Artificial Intelligence (AI) is significantly transforming threat detection by enabling faster, more accurate identification of potential security breaches through its ability to analyze vast amounts of data in real-time, detect anomalies and patterns that might indicate a threat, even when those threats are new or previously unknown, thus providing a proactive approach to cybersecurity compared to traditional rule-based systems.
Salesforce Prompt Builder: Field Generation Prompt Template What is a Prompt? A prompt is a set of detailed instructions designed to guide a Large Language Model (LLM) in generating relevant and high-quality output. Just like chefs fine-tune their recipes through testing and adjustments, prompt design involves iterating on instructions to ensure that the LLM delivers accurate, actionable results. Effective prompt design involves “grounding” your prompts with specific data, such as business context, product details, and customer information. By tailoring prompts to your particular needs, you help the LLM provide responses that align with your business goals. Like a well-crafted recipe, an effective prompt consists of both ingredients and instructions that work together to produce optimal results. A great prompt offers clear directions to the LLM, ensuring it generates output that meets your expectations. But what does an ideal prompt template look like? Here’s a breakdown: What is a Field Generation Prompt Template? The Field Generation Prompt Template is a tool that integrates AI-powered workflows directly into fields within Lightning record pages. This template allows users to populate fields with summaries or descriptions generated by an LLM, streamlining interactions and enhancing productivity during customer conversations. Let’s explore how to set up a Field Generation Prompt Template by using an example: generating a summary of case comments to help customer service agents efficiently review a case. Steps to Create a Field Generation Prompt Template 1. Create a New Rich Text Field on the Case Object 2. Enable Einstein Setup 3. Create a Prompt Template with the Field Generation Template Type 4. Configure the Prompt Template Workspace Optional: You can also use Flow or Apex to incorporate additional merge fields. 5. Preview the LLM’s Response Example Prompt: Scenario:You are a customer service representative at a company called ENForce.com, and you need a quick summary of a case’s comments. Record Merge Fields: Instructions: vbnetCopy codeFollow these instructions precisely. Do not add information not provided. – Refer to the “contact” as “client” in the summary. – Use clear, concise, and straightforward language in the active voice with a friendly, informal, and informative tone. – Include an introductory sentence and closing sentence, along with several bullet points. – Use a variety of emojis as bullet points to make the list more engaging. – Limit the summary to no more than seven sentences. – Do not include any reference to missing values or incomplete data. 6. Add the “Case Summary” Field to the Lightning Record Page 7. Generate the Summary By following these steps, you can leverage Salesforce’s Prompt Builder to enhance case management processes and improve the efficiency of customer service interactions through AI-assisted summaries. 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
As the vacation ownership industry grows, focus on innovation, personalization, and partnerships sets Salesforce apart. By leveraging Salesforce and Tableau, the company ensures its systems, teams, and customer experiences evolve to meet the expectations of modern travelers, delivering on its promise of unforgettable vacations.
MOIRAI-MoE represents a groundbreaking advancement in time series forecasting by introducing a flexible, data-driven approach that addresses the limitations of traditional models. Its sparse mixture of experts architecture achieves token-level specialization, offering significant performance improvements and computational efficiency. By dynamically adapting to the unique characteristics of time series data, MOIRAI-MoE sets a new standard for foundation models, paving the way for future innovations and expanding the potential of zero-shot forecasting across diverse industries.
