Corporate

26Sep

OpenAI’s o1 model

The release of OpenAI’s o1 model has sparked some confusion. Unlike previous models that focused on increasing parameters and capabilities, this one takes a different approach. Let’s explore the technical distinctions first, share a real-world experience, and wrap up with some recommendations on when to use each model. Technical Differences The core difference is that o1 serves as an “agentic wrapper” around GPT-4 (or a similar model). This means it incorporates a layer of metacognition, or “thinking about thinking,” before addressing a query. Instead of immediately answering the question, o1 first evaluates the best strategy for tackling it by breaking it down into subtasks. Once this analysis is complete, o1 begins executing each subtask. Depending on the answers it receives, it may adjust its approach. This method resembles the “tree of thought” strategy, allowing users to see real-time explanations of the subtasks being addressed. For a deeper dive into agentic approaches, I highly recommend Andrew Ng’s insightful letters on the topic. However, this method comes with a cost—it’s about six times more expensive and approximately six times slower than traditional approaches. While this metacognitive process can enhance understanding, it doesn’t guarantee improved answers for straightforward factual queries or tasks like generating trivia questions, where simplicity may yield better results. Real-World Example To illustrate the practical implications, Tectonic began to deepen the understanding of variational autoencoders—a trend in multimodal LLMs. While we had a basic grasp of the concept, we had specific questions about their advantages over traditional autoencoders and the nuances of training them. This information isn’t easily accessible through a simple search; it’s more akin to seeking insight from a domain expert. To enhance our comprehension, we engaged with both GPT-4 and o1. We quickly noticed that o1’s responses were more thoughtful and facilitated a meaningful dialogue. In contrast, GPT-4 tended to recycle the same information, offering limited depth—much like how some people might respond in conversation. A particularly striking example occurred when we attempted to clarify our understanding. The difference was notable. o1 responded like a thoughtful colleague, addressing our specific points, while GPT-4 felt more like a know-it-all friend who rambled on, requiring me to sift through the information for valuable insights. Summary and Recommendations In essence, if we were to personify these models, GPT-4 would be the overzealous friend who dives into a stream of consciousness, while o1 would be the more attentive listener who takes a moment to reflect before delivering precise and relevant insights. Here are some scenarios where o1 may outperform GPT-4, justifying its higher cost: By leveraging these insights, you can better navigate the strengths of each model in your tasks and inquiries. 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

