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CXM
18Sep

CXM

XM Software Providers Set to Replace Point Solutions with Multifunction Suites By 2028, Enterprises Will Transition to Comprehensive CXM Solutions, According to New ISG Research According to new research from Information Services Group (ISG) (Nasdaq: III), companies are expected to shift from various customer experience (CX) point solutions to comprehensive, cross-functional suites by 2028. This transition aims to manage CX at the enterprise level more effectively. Keith Dawson, Director of Customer Experience Research at ISG, explains, “Enterprises recognize the need for platforms that manage the entire customer lifecycle. We are witnessing the rise of tools that integrate communication components with analytic assessments of customer value, loyalty, and intent, marking a significant shift in the marketplace.” The ISG Buyers Guide™ for Customer Experience Management (CXM) defines CXM as a suite of applications on a unified platform that provides a comprehensive view of customer activity and enables management of that activity across departments. The report notes that the mix of applications in a software provider’s suite often reflects their historical expertise and origins. CXM addresses the limitations of traditional Customer Resource Management (CRM) software, which has been more departmental and application-centric. In contrast, CXM focuses on the customer journey and interactions across all channels. The report highlights challenges in comparing similar offerings from different providers due to their varied origins and expertise. The range of functionality across CXM products often reflects their diverse components, users, and use cases. ISG identifies five core areas of platform functionality in CXM software: knowledge management, resource management, automation, analytics, and customer journey management. However, CXM software is still developing, and it is uncommon to find a single solution that excels in all five areas. Many providers start with their core strengths and expand their capabilities over time. The ISG Buyers Guide evaluates CXM software providers based on support for analytics, customer journey management, knowledge management, CRM platform support, operational resource management, and process control and optimization. To be included in the CXM Buyers Guide, products must cover at least three of the four areas: resource management, automation, analytics, and customer journey management. Separate guides on Customer Journey Management (CJM) and Knowledge Management (KM) are available for more specific analysis. For its 2024 Buyers Guides, ISG assessed 19 providers, including Adobe, eGain, Emplifi, Freshworks, Genesys, HubSpot, Microsoft, Nextiva, NICE, Oracle, Qualtrics, Salesforce, SAP, ServiceNow, Sprinklr, SugarCRM, Verint, Zendesk, and Zoho. The top three software providers in each category are: Mark Smith, Partner at ISG Software Research, notes, “Managing customer experience is crucial for every organization, yet many lack the technology to orchestrate the customer journey across channels. The Buyers Guide for CXM offers insights to help businesses understand, optimize, and select software providers that move beyond the limitations of traditional CRM systems.” The ISG Buyers Guides for CXM, CJM, and KM are based on over a year of market research. The research is independent and not influenced by software providers, aiming to help enterprises optimize their software investments. For more details, visit the ISG Buyers Guides to read executive summaries and request full reports. About ISG Software Research ISG Software Research, formerly Ventana Research, delivers expert market research and analysis on business and IT software. The firm provides consulting, advisory, research, and education services for enterprises, software and service providers, and investment firms. For more information and to join the community, visit Ventana Research. About ISG ISG (Information Services Group) (Nasdaq: III) is a global technology research and advisory firm specializing in digital transformation services. With a client base of over 900 organizations, ISG helps clients achieve operational excellence and growth. The firm’s expertise spans AI and automation, cloud and data analytics, sourcing advisory, and more. Founded in 2006 and based in Stamford, Conn., ISG employs 1,600 professionals in over 20 countries. For more information, visit ISG. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 18, 2024in Salesforce
Pay Per Chat
18Sep

