Dram - gettectonic.com
Google’s Gemini 1.5 Flash-8B

Google’s Gemini 1.5 Flash-8B

Google’s Gemini 1.5 Flash-8B: A Game-Changer in Speed and Affordability Google’s latest AI model, Gemini 1.5 Flash-8B, has taken the spotlight as the company’s fastest and most cost-effective offering to date. Building on the foundation of the original Flash model, 8B introduces key upgrades in pricing, speed, and rate limits, signaling Google’s intent to dominate the affordable AI model market. What Sets Gemini 1.5 Flash-8B Apart? Google has implemented several enhancements to this lightweight model, informed by “developer feedback and testing the limits of what’s possible,” as highlighted in their announcement. These updates focus on three major areas: 1. Unprecedented Price Reduction The cost of using Flash-8B has been slashed in half compared to its predecessor, making it the most budget-friendly model in its class. This dramatic price drop solidifies Flash-8B as a leading choice for developers seeking an affordable yet reliable AI solution. 2. Enhanced Speed The Flash-8B model is 40% faster than its closest competitor, GPT-4o, according to data from Artificial Analysis. This improvement underscores Google’s focus on speed as a critical feature for developers. Whether working in AI Studio or using the Gemini API, users will notice shorter response times and smoother interactions. 3. Increased Rate Limits Flash-8B doubles the rate limits of its predecessor, allowing for 4,000 requests per minute. This improvement ensures developers and users can handle higher volumes of smaller, faster tasks without bottlenecks, enhancing efficiency in real-time applications. Accessing Flash-8B You can start using Flash-8B today through Google AI Studio or via the Gemini API. AI Studio provides a free testing environment, making it a great starting point before transitioning to API integration for larger-scale projects. Comparing Flash-8B to Other Gemini Models Flash-8B positions itself as a faster, cheaper alternative to high-performance models like Gemini 1.5 Pro. While it doesn’t outperform the Pro model across all benchmarks, it excels in cost efficiency and speed, making it ideal for tasks requiring rapid processing at scale. In benchmark evaluations, Flash-8B surpasses the base Flash model in four key areas, with only marginal decreases in other metrics. For developers prioritizing speed and affordability, Flash-8B offers a compelling balance between performance and cost. Why Flash-8B Matters Gemini 1.5 Flash-8B highlights Google’s commitment to providing accessible AI solutions for developers without compromising on quality. With its reduced costs, faster response times, and higher request limits, Flash-8B is poised to redefine expectations for lightweight AI models, catering to a broad spectrum of applications while maintaining an edge in affordability. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
AI-Checking Agents

AI-Checking Agents

Introducing AI-Checking Agents: The Next Frontier in Software Quality Assurance The software industry has continually evolved in its pursuit of better quality assurance (QA) methods. While traditional approaches like unit testing and manual QA offer foundational tools, they often fail to meet the growing complexity of modern software. Automated testing and DevOps practices have helped, but these methods are still time-intensive, costly, and limited in scope. AI-Checking Agents. Enter AI-Checking Agents — an innovative solution leveraging generative AI to revolutionize software testing and quality assurance. These agents promise unprecedented coverage, speed, and efficiency, addressing the challenges of today’s demanding software ecosystems. Why AI-Checking Agents? Traditional QA methods fall short in delivering exhaustive coverage for the diverse behaviors and interactions of modern software. AI-Checking Agents close this gap by introducing: Synthetic Users: Revolutionizing User Experience (UX) Testing One of the most groundbreaking features of AI-Checking Agents is the ability to create synthetic users. These AI-driven personas simulate real-world user interactions, offering a novel approach to UX analysis. Key Features of Synthetic Users: UX Insights Delivered by Synthetic Users: Benefits of AI-Checking Agents in QA Integrating AI-Checking Agents with Existing QA Practices AI-Checking Agents are not a replacement for traditional methods but a powerful complement to existing practices: Transforming the Development Process AI-Checking Agents not only streamline QA but also enhance the overall development process: The Future of Quality Assurance AI-Checking Agents represent a paradigm shift in software testing, blending the best of AI-driven insights with traditional QA practices. By integrating these agents into their workflows, development teams can achieve: In a world of ever-evolving software demands, AI-Checking Agents are the key to achieving unparalleled speed, depth, and precision in quality assurance. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
Government CRM System

Salesforce Announces Top Secret Gov Cloud

This advanced cloud solution is hosted on Amazon Web Services’ Top Secret cloud infrastructure. According to Salesforce’s press release, Government Cloud Premium is built with an API-first architecture, enabling agencies to leverage other data sources and systems, including proprietary AI applications, to enhance mission-critical operations.