September 26, 2024in Salesforce

25Sep

AI Leader Salesforce

Salesforce Is a Wild Mustang in the AI Race In the bustling world of artificial intelligence, Salesforce Inc. has emerged as an unsurpassed and true leader. “Salesforce?” one might wonder. The company known for its customer relationship management software? How can it be an AI leader if it is only focused on each department or division (or horse) is only focused on its own survival? AI Leader Salesforce. Herds of horses have structure, unique and important roles they each play. While they survival depends greatly on each members’ independece they must remain steadfast in the roles and responsibilities they carry to the entire herd. The lead stallion must be the protector. The lead mare must organize all the mothers and foals into obedient members of the herd. But they must all collaborate. AI Leader Salesforce To stay strong and competetive Salesforce is making bold strides in AI as well. Recently, the company became the first major tech firm to introduce a new class of generative AI tools known as “agents,” which have long been discussed by others but never fully realized. Unlike its competitors, Salesforce is upfront about how these innovative tools might impact employment. This audacious approach could be the key to propelling the company ahead in the AI race, particularly as newer players like OpenAI and Anthropic make their moves. Marc Benioff, Salesforce’s dynamic CEO, is driving this change. Known for his unconventional strategies that helped propel Salesforce to the forefront of the software-as-a-service (SaaS) revolution, Benioff has secured a client base that includes 90% of Fortune 500 companies, such as Walt Disney Co. and Ford Motor Co. Salesforce profits from subscriptions to applications like Sales Cloud and Service Cloud, which help businesses manage their sales and customer service processes. At the recent Dreamforce conference, Salesforce unveiled Agentforce, a new service that enables customers to deploy autonomous AI-powered agents. If Benioff himself is the alpha herd leader, Agentforce may well be the lead mare. Salesforce distinguishes itself by replacing traditional chatbots with these new agents. While chatbots, powered by technologies from companies like OpenAI, Google, and Anthropic, typically handle customer inquiries, agents can perform actions such as filing complaints, booking appointments, or updating shipping addresses. The notion of AI “taking action” might seem risky, given that generative models can sometimes produce erroneous results. Imagine an AI mishandling a booking. However, Salesforce is confident that this won’t be an issue. “Hallucinations go down to zero because [Agentforce] is only allowed to generate content from the sources you’ve trained it on,” says Bill Patterson, corporate strategy director at Salesforce. This approach is touted as more reliable than models that scrape the broader internet, which can include inaccurate information. Salesforce’s willingness to confront a typically sensitive issue — the potential job displacement caused by AI — is also noteworthy. Unlike other AI companies that avoid discussing the impact of cost-cutting on employment, Salesforce openly addresses it. For instance, education publisher John Wiley & Sons Inc. reported that using Agentforce reduced the time spent answering customer inquiries by nearly 50% over three months. This efficiency meant Wiley did not need to hire additional staff for the back-to-school season. In the herd, the leader must acknowledge some of his own offspring will have to join other herds, there is a genetic survival of the fittest factor. I would suspect Benioff will re-train and re-purpose as many of the Salesforce family as he can, rather than seeing them leave the herd. Benioff highlighted this in his keynote, asking, “What if you could surge your service organization and your sales organization without hiring more people?” That’s the promise of Agentforce. And what if? Imagine the herd leader having to be always the alpha, always on guard, always in protective mode. When does he slngeep, eat, rest, and recuperate? Definitely not by bringing in another herd leader. The two inevitably come to arms each excerting their dominance until one is run off by the other, to survive on his own. The herd leader needs to clone himself, create additional herd, or corporate, assets to help him do his job better. Enter the power behind Salesforce’s long history with Artificial Intelligence. The effectiveness of Salesforce’s tools in delivering a return on investment remains to be seen, especially as many businesses struggle to evaluate the success of generative AI. Nonetheless, Salesforce poses a significant challenge to newer firms like OpenAI and Anthropic, which have privately acknowledged their use of Salesforce’s CRM software. For many chief innovation officers, it’s easier to continue leveraging Salesforce’s existing platform rather than adopt new technologies. Like the healthiest of the band of Mustangs, the most skilled and aggressive will thrive and survive. Salesforce’s established presence and broad distribution put it in a strong position at a time when large companies are often hesitant to embrace new tech. Its fearless approach to job displacement suggests the company is poised to profit significantly from its AI venture. As a result, Salesforce may well become a formidable competitor in the AI world. Furthermore taking its own investment in AI education to new heights, one can believe that Salesforce has an eye on people and not just profits. Much like the lead stallion in a wild herd, Salesforce is protecting itself and its biggest asset, its people! By Tectonic’s Salesforce Solutions Architect, Shannan Hearne 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

September 25, 2024in AI Tools, Artificial Intelligence, Generative AI, Google, Salesforce

23Sep

Agentforce – AI’s New Role in Sales and Service

From Science Fiction to Reality: AI’s Game-Changing Role in Service and Sales AI for service and sales has reached a critical tipping point, driving rapid innovation. At Dreamforce in San Francisco, hosted by Salesforce we explored how Salesforce clients are leveraging CRM, Data Cloud, and AI to extract real business value from their Salesforce investments. In previous years, AI features branded under “Einstein” had been met with skepticism. These features, such as lead scoring, next-best-action suggestions for service agents, and cross-sell/upsell recommendations, often required substantial quality data in the CRM and knowledge base to be effective. However, customer data was frequently unreliable, with duplicate records and missing information, and the Salesforce knowledge base was underused. Building self-service capabilities with chatbots was also challenging, requiring accurate predictions of customer queries and well-structured decision trees. This year’s Dreamforce revealed a transformative shift. The advancements in AI, especially for customer service and sales, have become exceptionally powerful. Companies now need to take notice of Salesforce’s capabilities, which have expanded significantly. Agentforce – AI’s New Role in Sales and Service Some standout Salesforce features include: At Dreamforce, we participated in a workshop where they built an AI agent capable of responding to customer cases using product sheets and company knowledge within 90 minutes. This experience demonstrated how accessible AI solutions have become, no longer requiring developers or LLM experts to set up. The key challenge lies in mapping external data sources to a unified data model in Data Cloud, but once achieved, the potential for customer service and sales is immense. How AI and Data Integrate to Transform Service and Sales Businesses can harness the following integrated components to build a comprehensive solution: Real-World Success and AI Implementation OpenTable shared a successful example of building an AI agent for its app in just two months, using a small team of four. This was a marked improvement from the company’s previous chatbot projects, highlighting the efficiency of the latest AI tools. Most CEOs of large enterprises are exploring AI strategies, whether by developing their own LLMs or using pre-existing models. However, many of these efforts are siloed, and engineering costs are high, leading to clunky transitions between AI and human agents. Tectonic is well-positioned to help our clients quickly deploy AI-powered solutions that integrate seamlessly with their existing CRM and ERP systems. By leveraging AI agents to streamline customer interactions, enhance sales opportunities, and provide smooth handoffs to human agents, businesses can significantly improve customer experiences and drive growth. Tectonic is ready to help businesses achieve similar success with AI-driven innovation. 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