Pay Per Chat

Salesforce is launching its AI-powered Agentforce platform across its key clouds, including Sales, Service, Marketing, and Commerce. However, a significant question remains: Will enterprises be willing to pay $2 per conversation for Agentforce, especially without volume discounts? The introduction of Agentforce wasn’t unexpected, as CEO Marc Benioff has been discussing autonomous AI agents since the company’s second-quarter earnings call. Leading up to Dreamforce, Salesforce has consistently emphasized agentic AI, with Benioff previously hinting at the $2 per conversation pricing model. Agentforce is part of Salesforce’s ongoing effort to move beyond generative AI copilots to fully autonomous digital agents that can perform tasks independently. Much of this technology stems from Salesforce’s acquisition of Airkit.ai last year. Additionally, the company’s acquisition of Own highlights a strategic, smaller-scale approach to mergers and acquisitions. The core of Salesforce’s AI vision is a blend of human expertise and AI agents. While humans focus on relationship-building, industry knowledge, and goal-setting, AI agents will handle tasks like answering questions, scheduling meetings, and gathering information. Key features of Agentforce include: Pay Per Chat? Salesforce is unifying its clouds under a single platform, with Data Cloud as the common thread connecting Sales, Service, Marketing, Commerce, and Tableau. According to Constellation Research analyst Holger Mueller, the real story is the infrastructure behind the agents, which will drive innovation in the future of work by enhancing developer velocity and productivity. At Dreamforce, Salesforce also unveiled Einstein Sales Agents, including a Sales Development Representative (SDR) agent and a Sales Coach, designed to improve sales performance. Salesforce highlighted that agents, unlike traditional bots, are dynamic, outcome-driven, and capable of adapting to various situations. Beyond sales, the Agentforce lineup includes: Agentforce is poised to serve as the connective tissue, unifying Salesforce’s various clouds and driving value with ongoing innovations in Data Cloud and AI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 18, 2024in Agentforce Platform, Generative AI, Mulesoft
Data Cloud and Genpact
16Sep

6 Work Easing Google AI Extensions

Time is often equated with money, and that couldn’t be more accurate. These Work Easing Google AI Extensions will give you back some time. Time is an invaluable asset, essential for managing both work and life. Many find themselves overwhelmed with tasks, constantly battling stress and exhaustion due to a lack of time. This was the case until AI-powered Chrome extensions came along, revolutionizing the way work is approached. Time concious workers have discovered the transformative power of these digital tools. They not only improved their careers but also completely changed how each manages there workload. Now, Tectonic’s sharing these invaluable resources, which have significantly boosted her productivity and time management. Here are some of the AI Chrome extensions we recommend: 1. Glasp AI Extension Glasp AI Chrome Extension Glasp AI is a robust tool that aids in capturing, organizing, and sharing knowledge from the web. Features: Benefits: 2. Merlin AI Merlin AI Chrome Extension Merlin AI uses advanced technology to assist with various tasks, helping users work faster and more efficiently. What it does: Why it’s helpful: 3. Just Done AI Extension Just Done AI Just Done AI is a great tool for detecting AI content. Features: Benefits: 4. Perplexity AI Perplexity AI Chrome Extension Perplexity AI is designed to elevate the browsing experience by providing quick access to AI-driven information and assistance. Why it’s useful: Benefits: 5. SciSpace SciSpace Chrome Extension SciSpace simplifies the understanding of scientific papers or reports by acting as a virtual assistant within the web browser. Just imagine having a coach explaining the technical concepts. Features: 6. WebChatGPT WebChatGPT Chrome Extension WebChatGPT enhances ChatGPT by allowing it to access current information from the internet, making the tool even more effective, by connecting it to up-to-date data. What it does: Why it’s beneficial: Work Easing Google AI Extensions These AI Chrome extensions have dramatically improved time management and productivity. They offer similar potential for anyone looking to optimize their workflow and make the most of their work time. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 16, 2024in Salesforce
GPT-o1 GPT5 Review
15Sep