Read More
UX Principles for AI in Healthcare

UX Principles for AI in Healthcare

The Role of UX in AI-Driven Healthcare AI is poised to revolutionize the global economy, with predictions it could contribute $15.7 trillion by 2030—more than the combined economic output of China and India. Among the industries likely to see the most transformative impact is healthcare. However, during my time at NHS Digital, I saw how systems that weren’t designed with existing clinical workflows in mind added unnecessary complexity for clinicians, often leading to manual workarounds and errors due to fragmented data entry across systems. The risk is that AI, if not designed with user experience (UX) at the forefront, could exacerbate these issues, creating more disruption rather than solving problems. From diagnostic tools to consumer health apps, the role of UX in AI-driven healthcare is critical to making these innovations effective and user-friendly. This article explores the intersection of UX and AI in healthcare, outlining key UX principles to design better AI-driven experiences and highlighting trends shaping the future of healthcare. The Shift in Human-Computer Interaction with AI AI fundamentally changes how humans interact with computers. Traditionally, users took command by entering inputs—clicking, typing, and adjusting settings until the desired outcome was achieved. The computer followed instructions, while the user remained in control of each step. With AI, this dynamic shifts dramatically. Now, users specify their goal, and the AI determines how to achieve it. For example, rather than manually creating an illustration, users might instruct AI to “design a graphic for AI-driven healthcare with simple shapes and bold colors.” While this saves time, it introduces challenges around ensuring the results meet user expectations, especially when the process behind AI decisions is opaque. The Importance of UX in AI for Healthcare A significant challenge in healthcare AI is the “black box” nature of the systems. For example, consider a radiologist reviewing a lung X-ray that an AI flagged as normal, despite the presence of concerning lesions. Research has shown that commercial AI systems can perform worse than radiologists when multiple health issues are present. When AI decisions are unclear, clinicians may question the system’s reliability, especially if they cannot understand the rationale behind an AI’s recommendation. This opacity hinders feedback, making it difficult to improve the system’s performance. Addressing this issue is essential for UX designers. Bias in AI is another significant issue. Many healthcare AI tools have been documented as biased, such as systems trained on predominantly male cardiovascular data, which can fail to detect heart disease in women. AIs also struggle to identify conditions like melanoma in people with darker skin tones due to insufficient diversity in training datasets. UX can help mitigate these biases by designing interfaces that clearly explain the data used in decisions, highlight missing information, and provide confidence levels for predictions. The movement toward eXplainable AI (XAI) seeks to make AI systems more transparent and interpretable for human users. UX Principles for AI in Healthcare To ensure AI is beneficial in real-world healthcare settings, UX designers must prioritize certain principles. Below are key UX design principles for AI-enabled healthcare applications: Applications of AI in Healthcare AI is already making a significant impact in various healthcare applications, including: Real-world deployments of AI in healthcare have demonstrated that while AI can be useful, its effectiveness depends heavily on usability and UX design. By adhering to the principles of transparency, interpretability, controllability, and human-centered AI, designers can help create AI-enabled healthcare applications that are both powerful and user-friendly. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