September 23, 2024in Agentforce Platform, AI Tools, Data, Enterprise, Generative AI, Google, Marketing Automation, Salesforce, Salesforce Financial Services Solutions, Salesforce for Nonprofits, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services, Salesforce Manufacturing Automotive Energy, Salesforce Optimization, Salesforce Public Sector Solutions, Snowflake

21Sep

ChatGPT Open AI o1

OpenAI has firmly established itself as a leader in the generative AI space, with its ChatGPT being one of the most well-known applications of AI today. Powered by the GPT family of large language models (LLMs), ChatGPT’s primary models, as of September 2024, are GPT-4o and GPT-3.5. In August and September 2024, rumors surfaced about a new model from OpenAI, codenamed “Strawberry.” Speculation grew as to whether this was a successor to GPT-4o or something else entirely. The mystery was resolved on September 12, 2024, when OpenAI launched its new o1 models, including o1-preview and o1-mini. What Is OpenAI o1? The OpenAI o1 family is a series of large language models optimized for enhanced reasoning capabilities. Unlike GPT-4o, the o1 models are designed to offer a different type of user experience, focusing more on multistep reasoning and complex problem-solving. As with all OpenAI models, o1 is a transformer-based architecture that excels in tasks such as content summarization, content generation, coding, and answering questions. What sets o1 apart is its improved reasoning ability. Instead of prioritizing speed, the o1 models spend more time “thinking” about the best approach to solve a problem, making them better suited for complex queries. The o1 models use chain-of-thought prompting, reasoning step by step through a problem, and employ reinforcement learning techniques to enhance performance. Initial Launch On September 12, 2024, OpenAI introduced two versions of the o1 models: Key Capabilities of OpenAI o1 OpenAI o1 can handle a variety of tasks, but it is particularly well-suited for certain use cases due to its advanced reasoning functionality: How to Use OpenAI o1 There are several ways to access the o1 models: Limitations of OpenAI o1 As an early iteration, the o1 models have several limitations: How OpenAI o1 Enhances Safety OpenAI released a System Card alongside the o1 models, detailing the safety and risk assessments conducted during their development. This includes evaluations in areas like cybersecurity, persuasion, and model autonomy. The o1 models incorporate several key safety features: GPT-4o vs. OpenAI o1: A Comparison Here’s a side-by-side comparison of GPT-4o and OpenAI o1: Feature GPT-4o o1 Models Release Date May 13, 2024 Sept. 12, 2024 Model Variants Single Model Two: o1-preview and o1-mini Reasoning Capabilities Good Enhanced, especially in STEM fields Performance Benchmarks 13% on Math Olympiad 83% on Math Olympiad, PhD-level accuracy in STEM Multimodal Capabilities Text, images, audio, video Primarily text, with developing image capabilities Context Window 128K tokens 128K tokens Speed Fast Slower due to more reasoning processes Cost (per million tokens) Input: $5; Output: $15 o1-preview: $15 input, $60 output; o1-mini: $3 input, $12 output Availability Widely available Limited to specific users Features Includes web browsing, file uploads Lacks some features from GPT-4o, like web browsing Safety and Alignment Focus on safety Improved safety, better resistance to jailbreaking ChatGPT Open AI o1 OpenAI o1 marks a significant advancement in reasoning capabilities, setting a new standard for complex problem-solving with LLMs. With enhanced safety features and the ability to tackle intricate tasks, o1 models offer a distinct upgrade over their predecessors. 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