GenAI: Transforming the Role of Data Science Teams Challenges, Opportunities, and the Evolving Responsibilities of Data Scientists Generative AI (GenAI) is revolutionizing the AI landscape, offering faster development cycles, reduced technical overhead, and enabling groundbreaking use cases that once seemed unattainable. However, it also introduces new challenges, including the risks of hallucinations and reliance on third-party APIs. For Data Scientists and Machine Learning (ML) teams, this shift directly impacts their roles. GenAI-driven projects, often powered by external providers like OpenAI, Anthropic, or Meta, blur traditional lines. AI solutions are increasingly accessible to non-technical teams, but this accessibility raises fundamental questions about the role and responsibilities of data science teams in ensuring effective, ethical, and future-proof AI systems. Let’s explore how this evolution is reshaping the field. Expanding Possibilities Without Losing Focus While GenAI unlocks opportunities to solve a broader range of challenges, not every problem warrants an AI solution. Data Scientists remain vital in assessing when and where AI is appropriate, selecting the right approaches—whether GenAI, traditional ML, or hybrid solutions—and designing reliable systems. Although GenAI broadens the toolkit, two factors shape its application: For example, incorporating features that enable user oversight of AI outputs may prove more strategic than attempting full automation with extensive fine-tuning. Differentiation will not come from simply using LLMs, which are widely accessible, but from the unique value and functionality they enable. Traditional ML Is Far from Dead—It’s Evolving with GenAI While GenAI is transformative, traditional ML continues to play a critical role. Many use cases, especially those unrelated to text or images, are best addressed with ML. GenAI often complements traditional ML, enabling faster prototyping, enhanced experimentation, and hybrid systems that blend the strengths of both approaches. For instance, traditional ML workflows—requiring extensive data preparation, training, and maintenance—contrast with GenAI’s simplified process: prompt engineering, offline evaluation, and API integration. This allows rapid proof of concept for new ideas. Once proven, teams can refine solutions using traditional ML to optimize costs or latency, or transition to Small Language Models (SMLs) for greater control and performance. Hybrid systems are increasingly common. For example, DoorDash combines LLMs with ML models for product classification. LLMs handle cases the ML model cannot classify confidently, retraining the ML system with new insights—a powerful feedback loop. GenAI Solves New Problems—But Still Needs Expertise The AI landscape is shifting from bespoke in-house models to fewer, large multi-task models provided by external vendors. While this simplifies some aspects of AI implementation, it requires teams to remain vigilant about GenAI’s probabilistic nature and inherent risks. Key challenges unique to GenAI include: Data Scientists must ensure robust evaluations, including statistical and model-based metrics, before deployment. Monitoring tools like Datadog now offer LLM-specific observability, enabling teams to track system performance in real-world environments. Teams must also address ethical concerns, applying frameworks like ComplAI to benchmark models and incorporating guardrails to align outputs with organizational and societal values. Building AI Literacy Across Organizations AI literacy is becoming a critical competency for organizations. Beyond technical implementation, competitive advantage now depends on how effectively the entire workforce understands and leverages AI. Data Scientists are uniquely positioned to champion this literacy by leading initiatives such as internal training, workshops, and hackathons. These efforts can: The New Role of Data Scientists: A Strategic Pivot The role of Data Scientists is not diminishing but evolving. Their expertise remains essential to ensure AI solutions are reliable, ethical, and impactful. Key responsibilities now include: By adapting to this new landscape, Data Scientists will continue to play a pivotal role in guiding organizations to harness AI effectively and responsibly. GenAI is not replacing them; it’s expanding their impact. 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