Read More
How Skechers Solved Its Ecommerce Challenges

How Skechers Solved Its Ecommerce Challenges

Skechers Boosts Direct-to-Consumer Sales with Ecommerce Platform Upgrades Skechers, now a global brand in 2024, credits its recent ecommerce platform upgrades for saving time and increasing direct-to-consumer sales. However, it wasn’t always equipped with the right technology to support its massive growth. During Salesforce’s Dreamforce conference in San Francisco, Eric Cheng, Skechers USA Inc.’s director of ecommerce architecture, shared insights into how key technology decisions helped the brand expand and enhance its website and content capabilities. “Today, we’re present in over 180 countries worldwide,” Cheng said, speaking on stage at the Moscone Center. Skechers’ journey began in 1992, and its expansion has taken the brand across borders, reaching millions of customers worldwide. “We connect hundreds of millions of customers through our retail stores and ecommerce platform to deliver a unique experience,” Cheng noted, emphasizing the need to meet the diverse demands of each market. Skechers ranks No. 273 in the Top 1000, Digital Commerce 360’s ranking of the largest North American e-retailers by online sales, where it is categorized as an Apparel & Accessories retailer. Digital Commerce 360 projects that Skechers will reach 0.65 million in online sales by 2024. Ecommerce Platform Challenges Cheng acknowledged that Skechers’ digital transformation wasn’t immediate: “The journey did not just happen overnight; it took time and effort.” Skechers faced challenges in three key areas: content management, scalability, and customer experience. The legacy system was inadequate, lacking robust tools for efficient content delivery, previewing scheduled content, and handling localization. As Cheng described, launching a marketing page often required the content team to be on standby at midnight—an unsustainable approach for 17 countries. How Skechers Solved Its Ecommerce Challenges To overcome these hurdles, Skechers partnered with Astound Digital. Together, they implemented Salesforce Service Cloud and Manhattan Active Omni for order management. Kyle Montgomery, senior vice president of commerce at Astound Digital, joined Cheng on stage and highlighted the goal: “Their vision was to unify, supply, and scale.” This transformation enabled Skechers to bring 17 countries in Europe, Japan, and North America onto a single platform. Jennifer Lane, Salesforce’s director of success guides, also emphasized the flexibility achieved using Salesforce’s Page Designer and localization solutions from Salesforce’s AppExchange. Integrations with Thomson Reuters for tax, CyberSource for payments, and Salesforce Marketing Cloud for personalization further enhanced Skechers’ capabilities. The Results Cheng highlighted three key improvements after the ecommerce overhaul. First, content creation and localization tools improved operational efficiency by over 500%. The time to launch in new markets was dramatically reduced from five months to just a few weeks. Additionally, Skechers saw a notable sales boost, with a 24.5% increase in its direct-to-consumer segment during Q1 2023. Skechers’ success demonstrates the significant impact of a well-executed ecommerce platform upgrade, allowing the brand to scale globally while improving customer experience and operational efficiency. Contact Tectonic to learn what Salesforce can do for you. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
GPUs and AI Development

GPUs and AI Development

Graphics processing units (GPUs) have become widely recognized due to their growing role in AI development. However, a lesser-known but critical technology is also gaining attention: high-bandwidth memory (HBM). HBM is a high-density memory designed to overcome bottlenecks and maximize data transfer speeds between storage and processors. AI chipmakers like Nvidia rely on HBM for its superior bandwidth and energy efficiency. Its placement next to the GPU’s processor chip gives it a performance edge over traditional server RAM, which resides between storage and the processing unit. HBM’s ability to consume less power makes it ideal for AI model training, which demands significant energy resources. However, as the AI landscape transitions from model training to AI inferencing, HBM’s widespread adoption may slow. According to Gartner’s 2023 forecast, the use of accelerator chips incorporating HBM for AI model training is expected to decline from 65% in 2022 to 30% by 2027, as inferencing becomes more cost-effective with traditional technologies. How HBM Differs from Other Memory HBM shares similarities with other memory technologies, such as graphics double data rate (GDDR), in delivering high bandwidth for graphics-intensive tasks. But HBM stands out due to its unique positioning. Unlike GDDR, which sits on the printed circuit board of the GPU, HBM is placed directly beside the processor, enhancing speed by reducing signal delays caused by longer interconnections. This proximity, combined with its stacked DRAM architecture, boosts performance compared to GDDR’s side-by-side chip design. However, this stacked approach adds complexity. HBM relies on through-silicon via (TSV), a process that connects DRAM chips using electrical wires drilled through them, requiring larger die sizes and increasing production costs. According to analysts, this makes HBM more expensive and less efficient to manufacture than server DRAM, leading to higher yield losses during production. AI’s Demand for HBM Despite its manufacturing challenges, demand for HBM is surging due to its importance in AI model training. Major suppliers like SK Hynix, Samsung, and Micron have expanded production to meet this demand, with Micron reporting that its HBM is sold out through 2025. In fact, TrendForce predicts that HBM will contribute to record revenues for the memory industry in 2025. The high demand for GPUs, especially from Nvidia, drives the need for HBM as AI companies focus on accelerating model training. Hyperscalers, looking to monetize AI, are investing heavily in HBM to speed up the process. HBM’s Future in AI While HBM has proven essential for AI training, its future may be uncertain as the focus shifts to AI inferencing, which requires less intensive memory resources. As inferencing becomes more prevalent, companies may opt for more affordable and widely available memory solutions. Experts also see HBM following the same trajectory as other memory technologies, with continuous efforts to increase bandwidth and density. The next generation, HBM3E, is already in production, with HBM4 planned for release in 2026, promising even higher speeds. Ultimately, the adoption of HBM will depend on market demand, especially from hyperscalers. If AI continues to push the limits of GPU performance, HBM could remain a critical component. However, if businesses prioritize cost efficiency over peak performance, HBM’s growth may level off. 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 Alphabet Soup of Cloud Terminology As with any technology, the cloud brings its own alphabet soup of terms. This insight will hopefully help you navigate Read more

