages. Practical Wisdom for Your Day: Live Life in Semesters A useful approach to structuring life is to think in “semesters”—15 to 17 weeks of focused work. This timeframe is long enough to accomplish something significant, but short enough to avoid burnout. 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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September 9, 2024in Generative AI
Army of AI Bots
09Sep

Army of AI Bots

Salesforce Inc. has announced a significant upgrade with the launch of Industries AI, a new automation platform designed to handle a wide range of time-consuming tasks, enhancing productivity across various sectors. We are NOT advocating that the next war will be fought with AI Bots. We aren’t even suggesting there is anything negative about these bots. However, if the next war were to be information and data based, who knows. Industries AI will be integrated into all 15 of Salesforce’s cloud platforms, including Sales Cloud, Data Cloud, Service Cloud, Commerce Cloud, and Marketing Cloud. This expansive solution is capable of managing over 100 common tasks, from matching patients with clinical trials and providing maintenance alerts for vehicles and machinery, to streamlining recruitment processes and enhancing government services. The launch of Industries AI responds to findings from Salesforce’s Trends in AI for CRM Report, which indicated that over 75% of business leaders are concerned about missing out on AI advancements if they do not adopt the technology soon. With a 700% increase in urgency to implement AI over the past six months, many organizations struggle with the resources and expertise needed to develop and train AI models. Salesforce aims to address this by offering a ready-made framework for creating AI agents tailored to industry-specific needs, utilizing each customer’s proprietary data within the Salesforce platform. Industries AI will provide a foundation for quickly deploying autonomous agents, with setup times estimated at just a few minutes. To assist customers in leveraging AI automation, Salesforce has created use case libraries for each of its cloud platforms, featuring over 100 capabilities at launch. These capabilities span multiple industries: Salesforce will begin rolling out Industries AI capabilities in October 2024, with some features available by February 2025. The company plans to regularly update Industries AI with new capabilities as part of its annual Salesforce releases. Jeff Amann, executive vice president and general manager of Salesforce Industries, emphasized that this innovation aims to make powerful AI accessible to all enterprises, regardless of size or budget. “Organizations can now easily start with AI solutions tailored to their specific challenges, enhancing efficiency and productivity across various functions,” he 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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September 9, 2024in Generative AI
Salesforce AI Agents Explained
09Sep