Without measurement, a business is flying by the seat of its pants. In business, as in many areas of life, tracking progress is essential for growth. For example, one individual has been tracking cycling times on the same routes for over five years, and while performance has slowed, improvements in other areas, like taking more time off with family and building stronger client relationships, have been evident. Despite this, many businesses still fail to measure enough, particularly when it comes to understanding key performance indicators. A recent Salesforce survey found that 60% of small businesses rely primarily on cash flow as their key metric, often neglecting other important indicators of business health. For many, the primary measure of success is simply how much money is in the bank account, which, while important, is only a small part of the larger picture. The importance of measurement and metrics for business success and growth cannot be over emphasized. By tracking the right indicators, businesses gain a competitive edge and the ability to adapt and thrive in an ever-changing market. The Importance of Measurement Today, measuring business performance is more critical than ever for several reasons: Key Metrics to Measure While industry-specific metrics are important, there are several universal indicators that every management team should focus on. Thanks to new digital tools, gathering and analyzing these metrics is easier than ever, offering a comprehensive view of a business’s health. The Consequences of Not Measuring Without measurement, businesses are essentially operating without road signs. Small businesses, in particular, may not measure enough, while larger organizations may suffer from “analysis paralysis” by over-measuring and becoming overwhelmed by data. Measurement makes a difference. Just as an individual may track cycling times without measuring other variables like weight or diet, businesses must decide which metrics are most relevant to their success. While some aspects of business may be left unmeasured, others—such as sales, margins, and marketing performance—are vital for growth and strategic decision-making. In conclusion, businesses that embrace measurement are better equipped to navigate challenges, seize opportunities, and ultimately, thrive in a competitive 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
Can AI-Driven Care Coordination Software Improve Workflows? University Hospitals is leveraging AI to enhance care coordination across its network of 13 hospitals and numerous outpatient settings. This effort highlights the transformative potential of AI-driven platforms in streamlining workflows, improving patient outcomes, and addressing clinician burnout. The Role of AI in Care Coordination Care coordination ensures seamless collaboration between healthcare providers, aiming for safe, appropriate, and effective treatment. Effective information-sharing can: According to the U.S. Centers for Medicare & Medicaid Services (CMS), poor care coordination can lead to: The Agency for Healthcare Research and Quality (AHRQ) advocates for a mix of technology adoption and care-specific strategies, such as proactive care plans tailored to patient needs. While electronic health records (EHRs) aid in these efforts, AI’s ability to analyze vast data sets positions it as the next evolution in care coordination. University Hospitals’ AI Initiative University Hospitals has partnered with Aidoc to deploy its AI-powered platform, aiOS, to improve radiology and care coordination workflows. Chair of Radiology Donna Plecha shared insights on how AI is already assisting in their operations: Best Practices for Implementing AI 1. Identify High-Value Use Cases: 2. Conduct Architectural Reviews: 3. Monitor ROI and Metrics: 4. Gain Clinician Buy-In: Looking Ahead AI is proving to be a valuable tool in care coordination, but its adoption requires realistic expectations and a thoughtful approach. Plecha underscores that AI won’t replace radiologists but will empower those who embrace it. As healthcare faces increasing patient volumes and clinician shortages, leveraging AI to reduce workloads and enhance care quality is becoming a necessity. With ongoing evaluations and phased implementations, University Hospitals is setting a precedent for how AI can drive innovation in care coordination while maintaining clinician oversight and patient trust. 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
At Dreamforce 2024, Salesforce customers showcased the power of Agentforce by creating over 10,000 autonomous agents, each designed to address specific business challenges. The message was clear: “If you can describe it, Agentforce can do it.” By leveraging Agentforce, customers are able to create a flexible, on-demand digital workforce that operates without limitations, making it easy to build and deploy agents using familiar Salesforce tools and language. Why This Matters: Recent Salesforce research reveals that U.S. consumers often spend up to nine hours interacting with customer service to resolve a single issue. Moreover, 67% of consumers are frustrated when their issues aren’t resolved immediately and may abandon one-third of customer service interactions. This presents a massive opportunity to enhance the customer experience with AI-powered agents. “Piloting Agentforce made a noticeable difference during our busiest period — back-to-school season. We saw a 40% increase