Read More
Revolution Customer Service with Agentforce

Revolution Customer Service with Agentforce

Agentforce stole the spotlight at Dreamforce, but it’s not just about replacing human workers. Equally significant for Service Cloud was the focus on how AI can be leveraged to make agents, dispatchers, and field service technicians more productive and proactive. Join a conversation to unpack the latest Sales Cloud innovations, with a spotlight on Agentforce for sales followed by a Q&A with Salesblazers. During the Dreamforce Service Cloud keynote, GM Kishan Chetan emphasized the dramatic shift over the past year, with AI moving from theoretical to practical applications. He challenged customer service leaders to embrace AI agents, highlighting that AI-driven solutions can transform customer service from delivering “good” benefits to achieving exponential growth. He noted that AI agents are capable of handling common customer requests like tech support, scheduling, and general inquiries, as well as more complex tasks such as de-escalation, billing inquiries, and even cross-selling and upselling. In practice, research by Valoir shows that most Service Cloud customers are still in the early stages of AI adoption, particularly with generative AI. While progress has accelerated recently, most companies are only seeing incremental gains in individual productivity rather than the exponential improvements highlighted at Dreamforce. To achieve those higher-level returns, customers must move beyond simple automation and summarization to AI-driven transformation, powered by Agentforce. Chetan and his team outlined four key steps to make this transition. “Agentforce represents the Third Wave of AI—advancing beyond copilots to a new era of highly accurate, low-hallucination intelligent agents that actively drive customer success. Unlike other platforms, Agentforce is a revolutionary and trusted solution that seamlessly integrates AI across every workflow, embedding itself deeply into the heart of the customer journey. This means anticipating needs, strengthening relationships, driving growth, and taking proactive action at every touchpoint,” said Marc Benioff, Chair and CEO, Salesforce. “While others require you to DIY your AI, Agentforce offers a fully tailored, enterprise-ready platform designed for immediate impact and scalability. With advanced security features, compliance with industry standards, and unmatched flexibility. Our vision is bold: to empower one billion agents with Agentforce by the end of 2025. This is what AI is meant to be.” In contrast to now-outdated copilots and chatbots that rely on human requests and strugglewith complex or multi-step tasks, Agentforce offers a new level of sophistication by operating autonomously, retrieving the right data on demand, building action plans for any task, and executing these plans without requiring human intervention. Like a self-driving car, Agentforce uses real-time data to adapt to changing conditions and operates independently within an organizations’ customized guardrails, ensuring every customer interaction is informed, relevant, and valuable. And when desired, Agentforce seamlessly hands off to human employees with a summary of the interaction, an overview of the customer’s details, and recommendations for what to do next. Deploy AI agents across channelsAgentforce Service Agent is more than a chatbot—it’s an autonomous AI agent capable of handling both simple and complex requests, understanding text, video, and audio. Customers were invited to build their own Service Agents during Dreamforce, and many took up the challenge. Service-related agents are a natural fit, as research shows Service Cloud customers are generally more prepared for AI adoption due to the volume and quality of customer data available in their CRM systems. Turn insights into actionLaunching in October 2024, Customer Experience Intelligence provides an omnichannel supervisor Wall Board that allows supervisors to monitor conversations in real time, complete with sentiment scores and organized metrics by topics and regions. Supervisors can then instruct Service Agent to dive into root causes, suggest proactive messaging, or even offer discounts. This development represents the next stage of Service Intelligence, combining Data Cloud, Tableau, and Einstein Conversation Mining to give supervisors real-time insights. It mirrors capabilities offered by traditional contact center vendors like Verint, which also blend interaction, sentiment, and other data in real time—highlighting the convergence of contact centers and Service Cloud service operations. Empower teams to become trusted advisorsSalesforce continues to navigate the delicate balance between digital and human agents, especially within Service Cloud. The key lies in the intelligent handoff of customer data when escalating from a digital agent to a human agent. Service Planner guides agents step-by-step through issue resolution, powered by Unified Knowledge. The demo also showcased how Service Agent can merge Commerce and Service by suggesting agents offer complimentary items from a customer’s shopping cart. Enable field teams to be proactiveSalesforce also announced improvements in field service, designed to help dispatchers and field service agents operate more proactively and efficiently. Agentforce for Dispatchers enhances the ability to address urgent appointments quickly. Asset Service Prediction leverages AI to forecast asset failures and upcoming service needs, while AI-generated prework briefs provide field techs with asset health scores and critical information before they arrive on site. Setting a clear roadmap for adopting Agentforce across these four areas is an essential step toward helping customers realize more than just incremental gains in their service operations. Equally important will be helping customers develop a data strategy that harnesses the power of Data Cloud and Salesforce’s partner ecosystem, enabling a truly data-driven service experience. Investments in capabilities like My Service Journeys will also be critical in guiding customers through the process of identifying which AI features will deliver the greatest returns for their specific needs. Agentforce leverages Salesforce’s generative AI, like Einstein GPT, to automate routine tasks, provide real-time insights, and offer personalized recommendations, enhancing efficiency and enabling agents to deliver exceptional customer experiences. Agentforce is not just another traditional chatbot; it is a next-generation, AI-powered solution that understands complex queries and acts autonomously to enhance operational efficiency. Unlike conventional chatbots, Agentforce is intelligent and adaptive, capable of managing a wide range of customer issues with precision. It offers 24/7 support, responds in a natural, human-like manner, and seamlessly escalates to human agents when needed and redefining customer service by delivering faster, smarter, and more effective support experiences. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM

Read More
Spotlight on Agentforce

Spotlight on Agentforce

Agentforce stole the spotlight at Dreamforce, but it’s not just about replacing human workers. Equally significant for Service Cloud was the focus on how AI can be leveraged to make agents, dispatchers, and field service technicians more productive and proactive. During the Dreamforce Service Cloud keynote, GM Kishan Chetan emphasized the dramatic shift over the past year, with AI moving from theoretical to practical applications. He challenged customer service leaders to embrace AI agents, highlighting that AI-driven solutions can transform customer service from delivering “good” benefits to achieving exponential growth. He noted that AI agents are capable of handling common customer requests like tech support, scheduling, and general inquiries, as well as more complex tasks such as de-escalation, billing inquiries, and even cross-selling and upselling. In practice, research by Valoir shows that most Service Cloud customers are still in the early stages of AI adoption, particularly with generative AI. While progress has accelerated recently, most companies are only seeing incremental gains in individual productivity rather than the exponential improvements highlighted at Dreamforce. To achieve those higher-level returns, customers must move beyond simple automation and summarization to AI-driven transformation, powered by Agentforce. Chetan and his team outlined four key steps to make this transition. Deploy AI agents across channelsAgentforce Service Agent is more than a chatbot—it’s an autonomous AI agent capable of handling both simple and complex requests, understanding text, video, and audio. Customers were invited to build their own Service Agents during Dreamforce, and many took up the challenge. Service-related agents are a natural fit, as research shows Service Cloud customers are generally more prepared for AI adoption due to the volume and quality of customer data available in their CRM systems. Turn insights into actionLaunching in October 2024, Customer Experience Intelligence provides an omnichannel supervisor Wall Board that allows supervisors to monitor conversations in real time, complete with sentiment scores and organized metrics by topics and regions. Supervisors can then instruct Service Agent to dive into root causes, suggest proactive messaging, or even offer discounts. This development represents the next stage of Service Intelligence, combining Data Cloud, Tableau, and Einstein Conversation Mining to give supervisors real-time insights. It mirrors capabilities offered by traditional contact center vendors like Verint, which also blend interaction, sentiment, and other data in real time—highlighting the convergence of contact centers and Service Cloud service operations. Empower teams to become trusted advisorsSalesforce continues to navigate the delicate balance between digital and human agents, especially within Service Cloud. The key lies in the intelligent handoff of customer data when escalating from a digital agent to a human agent. Service Planner guides agents step-by-step through issue resolution, powered by Unified Knowledge. The demo also showcased how Service Agent can merge Commerce and Service by suggesting agents offer complimentary items from a customer’s shopping cart. Enable field teams to be proactiveSalesforce also announced improvements in field service, designed to help dispatchers and field service agents operate more proactively and efficiently. Agentforce for Dispatchers enhances the ability to address urgent appointments quickly. Asset Service Prediction leverages AI to forecast asset failures and upcoming service needs, while AI-generated prework briefs provide field techs with asset health scores and critical information before they arrive on site. Setting a clear roadmap for adopting Agentforce across these four areas is an essential step toward helping customers realize more than just incremental gains in their service operations. Equally important will be helping customers develop a data strategy that harnesses the power of Data Cloud and Salesforce’s partner ecosystem, enabling a truly data-driven service experience. Investments in capabilities like My Service Journeys will also be critical in guiding customers through the process of identifying which AI features will deliver the greatest returns for their specific needs. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
Is Agentforce Different?