GPT-o1 GPT5 Review

OpenAI has released its latest model, GPT-5, also known as Project Strawberry or GPT-o1, positioning it as a significant advancement in AI with PhD-level reasoning capabilities. This new series, OpenAI-o1, is designed to enhance problem-solving in fields such as science, coding, and mathematics, and the initial results indicate that it lives up to the anticipation. Key Features of OpenAI-o1 Enhanced Reasoning Capabilities Safety and Alignment Targeted Applications Model Variants Access and Availability The o1 models are available to ChatGPT Plus and Team users, with broader access expected soon for ChatGPT Enterprise users. Developers can access the models through the API, although certain features like function calling are still in development. Free access to o1-mini is expected to be provided in the near future. Reinforcement Learning at the Core The o1 models utilize reinforcement learning to improve their reasoning abilities. This approach focuses on training the models to think more effectively, improving their performance with additional time spent on tasks. OpenAI continues to explore how to scale this approach, though details remain limited. Major Milestones The o1 model has achieved impressive results in several competitive benchmarks: Chain of Thought Reasoning OpenAI’s o1 models employ the “Chain of Thought” prompt engineering technique, which allows the model to think through problems step by step. This method helps the model approach complex problems in a structured way, similar to human reasoning. Key aspects include: While the o1 models show immense promise, there are still some limitations, which have been covered in detail elsewhere. However, based on early tests, the model is performing impressively, and users are hopeful that these capabilities are as robust as advertised, rather than overhyped like previous projects such as SORA or SearchGPT by OpenAI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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September 15, 2024in Enterprise
New Slack Innovations
13Sep

New Slack Innovations

Salesforce Unveils Innovative Slack Updates Ahead of its Dreamforce conference in San Francisco later this week, Salesforce has introduced several groundbreaking updates to Slack, designed to consolidate company knowledge, data, agents, apps, and automation into a unified, agent-powered work operating system. New Slack Innovations. The latest enhancements to Slack include: Denise Dresser, CEO of Slack, commented on the updates: “Slack’s agent-powered work operating system is transforming productivity by seamlessly integrating purpose-built AI, customer data, and automation into the everyday workflow. This innovation isn’t just about improving how work gets done—it’s about unlocking new levels of productivity to drive business success across every team and department. In a complex work environment, true productivity demands a future-ready work operating system, and Slack is leading the way.” For more information on these updates and how they can benefit your organization, stay tuned for further details from Dreamforce. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 13, 2024in Data
IntraEdge Higher Education
13Sep

IntraEdge Higher Education

PHOENIX–(BUSINESS WIRE)–IntraEdge, Inc., a leading global technology products and services provider, recently announced its expanded investment in itsHigher Education division with the addition of new leadership to bolster their Salesforce service offerings. The new leaders each possess over 20 years of higher education experience and have a proven track record of building innovative and high performing consulting practices. “Our team has a proven track record of success in helping higher education institutions achieve their goals. We look forward to partnering with colleges and universities to leverage the power of Salesforce to improve student outcomes and operational efficiency.” The Higher Education division leadership team consists of Vince Salvato, Todd Edge, and Ryan Clemens. Salvato, who will be leading the division, is a recognized pioneer in Salesforce implementations for higher education. He brings a wealth of experience from his years working with higher education leaders, Salesforce, and ISV Partners. Edge and Clemens have a long history implementing Salesforce and other technologies for higher education leveraging global capabilities to assemble well balanced implementation teams. Together, this team boasts a proven track record of serving over 150 higher education institutions. Their collective history of successful Salesforce and technology implementations within higher education, coupled with IntraEdge’s 3,000+ global resources and complimentary product and service offerings, positions IntraEdge to deliver exceptional solutions. “We are thrilled to welcome Vince, Ryan, and Todd to the IntraEdge team,” said Kal Somani, CEO of IntraEdge. “Their combined experience and knowledge of the higher education landscape make them invaluable assets as we expand our footprint in this industry. By leveraging Salesforce’s powerful platform with IntraEdge’s full breadth of technology capabilities, we are confident in our ability to deliver exceptional solutions that address the unique challenges and opportunities facing higher education institutions.” IntraEdge redefines the typical implementation approach by delivering accelerated, cost-effective, and highly successful implementations. The company’s proven methodology and global delivery capabilities, combined with a team of seasoned higher education experts, will enable institutions to maximize the value of Salesforce while minimizing disruption to campus operations. IntraEdge’s Higher Education division offers a comprehensive suite of Salesforce-based solutions tailored to the specific needs of colleges and universities. With implementation, consulting, and value-add products and services, institutions can maximize the value of their Salesforce investment, including but not limited to Data Integration and Visualization, Digital Experience Strategy, Digital Content Strategy and Development, Managed and Capacity Services, AI Governance and Compliance Software. “We are excited to join IntraEdge and be a part of a world-class higher education practice,” said Salvato, Senior Vice President of Higher Education at IntraEdge. “Our team has a proven track record of success in helping higher education institutions achieve their goals. We look forward to partnering with colleges and universities to leverage the power of Salesforce to improve student outcomes and operational efficiency.” IntraEdge is proud to be a trusted partner to higher education institutions across North America. Our company is committed to delivering exceptional results and exceeding client expectations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 13, 2024in Salesforce
Large and Small Language Models
13Sep