in case resolution, surpassing the performance of our old bot. Agentforce helps manage routine tasks, allowing our service teams to focus on more complex cases.” – Kevin Quigley, Director of Process Improvement, Wiley What’s New: Several new solutions are now available to all customers: Going Deeper: Agentforce is fully integrated into the Salesforce Platform, combining powerful data, AI, and the Salesforce Customer 360 ecosystem. This integration unlocks infinite agent capacity and proactive actions across all roles and channels, with full context on every customer interaction. Industry-Specific Examples: Agentforce’s flexibility allows it to serve various industries with tailored solutions: Customer & Analyst Quotes: “Agentforce is enhancing Saks’ ability to provide personalized customer support, automating routine tasks like order tracking, which allows our teams to focus on delivering a high-touch experience.” – Mike Hite, Chief Technology Officer, Saks Global “With Agentforce, OpenTable is automating routine tasks, saving time for our reps to focus on strengthening customer relationships and providing exceptional service to diners and restaurants worldwide.” – George Pokorny, Senior VP of Global Customer Success, OpenTable “By integrating Agentforce with Data Cloud and MuleSoft, we’re unlocking the full potential of our data, driving faster decisions and reimagining how we serve clients.” – Caroline Basyn, Chief Digital & IT Officer, The Adecco Group “Agentforce will revolutionize ezCater’s food management services, blending AI and human interaction to ensure seamless, personalized experiences for every customer.” – Erin DeCesare, CTO, ezCater 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
By adopting a NaaS model, businesses can optimize their networks for the future while focusing on what matters most—their core mission. The era of “hands-free” networking has arrived, and it’s redefining the IT landscape
The Nature Tech Revolution: From “Do No Harm” to “Nature-Positive” In January, ERM, Salesforce, Planet, and NatureMetrics launched the NatureTech Alliance at the World Economic Forum in Davos. The Alliance’s mission is clear: empower companies to leverage advanced data and technology to address pressing nature-related challenges. This integrated effort focuses on: After engaging with clients in early 2024, the Alliance identified recurring challenges across value chains. Through interviews with industry leaders, it uncovered actionable insights into corporate efforts to overcome these hurdles. Seven key takeaways highlight the obstacles and opportunities for effective nature-positive strategies. Seven Key Insights for Corporate Nature Action 1. Nature Risk is Both Global and Highly Local Nature-related risks, such as water scarcity or biodiversity loss, vary significantly by region. However, many companies rely on coarse, global data that overlooks critical local nuances like community-level resource usage or ecosystem dynamics. This mismatch creates blind spots that can hinder decision-making, disrupt operations, or lead to regulatory non-compliance. 2. Nature Risk Lacks Integration with Enterprise Strategy Nature-related risks often remain siloed from broader enterprise risk frameworks, despite deep ties to issues like climate change. For instance, deforestation exacerbates biodiversity loss and water stress while releasing carbon into the atmosphere. Integrating nature data into strategic planning is essential for resilience and sustainable performance. 3. Gaps in Understanding Hinder Progress Corporate decision-makers and investors frequently struggle to interpret complex nature-related data, slowing the adoption of nature-positive strategies. Bridging this gap with accessible tools and clear communication is critical to driving meaningful action. 4. A Shift from “Do No Harm” to “Net Positive” Businesses are evolving from mitigating harm (e.g., reducing deforestation) to pursuing net-positive outcomes, such as reforestation or ecosystem restoration. While promising, many of these efforts remain in pilot phases due to challenges in site-level data and measuring impacts. 5. Financial Institutions Lag but Hold Scaling Potential The financial sector trails industries like agriculture in incorporating nature-related data into decision-making. However, as institutions recognize risks like biodiversity loss and soil degradation, they are poised to influence capital flows and set new standards for nature-positive investments. 6. The Future Lies in Outcome-Based Metrics Companies are shifting from input-based metrics (e.g., reduced fertilizer use) to measuring real-world outcomes for biodiversity and ecosystem health. Outcome-based metrics offer better clarity on environmental impacts and link corporate actions to business value. However, challenges like standardized methodologies and reliable data collection persist. 