Salesforce AI Agents Explained

Salesforce’s AI Agents: Revolutionizing Enterprise Sales and Service for the Future In the rapidly evolving landscape of artificial intelligence (AI), Salesforce continues to lead the charge, transforming enterprise operations with cutting-edge AI agents. With the introduction of Agentforce, Salesforce is not just enhancing sales and service departments but reshaping business processes across sectors. This comprehensive exploration highlights how Salesforce’s AI agents are changing the game, offering enterprise-level executives insights into their revolutionary potential. Salesforce AI Agents Explained. AI Agents: Beyond Autonomous Vehicles A fitting analogy to grasp the progression of AI agents is the evolution of autonomous vehicles. Just as self-driving cars advance from basic driver assistance to full autonomy, AI agents evolve from simple automation to more complex decision-making. Salesforce’s Chief Product Officer, David Schmaier, draws this comparison: “In the autonomous driving world, we have levels of autonomy, from level zero to level five. AI agents for enterprises follow a similar path.” At the core of this evolution is what Salesforce defines as the “agentic” phase of AI. Unlike generative AI that follows instructions to create content, agentic AI autonomously determines and takes actions based on broader goals. Schmaier notes, “We’re at the point where AI not only creates content but takes strategic actions. It’s like having an infinite pool of interns handling mundane tasks so human employees can focus on higher-value activities.” Agentforce: Salesforce’s Next-Generation AI Platform Agentforce is the latest addition to Salesforce’s AI arsenal, unveiled during their Q2 ’25 earnings call and now positioned as a significant milestone in AI development. With Agentforce, organizations can build and manage autonomous agents for tasks across various business functions—not just customer service. This versatility is highlighted by Marc Benioff, Salesforce’s CEO, who described the energy around Agentforce during a recent briefing as “palpable.” Agentforce builds on Salesforce’s data management, security, and customization expertise, uniting these capabilities into an AI framework. Schmaier explains, “It’s about creating trusted, enterprise-ready agents, not just deploying a large language model. We’ve developed over 100 out-of-the-box use cases, from sales account summaries to service reply recommendations, all customizable and easy to deploy.” Agentforce “In Every App” A key announcement is the integration of Agentforce in every app across Salesforce’s product suite, including Sales, Service, Marketing, and Commerce Agents. The Atlas reasoning engine, Agent Builder, and a partner network were also introduced to further enhance its capabilities. The Atlas Reasoning Engine acts as the “brain” behind Agentforce, autonomously generating plans and refining them based on actions it needs to perform, such as running business processes or engaging customers through preferred channels. What Makes an AI Agent? Salesforce AI Agents Explained Building an AI agent with Agentforce requires five key elements: These components leverage existing Salesforce infrastructure, making it easier for businesses to deploy agents through Agent Builder, which is part of the new Agentforce Studio. Agents vs. Chatbots Unlike traditional chatbots, which provide pre-programmed responses, Salesforce’s AI agents use large language models (LLMs) and generative AI to interpret and autonomously execute customer requests based on CRM data. This distinction allows AI agents to perform tasks that go beyond simple queries, driving efficiency in customer service, sales, and other business areas. Practical Applications: Sales, Service, and Marketing Salesforce’s AI agents offer tangible business benefits. For instance, Sales Agent, available as both a Sales Development Representative (SDR) and Sales Coach, automates lead nurturing and inquiry management. It utilizes CRM data to deliver personalized pitches, handle objections, and even suggest meeting times—freeing sales teams to focus on more strategic tasks. In customer service, AI agents manage routine inquiries, allowing human representatives to address more complex customer needs. In marketing, AI agents generate data-driven insights to personalize campaigns, improving customer engagement and conversion rates. The Security and Trust Foundation Security and trust remain core to Salesforce’s approach to AI. The Einstein Trust Layer ensures that data protection, privacy, and ethical guidelines are maintained throughout AI interactions. Schmaier emphasizes, “Our platform defines what data agents can access and how they use it, adhering to strict data integrity standards.” The Trust Layer also prevents AI from training on customer data without consent, ensuring transparency and security. A Partnership Between Humans and AI-Salesforce AI Agents Explained Salesforce’s vision emphasizes the synergy between human employees and AI agents. As Schmaier points out, “AI agents handle routine tasks and deliver insights, allowing employees to focus on more creative and strategic work.” This human-AI partnership boosts productivity and innovation, ultimately improving business outcomes. The Future of AI in Business As AI technology advances, Salesforce is already working on next-generation capabilities for Agentforce, including predictive analytics and more sophisticated autonomous agents. Schmaier forecasts, “These agents will handle a wider range of tasks and provide deeper insights and recommendations.” With Agentforce launching in October 2024, businesses can expect significant returns on investment, thanks to its cost-efficient model starting at $2 per conversation. In summary, Salesforce’s Agentforce is a game-changing innovation, blending AI and human intelligence to transform sales, service, and marketing. As more details unfold, it’s clear that Agentforce will redefine the future of business operations—driving efficiency, personalization, and strategic success. 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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September 9, 2024in Agentforce Platform, Generative AI, Technology
Slack Expands AI Features
08Sep

Slack Expands AI Features

Slack is introducing several new AI-driven features, including the integration of AI-powered agents from Salesforce and other leading partners across the platform. The Big Picture: As part of its evolution, the Salesforce-owned company aims to position Slack as a hub where humans collaborate seamlessly with an increasing number of bots and AI agents. Key Updates: Ahead of Salesforce’s Dreamforce conference, Slack announced its support for agents from partners such as Adobe, Anthropic, Cohere, Perplexity, Writer, and more, alongside Salesforce’s own Agentforce. Additionally, Slack is enhancing its AI capabilities, expanding its AI-driven transcription features to include informal video chat sessions, known as “huddles.” Why It Matters: This move aligns with Salesforce’s broader strategy of leveraging generative AI to power autonomous agents that can take independent action, moving beyond the traditional role of AI as a co-pilot merely assisting humans. What They’re Saying: “Slack’s vision of becoming an AI-powered work operating system fits perfectly with the growing role of agents in the workplace,” said Slack CEO Denise Dresser in a statement to Axios. While Dresser didn’t disclose how many paying customers have adopted Slack’s AI features, it’s worth noting that these features require a separate monthly fee. Initially, Slack planned to require companies to pay for AI features for all users or none, but the company later shifted this approach following customer feedback. And Slack Expands AI Features with New Agent Integrations Slack is introducing several new AI-driven features, including the integration of AI-powered agents from Salesforce and other leading partners across the platform. The Big Picture: As part of its evolution, the Salesforce-owned company aims to position Slack as a hub where humans collaborate seamlessly with an increasing number of bots and AI agents. Key Updates: Ahead of Salesforce’s Dreamforce conference, Slack announced its support for agents from partners such as Adobe, Anthropic, Cohere, Perplexity, Writer, and more, alongside Salesforce’s own Agentforce. Additionally, Slack is enhancing its AI capabilities, expanding its AI-driven transcription features to include informal video chat sessions, known as “huddles.” Why It Matters: This move aligns with Salesforce’s broader strategy of leveraging generative AI to power autonomous agents that can take independent action, moving beyond the traditional role of AI as a co-pilot merely assisting humans. What They’re Saying: “Slack’s vision of becoming an AI-powered work operating system fits perfectly with the growing role of agents in the workplace,” said Slack CEO Denise Dresser in a statement to Axios. While Dresser didn’t disclose how many paying customers have adopted Slack’s AI features, it’s worth noting that these features require a separate monthly fee. Initially, Slack planned to require companies to pay for AI features for all users or none, but the company later shifted this approach following customer feedback. 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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September 8, 2024in Generative AI
EU AI Act
07Sep