Large and Small Language Models

Understanding Language Models in AI Language models are sophisticated AI systems designed to generate natural human language, a task that is far from simple. These models operate as probabilistic machine learning systems, predicting the likelihood of word sequences to emulate human-like intelligence. In the scientific realm, the focus of language models has been twofold: While today’s cutting-edge AI models in Natural Language Processing (NLP) are impressive, they have not yet fully passed the Turing Test—a benchmark where a machine’s communication is indistinguishable from that of a human. The Emergence of Language Models We are approaching this milestone with advancements in Large Language Models (LLMs) and the promising but less discussed Small Language Models (SLMs). Large Language Models compared to Small Language Models LLMs like ChatGPT have garnered significant attention due to their ability to handle complex interactions and provide insightful responses. These models distill vast amounts of internet data into concise and relevant information, offering an alternative to traditional search methods. Conversely, SLMs, such as Mistral 7B, while less flashy, are valuable for specific applications. They typically contain fewer parameters and focus on specialized domains, providing targeted expertise without the broad capabilities of LLMs. How LLMs Work Comparing LLMs and SLMs Choosing the Right Language Model The decision between LLMs and SLMs depends on your specific needs and available resources. LLMs are well-suited for broad applications like chatbots and customer support. In contrast, SLMs are ideal for specialized tasks in fields such as medicine, law, and finance, where domain-specific knowledge is crucial. Large and Small Language Models’ Roles Language models are powerful tools that, depending on their size and focus, can either provide broad capabilities or specialized expertise. Understanding their strengths and limitations helps in selecting the right model for your use case. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 13, 2024in Salesforce
AI-Driven Chatbots in Education
11Sep

AI-Driven Chatbots in Education

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

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September 11, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Generative AI, Salesforce Education Cloud, Salesforce Education Solutions
Ambient AI and Doctors
10Sep

Ambient AI and Doctors

A study published in JAMA Network Open found that nearly half of clinicians using an ambient AI clinical documentation tool reported positive outcomes. The tool, Dragon Ambient eXperience (DAX) Copilot from health IT vendor Nuance, leverages automatic speech recognition and natural language processing to draft electronic health record (EHR) documentation based on patient-provider conversations. The nonrandomized clinical trial included family medicine, internal medicine, and general pediatrics clinicians from outpatient clinics in North Carolina and Georgia within Atrium Health. Those who participated received an hour of training on the AI tool. Researchers compared the intervention group with a control group, which included clinicians encouraged to participate as controls by service line leaders and those who initially expressed interest in the AI tool but chose not to proceed after informational sessions. A seven-question survey was sent to 230 participants before and five weeks after implementing the AI tool to evaluate its impact on their EHR experience. The study showed that 47.1% of clinicians using the AI tool reported spending less time on EHR documentation at home, compared to 14.5% in the control group. Additionally, 43.5% of the AI tool users spent less time on clinical documentation post-visit, compared to 18.2% of the control group. Moreover, 44.7% of the intervention group reported reduced frustration with the EHR, compared to 14.5% of controls. However, around 44.7% of the intervention group and 68.7% of the control group indicated their EHR experiences remained similar before and after the AI tool implementation. The researchers acknowledged potential selection and recall biases as study limitations and called for further research to identify areas for improvement and explore the impact across different clinician groups and health systems. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more 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 Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more

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September 10, 2024in Salesforce Einstein, Salesforce Health and Life Sciences Solutions, Salesforce Optimization
EU AI Act
07Sep