7. Data Fragmentation, Not Technology, is the Biggest Barrier Although technologies like AI and remote sensing are widely available, fragmented and inconsistent data remains a significant hurdle. Many organizations collect localized data but struggle to integrate it across supply chains and operations. Advanced platforms that consolidate disparate datasets are critical for actionable insights. A Shared Vision for Nature-Positive Solutions The NatureTech Alliance envisions a transformative approach to addressing these challenges, built on five pillars: Achieving a Nature-Positive Future By aligning corporate strategies with these principles, businesses can move beyond “do no harm” to actively restoring ecosystems and driving nature-positive outcomes. This transition requires advanced tools, collaboration, and a commitment to measurable impact—paving the way for a more sustainable and resilient future. 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
Salesforce Unveils Agentforce Testing Center: A Breakthrough in AI Agent Lifecycle Management Salesforce, the global leader in AI-powered CRM solutions, has announced the Agentforce Testing Center, a first-of-its-kind platform for managing the lifecycle of autonomous AI agents. This innovative solution enables organizations to test AI agents at scale, leveraging synthetic data in secure environments, while ensuring accurate performance and robust monitoring. Designed to meet the unique demands of deploying intelligent AI agents, the Agentforce Testing Center introduces new tools to test, prototype, and optimize AI agents without disrupting live production systems. Core Features of the Agentforce Testing Center Why It Matters Autonomous AI agents represent a paradigm shift in enterprise software, capable of reasoning, retrieving data, and acting on behalf of users. However, ensuring their reliability and trustworthiness requires a robust testing framework that eliminates risks to live systems. The Agentforce Testing Center addresses these challenges by combining: “Agentforce is helping businesses create a limitless workforce,” said Adam Evans, EVP and GM for Salesforce AI Platform. “To deliver this value quickly, CIOs need advanced tools for testing and monitoring autonomous systems. Agentforce Testing Center provides the necessary framework for secure, repeatable deployment.” Customer and Analyst Perspectives Shree Reddy, CIO, PenFed:“With nearly 3 million members, PenFed is dedicated to providing personalized, efficient service. Using Data Cloud Sandboxes, we’re able to test and refine AI agents, ensuring they deliver fast, accurate support that aligns with our members’ financial goals.” Keith Kirkpatrick, Research Director, The Futurum Group:“To instill trust in AI, businesses must rigorously test autonomous agents. Salesforce’s Testing Center enables confidence by simulating hundreds of interaction scenarios, helping organizations deploy AI agents securely and effectively.” Availability A Competitive Edge in AI Lifecycle Management Salesforce’s Agentforce Testing Center sets a new industry standard for testing and deploying AI agents at scale. By providing a secure, scalable, and transparent solution, Salesforce enables businesses to embrace an “agent-first” approach with confidence. As enterprises continue adopting AI, tools like the Agentforce Testing Center will play a critical role in accelerating innovation while maintaining trust and reliability. 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
Leverage AI to Enhance Customer Retention and Reduce Churn Customer churn is among the most expensive challenges businesses face—and one of the hardest to tackle. Predictive and generative AI technologies offer an immediate opportunity to boost retention rates. When applied strategically, these tools can revolutionize how customer service and support teams operate, creating measurable improvements in retention and overall customer satisfaction. A recent McKinsey & Company study highlights the impact of AI in customer service. One company reported a 14% increase in issue resolution and a 9% reduction in issue handling time with generative AI. Requests to escalate to a manager dropped by 25%, and employee retention in service roles improved. When every percentage point matters, AI’s ability to engage and retain customers (and employees) can significantly affect your bottom line and business success. The Cost of Poor Customer Service on Retention Retaining existing customers is far more cost-effective than acquiring new ones. Happy, long-term customers are also more likely to purchase additional products or services, making upselling and cross-selling efforts easier. However, poor customer service experiences—such as lengthy hold times, repeating information, or unhelpful chatbot interactions—can damage customer relationships and lead to churn. As Salesforce points out, these four signs indicate broken customer service: To address these challenges, a seamless, data-driven