EU AI Act

The EU AI Act is a complex piece of legislation, packed with various sections, definitions, and guidelines, making it challenging for organizations to navigate. However, understanding the EU AI Act is crucial for companies aiming to innovate with AI while staying compliant with both legal and ethical standards. Arnoud Engelfriet, chief knowledge officer at ICTRecht, an Amsterdam-based legal services firm, specializes in IT, privacy, security, and data law. As the head of ICTRecht Academy, he is responsible for educating others on AI legislation, including the AI Act. In his book AI and Algorithms: Mastering Legal and Ethical Compliance, published by Technics, Engelfriet explores the intersection of AI legislation and ethical AI development, using the AI Act as a key example. He emphasizes that while new AI guidelines can raise concerns about creativity and compliance, it’s quite necessary for organizations to grasp the current and future legal landscape to build trustworthy AI systems. Balancing Compliance and Innovation As of August 2024, the much-anticipated AI Act is in effect, with implementation timelines extending from six months to over a year. Many businesses worry that the regulations might slow down AI innovation, especially given the rapid pace of technological advancements. Engelfriet acknowledges this tension, noting that “compliance and innovation have always been somewhat at odds.” However, he believes the act’s flexible, tiered approach offers space for businesses to adapt. For instance, the inclusion of regulatory sandboxes allows companies to test AI systems safely, without releasing them into the market. Engelfriet suggests that while innovation might slow down, the safety and trustworthiness of AI systems will improve. Ensuring Trustworthy AI The AI Act aims to promote “trustworthy AI,” a term that became central to discussions after its inclusion in the first draft of the act in 2019. Although the concept remains somewhat undefined, the act outlines three key characteristics of trustworthy AI: legality, technical robustness, and ethical soundness. Engelfriet underscores that trust in AI systems is ultimately about trusting the humans behind them. “You cannot really trust a machine,” he explained, “but you can trust its designers and operators.” The AI Act requires transparency around how AI systems function, ensuring they reliably perform their intended tasks, such as making automated decisions or serving as chatbots. Ethics has gained even more prominence with the rise of generative AI. Engelfriet highlights the fragmented nature of AI ethics guidelines, which address everything from data protection to bias prevention. The EU’s Assessment List for Trustworthy AI provides a framework to guide organizations in applying ethical standards, though Engelfriet notes that it may need to be tailored to specific industry needs. The Role of AI Compliance Officers Given the complexity of AI regulations, organizations may find it overwhelming to manage compliance efforts. To meet this growing need, Engelfriet recommends appointing AI compliance officers to help companies integrate AI responsibly into their operations. ICTRecht has also developed a course, based on AI and Algorithms, to teach employees how to navigate AI compliance. Participants from various roles—particularly those in data, privacy, and risk functions—attend the course to expand their knowledge in this increasingly important area. Salesforce is developing Trailblazer content to address these challenges as well. As with GDPR, Engelfriet believes the AI Act will set the tone for future AI regulations. He advises businesses to proactively engage with the AI Act to ensure they are prepared for the evolving regulatory landscape. To get assistance exploring your EU risks, contact Tectonic 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 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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September 7, 2024in Generative AI

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