Is Agentforce Different?

The Salesforce hype machine is in full swing, with product announcements like Chatter, Einstein GPT, and Data Cloud, all positioned as revolutionary tools that promise to transform how we work. Is Agentforce Different? However, it’s often difficult to separate fact from fiction in the world of Salesforce. The cloud giant thrives on staying ahead of technological advancements, which means reinventing itself every year with new releases and updates. You could even say three times per year with the major releases. Why Enterprises Need Multiple Salesforce Orgs Over the past decade, Salesforce product launches have been hit or miss—primarily miss. Offerings like IoT Cloud, Work.com, and NFT Cloud have faded into obscurity. This contrasts sharply with Salesforce’s earlier successes, such as Service Cloud, the AppExchange, Force.com, Salesforce Lightning, and Chatter, which defined its first decade in business. One notable exception is Data Cloud. This product has seen significant success and now serves as the cornerstone of Salesforce’s future AI and data strategy. With Salesforce’s growth slowing quarter over quarter, the company must find new avenues to generate substantial revenue. Artificial Intelligence seems to be their best shot at reclaiming a leadership position in the next technological wave. Is Agentforce Different? While Salesforce has been an AI leader for over a decade, the hype surrounding last year’s Dreamforce announcements didn’t deliver the growth the company was hoping for. The Einstein Copilot Studio—comprising Copilot, Prompt Builder, and Model Builder—hasn’t fully lived up to expectations. This can be attributed to a lack of AI readiness among enterprises, the relatively basic capabilities of large language models (LLMs), and the absence of fully developed use cases. In Salesforce’s keynote, it was revealed that over 82 billion flows are launched weekly, compared to just 122,000 prompts executed. While Flow has been around for years, this stat highlights that the use of AI-powered prompts is still far from mainstream—less than one prompt per Salesforce customer per week, on average. When ChatGPT launched at the end of 2022, many predicted the dawn of a new AI era, expecting a swift and dramatic transformation of the workplace. Two years later, it’s clear that AI’s impact has yet to fully materialize, especially when it comes to influencing global productivity and GDP. However, Salesforce’s latest release feels different. While AI Agents may seem new to many, this concept has been discussed in AI circles for decades. Marc Benioff’s recent statements during Dreamforce reflect a shift in strategy, including a direct critique of Microsoft’s Copilot product, signaling the intensifying AI competition. This year’s marketing strategy around Agentforce feels like it could be the transformative shift we’ve been waiting for. While tools like Salesforce Copilot will continue to evolve, agents capable of handling service cases, answering customer questions, and booking sales meetings instantly promise immediate ROI for organizations. Is the Future of Salesforce in the Hands of Agents? Despite the excitement, many questions remain. Are Salesforce customers ready for agents? Can organizations implement this technology effectively? Is Agentforce a real breakthrough or just another overhyped concept? Agentforce may not be vaporware. Reports suggest that its development was influenced by Salesforce’s acquisition of Airkit.AI, a platform that claims to resolve 90% of customer queries. Salesforce has even set up dedicated launchpads at Dreamforce to help customers start building their own agents. Yet concerns remain, especially regarding Salesforce’s complexity, technical debt, and platform sprawl. These issues, highlighted in this year’s Salesforce developer report, cannot be overlooked. Still, it’s hard to ignore Salesforce’s strategic genius. The platform has matured to the point where it offers nearly every functionality an organization could need, though at times the components feel a bit disconnected. For instance: Salesforce is even hinting at usage-based pricing, with a potential $2 charge per conversation—an innovation that could reshape their pricing model. Will Agents Be Salesforce’s Key to Future Growth? With so many unknowns, only time will tell if agents will be the breakthrough Salesforce needs to regain the momentum of its first two decades. Regardless, agents appear to be central to the future of AI. Leading organizations like Copado are also launching their own agents, signaling that this trend will define the next phase of AI innovation. In today’s macroeconomic environment, where companies are overstretched and workforce demands are high, AI’s ability to streamline operations and improve customer service has never been more critical. Whoever cracks customer service AI first could lead the charge in the inevitable AI spending boom. We’re all waiting to see if Salesforce has truly cracked the AI code. But one thing is certain: the race to dominate AI in customer service has begun. And Salsesforce may be at the forefront. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
Impact of EHR Adoption