EU AI Act

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

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September 7, 2024in Generative AI
Citizen Development
06Sep

Citizen Development

As we progress through the era of digital transformation, citizen development has emerged as a key trend in the business landscape. This approach empowers end-users to create their applications, streamlining workflows and reshaping corporate operations. However, like any innovation, citizen development presents both advantages and challenges. In this article, we will explore the benefits, pros and cons of citizen development, and strategies to effectively leverage it within your organization. 1. The Rise of Citizen Development The popularity of citizen development is on the rise, as reflected by Statista, which reports a remarkable 24.6% growth in this sector since 2020. The increasing demand for software solutions in the corporate environment has made the traditional model of IT departments solely managing application development unsustainable. By enabling non-technical personnel to develop their applications, businesses can relieve pressure on IT teams, speed up solution delivery, and cultivate a more agile business model. Furthermore, investing in citizen development platforms fosters an inclusive and innovative workplace, allowing diverse perspectives to generate unique applications that meet specific workflow needs. 2. Benefits of Citizen Development for Companies 2.1 Accelerated Pace and Flexibility Citizen development tools facilitate rapid prototyping and quicker application rollouts. Non-technical personnel can design, modify, and launch applications according to immediate needs, enhancing agility and responsiveness. 2.2 Boosted Creativity Empowering your staff to create applications unlocks a wealth of untapped potential. Citizen development nurtures a culture of innovation, leading to tailored solutions that address specific business challenges. 2.3 Tailored App Design Citizen developers, as end-users, possess an in-depth understanding of their workflow requirements. This perspective enables them to develop applications that align closely with user needs, improving adoption and utility. 2.4 Heightened Productivity By reducing the back-and-forth between IT departments and end-users, citizen development streamlines operations, leading to enhanced efficiency. 2.5 Cost-Effectiveness Citizen development significantly cuts costs associated with traditional application development, such as hiring professional developers or outsourcing tasks. Rapid application rollouts also help seize business opportunities quickly, optimizing ROI. 2.6 Reduced Workload for IT Staff Enabling non-technical personnel to handle minor application development tasks lightens the load on IT teams, allowing them to focus on high-priority projects. 2.7 Enhanced Visibility and Accountability Many citizen development platforms include built-in analytics and reporting features, offering insights into application usage and performance. This transparency helps businesses track initiatives, make data-driven decisions, and continuously improve processes. 3. Implementing Citizen Development with Salesforce Solutions Given its extensive benefits, citizen development is a strategy many businesses are eager to adopt. Salesforce provides a powerful platform to effectively harness citizen development. Salesforce’s platform caters to both professional and citizen developers, offering a comprehensive suite of user-friendly tools for building applications and managing workflows. With built-in safeguards for data security and regulatory compliance, Salesforce for Public Sector and Tribal Governments ensures a smooth and secure citizen development process. Their clear deployment roadmap and thorough training programs equip businesses for success in their citizen development journey. 4. Partnering with Tectonic for Public Sector and Tribal Government Solutions Consider Tectonic as your trusted partner for PSS solutions. Tectonic is a distinguished provider of technology solutions with extensive expertise in Salesforce and process management. With a proven track record of successful projects, Tectonic has earned the trust of clients globally. Tectonic maintains a close partnership with Salesforce, ensuring a deep understanding of its advanced features, including process automation. As a Salesforce partner, Tectonic keeps clients updated on the latest advancements, delivering cutting-edge solutions tailored to their specific needs. By selecting Tectonic as your implementation partner for public sector Salesforce, you benefit from their vast experience and specialized knowledge. Tectonic provides a dedicated public sector team that excels in implementing secure and efficient solutions, working closely with our clients to address their unique challenges. Tectonic offers a comprehensive range of services, from initial implementation to ongoing support and maintenance. Their offerings include process modeling, application design, automation implementation, and roles management. With Tectonic’s expertise, you can ensure seamless integration of automation into your pss projects. To learn more about Tectonic’s public sector services, visit our services page, where you can explore their offerings, including Salesforce Managed Services. Tectonic’s Managed Services provide full support to ensure your public sector environment runs smoothly, covering automation management, data governance, and performance optimization. 5. Final Thoughts While citizen development presents both advantages and challenges, the benefits largely outweigh the potential drawbacks. Although there are concerns about data security and the need for proper governance, the positive impact of citizen development makes it a vital component of the digital transformation narrative. Successful implementation hinges on selecting the right platform and tools that align with your business model and workflow needs. Salesforce Public Sector Solution excels in this regard, offering a user-friendly suite of tools with a clear roadmap for deployment and top-notch support. Brining your public sector tech into the 21st century is an imperative. To fully realize the benefits of citizen development, businesses must strike a balance between empowerment and control. Establishing an environment that fosters innovation and efficiency, while also implementing a governance structure to mitigate risks, is essential. With careful planning, the right tools, and a culture of collaboration, the rewards of citizen development can be substantial. Whether you’re looking to enhance speed and agility, optimize costs, or cultivate a culture of innovation, citizen development offers a promising pathway forward. Embrace citizen development in Salesforce PSS, and set your business on the road to success. If you have any questions about implementing Salesforce Public Sector Solutions and its benefits, feel free to contact us to discuss your project. 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

