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What is OpenAI Strawberry?
23Jul

What is OpenAI Strawberry?

OpenAI’s Secret Project: “Strawberry” Background and Goals OpenAI, the company behind ChatGPT, is working on a new AI project codenamed “Strawberry,” according to an insider and internal documents reviewed by Reuters. This project, whose details have not been previously reported, aims to showcase advanced reasoning capabilities in OpenAI’s models. The project seeks to enable AI to not only generate answers to queries but also plan and navigate the internet autonomously to perform “deep research.” What is OpenAI Strawberry? Project Overview The “Strawberry” initiative represents an evolution of the previously known Q* project, which demonstrated potential in solving complex problems like advanced math and science questions. While the precise date of the internal document is unclear, it outlines plans for using Strawberry to enhance AI’s reasoning and problem-solving abilities. The source describes the project as a work in progress, with no confirmed timeline for its public release. Technological Approach Strawberry is described as a method of post-training AI models, refining their performance after initial training on large datasets. This post-training phase involves techniques such as fine-tuning, where models are adjusted based on feedback and examples of correct and incorrect responses. The project is reportedly similar to Stanford’s 2022 “Self-Taught Reasoner” (STaR) method, which uses iterative self-improvement to enhance AI’s intelligence levels. Potential and Challenges If successful, Strawberry could revolutionize AI by improving its reasoning capabilities, allowing it to tackle complex tasks that require multi-step problem-solving and planning. This could lead to significant advancements in scientific research, software development, and various other fields. However, the project also raises concerns about ethical implications, control, accountability, and bias, necessitating careful consideration as AI becomes more autonomous. Industry Context OpenAI is not alone in this pursuit. Other major tech companies like Google, Meta, and Microsoft are also experimenting with improving AI reasoning. The broader goal across the industry is to develop AI that can achieve human or super-human levels of intelligence, capable of making major scientific discoveries and planning complex tasks. Conclusion OpenAI’s project Strawberry represents a significant step forward in AI research, pushing the boundaries of what AI can achieve. While the project is still in its early stages, its potential to enhance AI reasoning capabilities is significant. As OpenAI continues to develop and refine Strawberry, its impact on the future of artificial intelligence will be closely watched by researchers and industry leaders alike. 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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July 23, 2024in Salesforce
Patient Trust Tanked in Healthcare During COVID
21Jul

Patient Trust Tanked in Healthcare During COVID

Patient Trust in Healthcare Declined During COVID-19 Pandemic Patient trust in healthcare providers significantly declined during the COVID-19 pandemic, a trend that some experts believe could threaten public health. New data published in JAMA Network Open outlines the negative impact the pandemic had on patient trust levels. Patient Trust Tanked in Healthcare During COVID. The study, which analyzed survey results collected between April 2020 and January 2024, revealed a 30 percentage point drop in self-reported patient trust. Factors such as age, gender (specifically female), lower educational attainment, lower income, Black race, and living in rural areas were associated with lower trust levels, according to the researchers. These findings come as the healthcare industry examines the broader implications of the pandemic. The focus on patient trust is crucial because of the significant role healthcare providers play in public health and the profound impact the pandemic had on societal attitudes. “During the COVID-19 pandemic, medicine and public health became politicized, with the internet amplifying public figures and even some physicians encouraging distrust in public health experts and scientists,” the investigators wrote. “As such, the pandemic may have represented a turning point in trust, with a profession previously seen as trustworthy increasingly subject to doubt.” The data, drawn from 24 waves of surveys involving more than 443,000 individuals over age 18, showed that healthcare professionals began the pandemic with high trust ratings—71.5% of individuals reported trust in physicians and hospitals. However, by January 2024, this number had fallen to 40.1%. The decline in trust could have serious repercussions for public health. Lower patient trust was linked to a reduced likelihood of receiving flu or COVID-19 vaccinations. Patient Trust Tanked in Healthcare During COVID “Our results cannot establish causation, but in the context of prior studies documenting associations between physician trust and more positive health outcomes, they raise the possibility that the decrease in trust during the pandemic could have long-lasting public health implications,” the researchers explained. Conversely, higher levels of trust were associated with healthier behaviors, particularly the receipt of the COVID-19 vaccine, flu shots, and COVID-19 boosters. To address this issue, the healthcare sector should focus on reaffirming patient trust in physicians and hospitals. However, this may be a challenging task. A previous Cochrane review found that no intervention meaningfully changed trust in physicians, despite numerous efforts that generally had modest effects. “A better understanding of groups exhibiting particularly low trust, and the factors associated with that diminished trust, may be valuable in guiding future intervention development and deployment,” the researchers suggested. These findings contrast sharply with the early stages of the pandemic, including the COVID-19 vaccine rollout when public health experts touted doctors as among the most trusted COVID-19 messengers. The study could not pinpoint a specific reason for the loss of patient trust, noting that it was not linked to political affiliation nor fully explained by a lack of trust in science. This indicates that there was something particular about healthcare itself that contributed to the decline in trust during the pandemic. Further research is necessary to uncover more trends among individuals whose trust levels decreased during the pandemic, the researchers recommended. 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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July 21, 2024in Salesforce Health and Life Sciences Solutions, Salesforce Implementation Services, Salesforce Public Sector Solutions
Private Connectivity Between Salesforce and On-Premise Network
19Jul