September 21, 2024in Data, Enterprise, Generative AI

20Sep

Thoughts on Workday With Illuminate

Workday Expands AI Across HR and Finance Platforms with ‘Illuminate’ Workday is significantly enhancing its AI capabilities within its HR and finance platforms through a new set of updates called Illuminate. These updates aim to improve automation and increase productivity by embedding AI more broadly across various HR processes. From routine tasks like content generation to complex problem-solving, Workday’s AI now identifies inefficiencies in HR workflows and offers recommendations for improvement. Thoughts on Workday With Illuminate follow. A key feature of Illuminate is a series of AI agents designed to assist in areas such as succession planning. These agents can suggest internal candidates that HR teams might overlook, helping organizations identify potential leaders within their workforce. During a press briefing ahead of the Workday Rising conference, TechTarget asked if the AI agent used in succession planning could fully capture the intricacies of the employee experience and assess leadership potential. David Somers, Chief Product Officer at Workday, acknowledged the sensitivity of succession planning but emphasized that AI is used to augment—not replace—human decision-making. The agents provide recommendations, while the final hiring decisions still involve talent acquisition professionals and interview panels. Workday’s updates include tools for a wide range of tasks, from content summarization to more advanced capabilities such as detecting bottlenecks in onboarding processes and suggesting optimizations. “These AI agents will streamline common business workflows, boosting productivity and freeing up users to focus on strategic, meaningful work,” Somers explained. While AI has long been part of Workday’s offerings, generative AI is now driving rapid transformation in HR practices. Workday’s Illuminate platform combines data with contextual insights, offering features like compensation data tailored to a company’s specific information. Users can access these AI capabilities through Workday Assistant, a generative AI chatbot that integrates with Microsoft Teams and Slack. This tool will be generally available early next year, making it easier for teams to interact with Workday’s AI-powered systems. HR industry expert Josh Bersin sees Workday’s Illuminate as part of a broader trend of AI agents in the HR space, similar to SAP’s Joule. He believes Workday’s new AI agents will be a major focus for the company, though building out all the necessary Workday transactions into these tools will take time. Bersin does not foresee trust issues among Workday users regarding Illuminate, noting that the platform isn’t open to non-Workday data, which limits concerns around data security. Bersin’s own AI assistant, Galileo, is also expected to integrate with Workday’s platform in the future, further enhancing its capabilities. rativAccording to recent Gartner surveys from March and June, the majority of HR leaders are adopting AI in their organizations. Only 15% of respondents indicated they had no plans to incorporate generative AI into their HR processes, signaling widespread acceptance of AI tools like those Workday is rolling out with Illuminate. 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

September 20, 2024in AI Tools, Data, Generative AI

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

September 16, 2024in Salesforce

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

September 15, 2024in Enterprise

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

September 11, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Generative AI, Salesforce Education Cloud, Salesforce Education Solutions