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September 6, 2024in Data, Salesforce Development Services, Salesforce Public Sector Solutions, Technology
AI Senate Bill 1047
06Sep

AI Senate Bill 1047

California’s new AI bill has sparked intense debate, with proponents viewing it as necessary regulation and critics warning it could stifle innovation, particularly for small businesses. Senate Bill 1047, known as the Safe and Secure Innovation for Frontier Artificial Intelligence Models Act, mandates that developers of advanced AI systems costing at least $100 million to train must test their models for potential harm and put safeguards in place. It also offers whistleblower protections for employees at large AI firms and establishes CalCompute, a public cloud computing resource aimed at startups and researchers. The bill is awaiting Governor Gavin Newsom’s signature by Sept. 30 to become law. Prominent AI experts, including Geoffrey Hinton and Yoshua Bengio, support the bill. However, it has met resistance from various quarters, including Rep. Nancy Pelosi and OpenAI, who argue it could hinder innovation and the startup ecosystem. Pelosi and others have expressed concerns that the bill’s requirements might burden smaller businesses and harm California’s leadership in tech innovation. Gartner analyst Avivah Litan acknowledged the dilemma, stating that while regulation is critical for AI, the bill’s requirements might negatively impact small businesses. “Some regulation is better than none,” she said, but added that thresholds could be challenging for smaller firms. Steve Carlin, CEO of AiFi, criticized the bill for its vague language and complex demands on AI developers, including unclear guidance on enforcing the rules. He suggested that instead of focusing on AI models, legislation should address the risks and applications of AI, as seen with the EU AI Act. Despite concerns, some experts like Forrester Research’s Alla Valente support the bill’s safety testing and whistleblower protections. Valente argued that safeguarding AI models is essential across industries, though she acknowledged that the costs of compliance could be higher for small businesses. Still, she emphasized that the long-term costs of not implementing safeguards could be greater, with risks including customer lawsuits and regulatory penalties. California’s approach to AI regulation adds to the growing patchwork of state-level AI laws in the U.S. Colorado and Connecticut have also introduced AI legislation, and cities like New York have tackled issues like algorithmic bias. Carlin warned that a fragmented state-by-state regulatory framework could create a costly and complex environment for developers, calling for a unified federal standard instead. While federal legislation has been proposed, none has passed, and Valente pointed out that relying on Congress for action is a slow process. In the meantime, states like California are pushing ahead with their own AI regulations, creating both opportunities and challenges for the AI industry. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 6, 2024in Salesforce
Data Quality Critical
06Sep