approach to customer service is essential. Prevent Churn with CRM + AI Customer data spans multiple touchpoints, from website visits to call center interactions. Without a unified view, even the most skilled service teams struggle to deliver exceptional experiences. A solution like Salesforce Service Cloud, enhanced by AI tools such as Agentforce Service Agents, empowers teams to: By combining predictive analytics with a unified customer experience platform, businesses can deliver personalized, proactive service that fosters loyalty. Retention Agent: The AI Solution for Customer Retention Retention Agent, part of Tectonic’s Agentforce suite, leverages AI to identify at-risk customers and equip sales, service, and support teams with actionable insights. It provides recommendations for re-engagement strategies, personalized offers, and targeted communications to prevent costly churn. Here’s how Retention Agent works: By integrating AI into customer service operations, businesses can stay ahead of churn, improve satisfaction, and build stronger, longer-lasting customer relationships. 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
Salesforce Modernizes Heroku PaaS with Kubernetes, .NET, and More Salesforce is rolling out a significant upgrade to Heroku, its popular Platform-as-a-Service (PaaS), to better align with modern developer needs. Key enhancements include support for Amazon Elastic Container Registry (ECR), AWS Global Accelerator, Elastic Kubernetes Service (EKS), AWS Graviton processors, and AWS Bedrock. The revamped platform, dubbed the Heroku Next Generation Platform, was unveiled at the AWS Re:Invent 2024 conference. While some features are in public beta, Salesforce plans to fully release additional capabilities by 2025. Catering to the Modern DeveloperHeroku’s overhaul reflects the growing dominance of Kubernetes and the increasing demand for AI-enabled applications, including autonomous ones built in Salesforce’s Agentforce. Rebecca Wettemann, founder of Valoir, notes that these trends required Salesforce to evolve Heroku to remain competitive in the PaaS market. Kubernetes, for instance, is widely used for app containerization across clouds, while AI applications are becoming a focal point for many developers. “The update broadens Heroku’s appeal to developers who rely on Kubernetes or are building AI applications,” Wettemann said. Another notable addition is support for open telemetry, a standardized approach to monitoring app performance. Developers can now stream real-time metrics such as app health and container logs into their preferred visualization tools. “This integration offers unparalleled flexibility for our customers to work with a wide ecosystem of telemetry collectors,” said Gail Frederick, Heroku’s CTO at Salesforce. Introducing .NET SupportOne of the standout updates is the inclusion of .NET, a widely used open-source framework. Developers can now use .NET languages such as C#, F#, and Visual Basic alongside Heroku’s existing support for languages like Python, Ruby, Java, Node.js, and Scala. This strategic move aligns Heroku with a broader audience, especially developers familiar with Microsoft’s ecosystem. “Heroku is all about developer choice,” said Frederick. “Adding .NET ensures we continue to serve diverse needs.” Streamlining Development and DeploymentHeroku aims to simplify app development by automating infrastructure management and lifecycle tasks. “Heroku is the platform developers turn to when they need things to work without thinking about infrastructure,” said Adam Zimman, Senior Director of Product Marketing at Heroku. The platform abstracts complex deployment steps, such as configuration, provisioning, and autoscaling, enabling developers to focus on coding and innovation. Apps are deployed as pre-packaged “slugs” that run on Heroku’s dynos, isolated Unix-based containers. Developers can scale their apps dynamically by adding or removing dynos via the platform’s management interface. Efficiency Gains for BusinessesZimman highlighted the efficiency benefits of Heroku’s approach, projecting up to a 40% boost in developer productivity and a 30% reduction in developer expenses. “By taking care of the heavy lifting, we enable businesses to deliver applications faster and more cost-effectively,” he explained. Heroku also offers over 500 pre-built add-ons and build packs, covering functions like messaging, database management, and email services. These integrations provide additional flexibility and speed up the development lifecycle. Scaling Beyond StartupsWhile Heroku is often associated with startups, Salesforce has scaled the platform to accommodate enterprise-grade applications. “Heroku now evolves with your business,” said Chris Peterson, Senior Director of Product Management at Heroku. The platform has powered over 13 million applications and 38 million managed data stores since its launch in 2007. Many Salesforce applications also run on Heroku, leveraging deep integrations to extend the Salesforce ecosystem seamlessly. Heroku’s pricing starts at $7 per month for a basic plan and scales up to $40,000 per month for enterprise-grade solutions, ensuring it meets the needs of organizations of all sizes. With these updates, Heroku continues to position itself as a go-to platform for developers, enabling faster time-to-market, reduced operational complexity, and a better overall development experience. 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