07Sep

Adopting Salesforce Security Policies

Data breaches reached an all-time high in 2023, affecting more than 234 million individuals, and there’s no sign of the trend slowing down. At the center of this challenge is how organizations allocate resources to safeguard customer data. One of the most critical systems for managing this data is CRM platforms like Salesforce, used by over 150,000 U.S. businesses. However, security blind spots within Salesforce continue to pose significant risks. To address these concerns, the National Institute of Standards and Technology (NIST) offers a strategic framework for Salesforce security teams. In February 2024, NIST released Version 2.0 of its Cybersecurity Framework (CSF), marking the first major update in a decade. Key improvements include the introduction of a new “Govern” function, streamlining of categories to simplify usability, and updates to the “Respond” function to enhance incident management. This framework now applies across all industries, not just critical infrastructure. For Salesforce security leaders, these changes will significantly affect how they manage security, from aligning Salesforce practices with enterprise risk strategies to strengthening oversight of third-party apps. Here’s how these updates will influence Salesforce security going forward. What is the NIST Cybersecurity Framework 2.0? The NIST Cybersecurity Framework, first launched in 2014, was developed after an executive order by President Obama, aiming to provide a standardized set of guidelines to improve cybersecurity across critical infrastructure. The framework’s objectives include: The newly updated NIST CSF 2.0, released in 2024, expands on the original framework, providing organizations with structured, yet flexible, guidance for managing cybersecurity risks. It revolves around three core components: the CSF Core, CSF Profiles, and CSF Tiers. Key Components of NIST Cybersecurity Framework 2.0 These components help organizations understand, assess, and improve their cybersecurity posture, forming the basis for risk-informed strategies that align with organizational needs and the evolving threat landscape. Key Updates in the NIST Cybersecurity Framework 2.0 and Their Impact on Salesforce Security The 2024 updates to NIST CSF offer insights that Salesforce security leaders can use to align their strategies with evolving cybersecurity risks. Implementation Strategies for Salesforce Security Leaders To incorporate CSF 2.0 into Salesforce security operations, leaders should: Conclusion: Embracing NIST CSF 2.0 to Strengthen Salesforce Security The 2024 NIST Cybersecurity Framework updates offer crucial insights for Salesforce security leaders. By adopting these practices, organizations can enhance data protection, strengthen incident response capabilities, and ensure business continuity—critical for those relying on Salesforce for managing sensitive customer 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 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

September 7, 2024in Data, Enterprise, Salesforce, Salesforce Shield, Technology

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

September 6, 2024in Data, Salesforce Development Services, Salesforce Public Sector Solutions, Technology

30Aug

Detecting the Hot Chatbot

All the tech giants are eager to prove their chatbot is the hottest in the market. Like wild stallions fighting over the mares, Google, Meta, Microsoft, and OpenAI are competing to show that their AI models have the most momentum. Companies with built-in AI like Salesforce occupy a broader sector. Detecting the Hot Chatbot is the challenge for the consumer. Why Detecting the Hot Chatbot Matters These companies have poured immense resources—both talent and money—into developing their models and adding new features. Now, they’re keen to showcase that these investments are yielding results. What’s Happening In the past few dayss, several major players have released new usage statistics: The Big Picture Generative AI is still in its early stages, and the entire industry faces the challenge of proving that these products deliver real value—whether by capturing market share from the lucrative search industry or by helping companies save money through increased productivity. How are you Detecting the Hot Chatbot. In the short term, however, everyone is eager to show they’re leading the pack. TV commercials for generative AI are now common, with Meta, Google, and Microsoft all airing spots, although the effectiveness of these ads varies. Some companies even boast that their commercials were created using AI—not necessarily the most convincing selling point. Between the Lines The competition isn’t just about consumer popularity; it’s also spilling over into the battle to secure business customers. On Wednesday’s earnings call, Salesforce CEO Marc Benioff made a point of distinguishing Salesforce’s new Agentforce AI sales assistant from Microsoft’s Copilot offerings. “This is not Copilot,” Benioff said. “So many customers are disappointed with what they bought from Microsoft Copilot because they’re not getting the accuracy and response they want. Microsoft has let down many customers with AI.” Microsoft quickly responded in a comment to CNBC. “We are hearing something quite different from our Copilot for Microsoft 365 customers,” said corporate VP Jared Spataro. “When I talk to CIOs directly, and if you look at recent third-party data, organizations are betting on Microsoft for their AI transformation.” The Bottom Line The competition is heating up as tech giants vie to prove they have the upper hand in the AI race and the Hot Chatbot. Customers will ultimately decide. 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

August 30, 2024in Generative AI, Salesforce Financial Services Solutions, Salesforce for Nonprofits, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services, Salesforce Manufacturing Automotive Energy, Salesforce Public Sector Solutions