Data Quality Critical

Data quality has never been more critical, and it’s only set to grow in importance with each passing year. The reason? The rise of AI—particularly generative AI. Generative AI offers transformative benefits, from vastly improved efficiency to the broader application of data in decision-making. But these advllucantages hinge on the quality of data feeding the AI. For enterprises to fully capitalize on generative AI, the data driving models and applications must be accurate. If the data is flawed, so are the AI’s outputs. Generative AI models require vast amounts of data to produce accurate responses. Their outputs aren’t based on isolated data points but on aggregated data. Even if the data is high-quality, an insufficient volume could result in an incorrect output, known as an AI hallucination. With so much data needed, automating data pipelines is essential. However, with automation comes the challenge: humans can’t monitor every data point along the pipeline. That makes it imperative to ensure data quality from the outset and to implement output checks along the way, as noted by David Menninger, an analyst at ISG’s Ventana Research. Ignoring data quality when deploying generative AI can lead to not just inaccuracies but biased or even offensive outcomes. “As we’re deploying more and more generative AI, if you’re not paying attention to data quality, you run the risks of toxicity, of bias,” Menninger warns. “You’ve got to curate your data before training the models and do some post-processing to ensure the quality of the results.” Enterprises are increasingly recognizing this, with leaders like Saurabh Abhyankar, chief product officer at MicroStrategy, and Madhukar Kumar, chief marketing officer at SingleStore, noting the heightened emphasis on data quality, not just in terms of accuracy but also security and transparency. The rise of generative AI is driving this urgency. Generative AI’s potential to lower barriers to analytics and broaden access to data has made it a game-changer. Traditional analytics tools have been difficult to master, often requiring coding skills and data literacy training. Despite efforts to simplify these tools, widespread adoption has been limited. Generative AI, however, changes the game by enabling natural language interactions, making it easier for employees to engage with data and derive insights. With AI-powered tools, the efficiency gains are undeniable. Generative AI can take on repetitive tasks, generate code, create data pipelines, and even document processes, allowing human workers to focus on higher-level tasks. Abhyankar notes that this could be as transformational for knowledge workers as the industrial revolution was for manual labor. However, this potential is only achievable with high-quality data. Without it, AI-driven decision-making at scale could lead to ethical issues, misinformed actions, and significant consequences, especially when it comes to individual-level decisions like credit approvals or healthcare outcomes. Ensuring data quality is challenging, but necessary. Organizations can use AI-powered tools to monitor data quality, detect irregularities, and alert users to potential issues. However, as advanced as AI becomes, human oversight remains critical. A hybrid approach, where technology augments human expertise, is essential for ensuring that AI models and applications deliver reliable outputs. As Kumar of SingleStore emphasizes, “Hybrid means human plus AI. There are things AI is really good at, like repetition and automation, but when it comes to quality, humans are still better because they have more context.” Ultimately, while AI offers unprecedented opportunities, it’s clear that data quality is the foundation. Without it, the risks are too great, and the potential benefits could turn into unintended consequences. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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September 6, 2024in Generative AI
Einstein Knowledge Edits
02Sep

Einstein Knowledge Edits

Get Quick Revisions on Knowledge Articles with Einstein Knowledge Edits (Beta) Enhance your Knowledge articles quickly using Einstein generative AI with predefined revision styles. These styles can help improve grammar, conciseness, and readability. You can also customize these styles using the Prompt Builder to tailor the revisions to your business needs. This allows you to specify what information Einstein includes, how the content is formatted, and adjust the voice and tone. Where: This feature is available in Unlimited and Enterprise editions with the Einstein for Service add-on in Lightning Experience. Important: Einstein Knowledge Edits is currently in beta and is subject to Salesforce’s Beta Services Terms or a written Unified Pilot Agreement if executed by the Customer. Participation in this beta service is at the Customer’s discretion. Who: To access Knowledge Edits, you must have the following enabled: Agents also need the Prompt Template User and Einstein Knowledge Creation permission sets. How: To revise a Knowledge article: Quickly and effectively refine your Knowledge articles to meet your business standards with Einstein Knowledge Edits! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 2, 2024in Generative AI
guide to RAG
30Aug