Connected Care Technology

How Connected Care Technology Can Transform the Provider Experience Northwell Health is leveraging advanced connected care technologies, including AI, to alleviate administrative burdens and foster meaningful interactions between providers and patients. While healthcare technology has revolutionized traditional care delivery models, it has also inadvertently created barriers, increasing the administrative workload and distancing providers from their patients. Dr. Michael Oppenheim, Senior Vice President of Clinical Digital Solutions at Northwell Health, highlighted this challenge during the Connected Health 2024 virtual summit, using a poignant illustration published a decade ago in the Journal of the American Medical Association. The image portrays a physician focused on a computer with their back to a patient and family, emphasizing how technology can inadvertently shift attention away from patient care. Reimagining Technology to Enhance Provider-Patient Connections To prevent technology from undermining the patient-provider relationship, healthcare organizations must reduce the administrative burden and enhance connectivity between patients and care teams. Northwell Health exemplifies this approach by implementing innovative solutions aimed at improving access, efficiency, and communication. 1. Expanding Access Without Overloading Providers Connected healthcare technologies can dramatically improve patient access but may strain clinicians managing large patient panels. Dr. Oppenheim illustrated how physicians often need to review extensive patient histories for every interaction, consuming valuable time. Northwell Health addresses this challenge by employing mapping tools, propensity analyses, and matching algorithms to align patients with the most appropriate providers. By connecting patients to specialists who best meet their needs, providers can maximize their time and expertise while ensuring better patient outcomes. 2. Leveraging Generative AI for Chart Summarization Generative AI is proving transformative in managing the immense data volumes clinicians face. AI-driven tools help summarize patient records, extracting clinically relevant details tailored to the provider’s specialty. For instance, in a pilot at Northwell Health, AI successfully summarized complex hospitalizations, capturing the critical elements of care transitions. This “just right” approach ensures providers receive actionable insights without unnecessary data overload. Additionally, ambient listening tools are being used to document clinical consultations seamlessly. By automatically summarizing interactions into structured notes, physicians can focus entirely on their patients during visits, improving care quality while reducing after-hours charting. 3. Streamlining Team-Based Care Effective care delivery often involves a multidisciplinary team, including primary physicians, specialists, nurses, and social workers. Coordinating communication across these groups has historically been challenging. Northwell Health is addressing this issue by adopting EMR systems with integrated team chat functionalities, enabling real-time collaboration among care teams. These tools facilitate better care planning and communication, ensuring patients receive coordinated and consistent treatment. Dr. Oppenheim emphasized the importance of not only uniting clinicians in decision-making but also involving patients in discussions. By presenting clear, viable options, providers can enhance patient engagement and shared decision-making. The Path Forward: Balancing Technology with Provider Needs As healthcare continues its digital transformation, connected care technologies must prioritize clinician satisfaction alongside patient outcomes. Tools that simplify workflows, enhance communication, and reduce administrative burdens are crucial for fostering provider buy-in and ensuring the success of health IT initiatives. Northwell Health’s efforts demonstrate how thoughtfully implemented technologies can empower clinicians, strengthen patient relationships, and create a truly connected healthcare experience. Tectonic is here to help your facility plan. Content updated November 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