16Aug

Salesforce Thematic Personalization

Thematic Personalization Made Simple with Salesforce Leverage the power of thematic personalization to tailor your messaging and creative assets for each target audience directly within Salesforce. If you’re a Faraday user, integrating thematic personalization predictions into your CRM is a seamless way to elevate your outreach. With predictions accessible in Salesforce, you can shape your content to better resonate with your leads and contacts. This integration helps you understand what appeals to your audience, ensuring your communications are more relevant and impactful—all while working within the tools you already know. It’s an effortless way to enhance personalization and make the most of your data. Step-by-Step Integration Guide Step 1: Connect Your Data SourcesUse the link below to connect Salesforce to Faraday. Alternatively, you can skip this step and upload your data using CSV files to get started.👉 Connect to Salesforce Step 2: Ingest Data into Event StreamsStream your data into Faraday to enable the platform to interpret its meaning. Follow the link below for guidance on setting up event streams to power this template.👉 Ingest Data Step 3: Organize Your Customer DataGroup your data into cohorts—key building blocks in Faraday. These cohorts enable you to predict customer behavior with precision.👉 Define Cohorts Step 4: Declare Your Prediction ObjectivesOnce your cohorts are ready, instruct Faraday to predict the behaviors you care about. Follow the documentation using the link below.👉 Set Prediction Goals Step 5: Build and Deploy Your Personalization PipelineCreate a content personalization pipeline and deploy it to Salesforce to use predictions for shaping creative and messaging.👉 Deploy Content Personalization Step 6: Finalize Deployment to SalesforceComplete your setup by creating a deployment target within Salesforce or, if preferred, export your results as a CSV file.👉 Deploy to Salesforce Why Integrate Thematic Personalization?This integration empowers you to seamlessly incorporate predictive insights into your CRM workflow, enabling more personalized, effective communications. With minimal effort, you can connect with your audience on a deeper level, enhance engagement, and achieve better results. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

August 16, 2024in Data, Salesforce

14Aug

When The Customers Prefer Self-Service

Assistance is crucial for complex issues, but for simpler problems, customers typically prefer the convenience of self-service tools like account portals, FAQs, and chatbots. This preference is especially strong among digital natives, such as millennials and Gen Z. However, deploying self-service tools requires careful planning. For instance, over two-thirds of customers abandon a company’s chatbot after a single negative experience, underscoring the importance of a positive initial interaction. Statistics show that 72% of customers use self-service portals, and 55% engage with self-service chatbots. The willingness of nearly half of all customers, including 60% of millennials, to pay more for superior customer service highlights the importance of customer experience in an era of price sensitivity. Customers expect instant responses, creating a scalability challenge for service teams but also an opportunity to offer premium service. Instant responses can set a company apart, as even well-regarded brands often struggle to maintain quick and seamless connections between customers and agents. Self-service platforms must be easily adjustable, not only to address areas needing improvement but also to adapt to changing market demands. Customers now expect proactive service rather than the traditional reactive approach. Despite this, customer service is often perceived as reactive. The time and effort customers spend resolving service issues are significant, especially when service teams are inconsistently trained and equipped, leading to a perception that quality service is a matter of luck. Consistency across channels, devices, and departments is highly valued but often lacking. Many customers find themselves repeating information to different representatives, indicating a fragmented information environment. Poorly integrated technology and processes leave 55% of customers feeling as if they interact with separate departments rather than a unified company. Disconnected experiences are a major source of frustration. Prompt resolution of issues is a top priority for customers, and many find it quicker to search for answers themselves than to contact the company. Self-service not only facilitates quick problem-solving but also empowers customers to address issues at their own pace and learn as much or as little as they wish. In terms of preferences, over 67% of customers prefer some form of self-service over speaking with a representative. Additionally, 73% prefer using the company’s website for support rather than relying on social media, SMS, or live chat apps. Don’t always assume the “latest and greatest” solutions available are the best solutions for your customers. A self-service strategy involves providing customers with tools to resolve their needs independently, reducing the need for representative assistance. Reduce staffing needs and increase speed to answers for customers. Its a win win. However, implementing self-service can face challenges, such as confusing navigation, lack of ongoing attention, inflexibility, failure to incorporate feedback, constraints on users, extra work, lack of human interaction, difficulty in personalization, and the need for continuous analysis and monitoring. Successful self-service integration requires addressing these factors to meet customer expectations. Contact Tectonic for assistance bringing your self-service solutions to your customers. 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

August 14, 2024in Salesforce Commerce Cloud, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Manufacturing Automotive Energy, Salesforce Optimization, Salesforce Service Cloud, Technology