Tectonic Guide to Rag Part 2

The first notable change in the field of language models is the significant expansion of context window sizes and a reduction in token costs. For instance, Anthropic’s largest model, Claude, has a context window exceeding 200,000 tokens, while recent reports indicate that Gemini’s context window can reach up to 10 million tokens. Under such circumstances, Retrieval-Augmented Generation (RAG) may no longer be necessary for many tasks, as all required data can be accommodated within the expanded context window. Several financial and analytical projects have already demonstrated that tasks can be solved without needing a vector database as intermediate storage. This trend of reducing token costs and increasing context window sizes is likely to continue, potentially decreasing the need for external mechanisms in LLMs, although they are still relevant for the time being. If the context window remains insufficient, methods for summarization and context compression have been introduced. LangChain, for example, offers a class called ConversationSummaryMemory to address this challenge. pythonCopy codellm = OpenAI(temperature=0) conversation_with_summary = ConversationChain( llm=llm, memory=ConversationSummaryMemory(llm=OpenAI()), verbose=True ) conversation_with_summary.predict(input=”Hi, what’s up?”) Knowledge Graphs As the volume of data continues to grow, navigating through it efficiently becomes increasingly critical. In certain cases, understanding the structure and attributes of data is essential for effective use. For example, if the data source is a company’s wiki, an LLM might not recognize a phone number unless the structure or metadata indicates that it’s the company’s contact information. Humans can infer meaning from conventions, such as the subdirectory “Company Information,” but standard RAG may miss such connections. This challenge can be addressed by Knowledge Graphs, also known as Knowledge Maps, which provide both raw data and metadata that illustrates how different entities are interconnected. This method is referred to as Graph Retrieval-Augmented Generation (GraphRAG). Graphs are excellent for representing and managing structured, interconnected information. Unlike vector databases, they excel at capturing complex relationships and attributes among diverse data types. Creating a Knowledge Graph The process of creating a knowledge graph typically involves collecting and structuring data, which requires expertise in both the subject matter and graph modeling. However, LLMs can automate a significant portion of this process by analyzing textual data, identifying entities, and recognizing their relationships, which can then be represented in a graph structure. In many cases, an ensemble of vector databases and knowledge graphs can improve accuracy, as discussed previously. For example, search functionality might combine keyword search through a regular database (e.g., Elasticsearch) and graph-based queries. LangChain can also assist in extracting structured data from entities, as demonstrated in this code example: pythonCopy codedocuments = parse_and_load_data_from_wiki_including_metadata() graph_store = NebulaGraphStore( space_name=”Company Wiki”, tags=[“entity”] ) storage_context = StorageContext.from_defaults(graph_store=graph_store) index = KnowledgeGraphIndex.from_documents( documents, max_triplets_per_chunk=2, space_name=space_name, tags=[“entity”] ) query_engine = index.as_query_engine() response = query_engine.query(“Tell me more about our Company”) Here, searching is conducted based on attributes and related entities, instead of similar vectors. If set up correctly, metadata from the company’s wiki, such as its phone number, would be accessible through the graph. Access Control One challenge with this system is that data access may not be uniform. For instance, in a wiki, access could depend on roles and permissions. Similar issues exist in vector databases, leading to the need for access management mechanisms such as Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and Relationship-Based Access Control (ReBAC). These access control methods function by evaluating paths between users and resources within graphs, such as in systems like Active Directory. To ensure the integrity of data during the ingestion phase, metadata related to permissions must be preserved in both the knowledge graph and vector database. Some commercial vector databases already have this functionality built in. Ingestion and Parsing Data needs to be ingested into both graphs and vector databases, but for graphs, formatting is especially critical since it reflects the data’s structure and serves as metadata. One particular challenge is handling complex formats like PDFs, which can contain diverse elements like tables, images, and text. Extracting structured data from such formats can be difficult, and while frameworks like LLama Parse exist, they are not always foolproof. In some cases, Optical Character Recognition (OCR) may be more effective than parsing. Enhancing Answer Quality Several new approaches are emerging to improve the quality of LLM-generated answers: While these advancements in knowledge graphs, access control, and retrieval mechanisms are promising, challenges remain, particularly around data formatting and parsing. However, these methods continue to evolve, enhancing LLM capabilities and efficiency. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more 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

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August 30, 2024in Data

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