Read More
Salesforce Query Builder

Salesforce Query Builder

Salesforce Query Builder Effortlessly Build SOQL Queries for Salesforce Objects with Salesforce Query Builder. The Salesforce Query Builder is a powerful Chrome extension that simplifies the creation of SOQL (Salesforce Object Query Language) queries for administrators, developers, and power users. This tool addresses the common challenge of building complex queries directly within your Salesforce environment, eliminating the need for external tools. Key Features and Benefits Seamless Integration: The Query Builder works directly within your Salesforce tabs, streamlining your workflow by removing the need to switch between apps or browser windows. This integration ensures better productivity without disruption. User-Friendly Interface: Its intuitive design makes query building easy for users at any skill level. A step-by-step process walks you through selecting objects, fields, and applying filters, reducing the complexities of SOQL syntax. Dynamic Object and Field Selection: The extension automatically fetches and displays available Salesforce objects and fields, saving time and minimizing errors by using up-to-date schema information. Real-Time Query Generation: As you choose objects, fields, and filters, the extension generates the SOQL query in real-time. This live feedback helps you understand the structure of the query, allowing for quick adjustments. Secure Authentication: Using your existing Salesforce session, the Query Builder ensures your credentials remain secure. It doesn’t store or transmit sensitive information, maintaining the integrity of your data. Flexible Filtering: Easily add WHERE clauses to filter data based on specific criteria, making it simple to focus on the data subsets you need. Copy to Clipboard: With one click, copy the generated SOQL query to your clipboard for easy use in other tools, development environments, or for sharing with teammates. Field Search: For objects with many fields, the search function helps you quickly locate the fields you need, reducing time spent scrolling. Lightweight and Fast: As a browser extension, the Query Builder is lightweight, requiring no installation on your Salesforce instance, ensuring fast performance without impacting your org. Cross-Domain Support: The tool supports multiple Salesforce domains (salesforce.com, force.com, cloudforce.com), providing a consistent experience across different environments. Why You Should Install It Time-Saving: The Query Builder dramatically reduces the time spent constructing SOQL queries, especially for complex objects or unfamiliar schemas. Error Reduction: By providing a visual interface, the tool minimizes syntax errors that can occur when manually writing SOQL queries. Learning Tool: Ideal for those new to SOQL, the Query Builder helps users understand query structure and best practices through its interactive design. Increased Productivity: With seamless Salesforce integration, you can generate queries quickly without disrupting your workflow. Accessibility: The tool empowers users who may not be comfortable writing SOQL manually, making advanced querying capabilities accessible to a wider range of Salesforce users. Consistency: It encourages consistent query-building practices across teams, making collaboration and sharing of queries easier. No Setup Required: As a browser extension, it requires no changes to your Salesforce org, making it perfect for admins or developers working across multiple orgs or with limited customization permissions. By installing the Salesforce Query Builder, you gain a valuable tool for your daily Salesforce tasks. Whether you’re a developer needing to prototype queries, an admin exploring data relationships, or a business analyst needing custom views, this tool simplifies interacting with your Salesforce data. With its combination of ease of use, security, and powerful features, it’s an essential addition to any Salesforce professional’s toolkit. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
What is GovSlack

What is GovSlack?

GovSlack: Streamlined, Secure Collaboration for Government GovSlack brings together your team, tools, and partners into one secure platform, specifically designed to meet government regulations for processing and storing sensitive data. By integrating GovSlack, organizations can eliminate internal and external communication silos while empowering employees with the flexibility to excel in their roles. What is GovSlack?GovSlack is a tailored version of Slack that allows agencies, contractors, citizens, and partners to collaborate in a centralized, secure workspace. It complies with the strictest security and operational standards required by public sector clients. Is Slack FedRAMP approved?Yes, Slack holds FedRAMP Moderate authorization to meet public sector compliance needs. GovSlack goes further, earning FedRAMP JAB High authorization and is actively pursuing DoD CC SRG IL4 compliance to cater to defense sector clients. Does the federal government use Slack?Security is crucial for public sector agencies and their partners. Federal agencies trust Slack as their secure digital HQ, helping teams from the U.S. Department of Veterans Affairs to the GSA’s 18F office enhance collaboration while meeting stringent data privacy requirements. GovSlack Key FeaturesGovSlack, launched in July 2022 after extensive testing and feedback from government clients, offers several features to ensure secure and compliant collaboration: GovSlack integrates seamlessly with other government-specific tools such as Salesforce Government Cloud Plus, creating a powerful CRM and collaboration ecosystem to accelerate agency goals and improve constituent services. Case Study: Army Software Factory (SWF)The Army SWF, using agile methods to upskill soldiers and develop cutting-edge digital solutions, required a flexible and secure collaboration platform. By adopting GovSlack, they fostered improved collaboration without compromising compliance with stringent DoD policies. Partner IntegrationsLeading companies such as Lockheed Martin and Box are leveraging GovSlack to streamline collaboration while maintaining compliance with federal regulations. For example, Lockheed Martin is using GovSlack to manage projects with government partners while ensuring sensitive data remains protected. ThoughtsGovSlack is built for secure, government-specific collaboration, providing agencies and their partners with the flexibility to work more effectively while meeting compliance needs. By integrating with key tools and offering enhanced security features, GovSlack supports the digital transformation efforts of public sector organizations across the globe. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
Salesforce Government Cloud

Salesforce Government Cloud: Ensuring Compliance and Security

Salesforce Government Cloud public sector solutions offer dedicated instances known as Government Cloud Plus and Government Cloud Plus – Defense. These instances are built on Salesforce Customer 360, featuring both Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) offerings. Key Features: Scale and Secure Apps on a Compliant Government Cloud: Government Cloud Plus for Public Sector: Unique Aspects of Government Cloud Plus: Compliant Environment and Security Measures: Drive Adoption and Salesforce FedRAMP: Salesforce FedRAMP Overview: Salesforce Usage in the U.S. Government: Salesforce Government Cloud Public Sector Solutions Content updated February 2022. Like2 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
gettectonic.com