09Aug

Demandbase One for Sales iFrame

Understanding the Demandbase One for Sales iFrame in Salesforce The Demandbase One for Sales iFrame (formerly known as Sales Intelligence) allows sales teams to access deep, actionable insights directly within Salesforce. This feature provides account-level and people-level details, including engagement data, technographics, intent signals, and even relevant news, social media posts, and email communications. By offering this level of visibility, sales professionals can make informed decisions and take the most effective next steps on accounts. Key Points: Overview of the Demandbase One for Sales iFrame The iFrame is divided into several key sections: Account, People, Engagement, and Insights tabs. Each of these provides critical information to help you better understand and engage with the companies and people you’re researching. Account Tab People Tab Engagement Tab Final Notes: The Demandbase One for Sales iFrame is a powerful tool that provides a complete view of account activity, helping sales teams make informed decisions and drive results. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

August 9, 2024in Data

02Aug

Tectonic Guide to RAG

Guide to RAG (Retrieval-Augmented Generation) Retrieval-Augmented Generation (RAG) has become increasingly popular, and while it’s not yet as common as seeing it on a toaster oven manual, it is expected to grow in use. Despite its rising popularity, comprehensive guides that address all its nuances—such as relevance assessment and hallucination prevention—are still scarce. Drawing from practical experience, this insight offers an in-depth overview of RAG. Why is RAG Important? Large Language Models (LLMs) like ChatGPT can be employed for a wide range of tasks, from crafting horoscopes to more business-centric applications. However, there’s a notable challenge: most LLMs, including ChatGPT, do not inherently understand the specific rules, documents, or processes that companies rely on. There are two ways to address this gap: How RAG Works RAG consists of two primary components: While the system is straightforward, the effectiveness of the output heavily depends on the quality of the documents retrieved and how well the Retriever performs. Corporate documents are often unstructured, conflicting, or context-dependent, making the process challenging. Search Optimization in RAG To enhance RAG’s performance, optimization techniques are used across various stages of information retrieval and processing: Python and LangChain Implementation Example Below is a simple implementation of RAG using Python and LangChain: pythonCopy codeimport os import wget from langchain.vectorstores import Qdrant from langchain.embeddings import OpenAIEmbeddings from langchain import OpenAI from langchain_community.document_loaders import BSHTMLLoader from langchain.chains import RetrievalQA # Download ‘War and Peace’ by Tolstoy wget.download(“http://az.lib.ru/t/tolstoj_lew_nikolaewich/text_0073.shtml”) # Load text from html loader = BSHTMLLoader(“text_0073.shtml”, open_encoding=’ISO-8859-1′) war_and_peace = loader.load() # Initialize Vector Database embeddings = OpenAIEmbeddings() doc_store = Qdrant.from_documents( war_and_peace, embeddings, location=”:memory:”, collection_name=”docs”, ) llm = OpenAI() # Ask questions while True: question = input(‘Your question: ‘) qa = RetrievalQA.from_chain_type( llm=llm, chain_type=”stuff”, retriever=doc_store.as_retriever(), return_source_documents=False, ) result = qa(question) print(f”Answer: {result}”) Considerations for Effective RAG Ranking Techniques in RAG Dynamic Learning with RELP An advanced technique within RAG is Retrieval-Augmented Language Model-based Prediction (RELP). In this method, information retrieved from vector storage is used to generate example answers, which the LLM can then use to dynamically learn and respond. This allows for adaptive learning without the need for expensive retraining. Guide to RAG RAG offers a powerful alternative to retraining large language models, allowing businesses to leverage their proprietary knowledge for practical applications. While setting up and optimizing RAG systems involves navigating various complexities, including document structure, query processing, and ranking, the results are highly effective for most business use cases. 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

August 2, 2024in Data

OpenAI’s o1 model

ChatGPT Open AI o1

Thoughts on Workday With Illuminate

GPT-o1 GPT5 Review

AI-Driven Chatbots in Education

Citizen Development

Salesforce Thematic Personalization

Tectonic Guide to RAG

Recent Posts

Understanding the Causes of Disillusionment with Generative AI

Meta Joins the Race to Reinvent Search with AI

Google Prepares AI-Powered Jarvis Agent

Is the Future Agentic for ERP?

AI is Transforming Threat Detection

Contact Us

Be in touch today — and start your business on a path to success.

Category

Archives