Salesforce Expands Partnership with AWS: AI and Marketplace Integration Salesforce (NYSE: CRM) is making significant strides in its partnership with Amazon (NASDAQ: AMZN), unveiling an expanded collaboration at AWS. Customers can now purchase Salesforce products directly through the AWS Marketplace, paying with AWS credits. This integration aims to simplify access to Salesforce offerings, enhance data integration capabilities, and leverage generative AI tools. Key Announcements: Marc Benioff, Chair and CEO of Salesforce, highlighted the importance of this milestone: “We’re bringing together the No. 1 AI CRM provider and the leading cloud provider to deliver a trusted, open, integrated data and AI platform. With these enhancements to our partnership, we’re enabling all of our customers to be more innovative, productive, and successful in this new AI era.” AWS CEO Adam Selipsky echoed these sentiments, emphasizing how the partnership will enable joint customers to “innovate, collaborate, and build more customer-focused applications.” Strategic Benefits: Revenue-Sharing Structure: Like app stores, Amazon will take a percentage of Salesforce’s revenue generated through AWS Marketplace. Despite this, the potential growth in sales and efficiency gains may outweigh the costs. Market Reaction: Following the announcement, both Salesforce and Amazon shares experienced a boost in premarket trading, signaling investor optimism about the partnership’s potential. This expansion reinforces Salesforce’s strategy of aligning with major cloud providers to meet growing demand for AI-driven, integrated data platforms. As this collaboration evolves, it is poised to drive significant value for businesses navigating the AI and data revolution. 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
AI in Business Intelligence: Uses, Benefits, and Challenges AI tools are increasingly becoming integral to Business Intelligence (BI) systems, enhancing analytics capabilities and streamlining tasks. In this article, we explore how AI can bring new value to BI processes and what to consider as this integration continues to evolve. AI’s Role in Business Intelligence Business Intelligence tools, such as dashboards and interactive reports, have traditionally focused on analyzing historical and current data to describe business performance—known as descriptive analytics. While valuable, many business users seek more than just a snapshot of past performance. They also want predictive insights (forecasting future trends) and prescriptive guidance (recommendations for action). Historically, implementing these advanced capabilities was challenging due to their complexity, but AI simplifies this process. By leveraging AI’s analytical power and natural language processing (NLP), businesses can move from descriptive to predictive and prescriptive analytics, enabling proactive decision-making. AI-powered BI systems also offer the advantage of real-time data analysis, providing up-to-date insights that help businesses respond quickly to changing conditions. Additionally, AI can automate routine tasks, boosting efficiency across business operations. Benefits of Using AI in BI Initiatives The integration of AI into BI systems brings several key benefits, including: Examples of AI Applications in BI AI’s role in BI is not limited to internal process improvements. It can significantly enhance customer experience (CX) and support business growth. Here are a few examples: Challenges of Implementing AI in BI While the potential for AI in BI is vast, there are several challenges companies must address: Best Practices for Deploying AI in BI To maximize the benefits of AI in BI, companies should follow these best practices: Future Trends to Watch AI is not poised to replace traditional BI tools but to augment them with new capabilities. In the future, we can expect: In conclusion, AI is transforming business intelligence by turning data analysis from a retrospective activity into a forward-looking, real-time process. While challenges remain, such as data governance, ethical concerns, and skill shortages, AI’s potential to enhance BI systems and drive business success is undeniable. By following best practices and staying abreast of industry developments, businesses can harness AI to unlock new opportunities and deliver better insights. 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