Private Connectivity Between Salesforce and On-Premise Network

Salesforce is an AWS Partner and a trusted global leader in customer relationship management (CRM). Hyperforce is the next-generation Salesforce architecture, built on Amazon Web Services (AWS). Private Connectivity Between Salesforce and On-Premise Network explained. When business applications developed on Hyperforce are integrated with on-premises systems, traffic in both directions will flow over the internet. For customers in heavily regulated industries such as the public sector and financial services, programmatic access of the Salesforce APIs hosted on Hyperforce from on-premises systems is required to traverse a private connection. Conversely, accessing on-premises systems from business applications running in Hyperforce is required to use a private connection. In this insight, AWS describes how AWS Direct Connect and AWS Transit Gateway can be used in conjunction with Salesforce Private Connect to facilitate the private, bidirectional exchange of organizational data. Architectural overview How to use AWS Direct Connect to establish a dedicated, managed, and reliable connection to Hyperforce. The approach used a public virtual interface to facilitate connectivity to public Hyperforce endpoints. The approach in this insight demonstrates the use of a private or transit virtual interface to establish a dedicated, private connection to Hyperforce using Salesforce Private Connect. Approach AWS Direct Connect is set up between the on-premises network and a virtual private cloud (VPC) residing inside a customer’s AWS account to provide connectivity from the on-premises network to AWS. The exchange of data between the customer VPC and Salesforce’s transit VPC is facilitated through the Salesforce Private Connect feature, based on AWS PrivateLink technology. AWS PrivateLink allows consumers to securely access a service located in a service provider’s VPC as if it were located in the consumer’s VPC. Using Salesforce Private Connect, traffic is routed through a fully managed network connection between your Salesforce organization and your VPC instead of over the internet. The following table shows the definitions of inbound and outbound connections in the context of Salesforce Private Connect: Direction Inbound Outbound Description Traffic that flows into Salesforce Traffic that flows out of Salesforce Use cases AWS to Salesforce Salesforce to AWS On-premises network to Salesforce Salesforce to on-premises network Inbound and Outbound This pattern can only be adopted for Salesforce services supported by Salesforce Private Connect, such as Experience Cloud, Financial Services Cloud, Health Cloud, Platform Cloud, Sales Cloud, and Service Cloud. Check the latest Salesforce documentation for the specific Salesforce services that are supported. Furthermore, this architecture is only applicable to the inbound and outbound exchange of data and does not pertain to the access of the Salesforce UI. The following diagram shows the end-to-end solution of how private connectivity is facilitated bidirectionally. In this example, on-premises servers located on the 10.0.1.0/26 network are required to privately exchange data with applications running on the Hyperforce platform. Figure 1: Using AWS Direct Connect and Salesforce Private Connect to establish private, bidirectional connectivity Prerequisites for Private Connectivity Between Salesforce and On-Premise Network In order to implement this solution, the following prerequisites are required on both the Salesforce and AWS side. Salesforce Refer to Salesforce documentation for detailed requirements on migrating your Salesforce organization to Hyperforce. AWS Network flow between on-premises data center and Salesforce API The following figure shows how both inbound and outbound traffic flows through the architecture. Figure 2: Network flow between on-premises data center and Salesforce Inbound Outbound Considerations for Private Connectivity Between Salesforce and On-Premise Network Before you set up the private, bidirectional exchange of organizational data with AWS Direct Connect, AWS Transit Gateway, and Salesforce Private Connect, review these considerations. Resiliency We recommend that you set up multiple AWS Direct Connect connections to provide resilient communication paths to the AWS Region, especially if the traffic between your on-premises resources and Hyperforce is business-critical. Refer to the AWS documentation on how to achieve high and maximum resiliency for your AWS Direct Connect deployments. For inbound traffic flow, we recommend that the VPC endpoint is configured across Availability Zones for high availability. Configure customer DNS records for the Salesforce API with IP addresses associated with the VPC endpoint and implement the DNS failover or load-balancing mechanism on the customer side. For outbound traffic flow, we recommend that you configure your Network Load Balancer with two or more Availability Zones for high availability. Security For inbound traffic flow, source IP addresses used by the incoming connection are displayed in the Salesforce Private Connect inbound configuration. We recommend that these IP ranges be used in Salesforce configurations that permit the enforcement of source IP. Refer to the Salesforce documentation Restrict Access to Trusted IP Ranges for a Connected App to learn how you can use these IP ranges can to control access to the Salesforce APIs. You access Salesforce APIs using an encrypted TLS connection. AWS Direct Connect also offers a number of additional data in transit encryption options, including support for private IP VPNs over AWS Direct Connect and MAC security. An IP virtual private network (VPN) encrypts end-to-end traffic using an IPsec VPN tunnel, while MAC Security (MACsec) provides point-to-point encryption between devices. For outbound traffic flow, we recommend that you configure TLS listeners on your Network Load Balancers to ensure that traffic to the Network Load Balancer is encrypted. Cost optimization If your use case is to solely facilitate access to Salesforce, you can use a virtual private gateway and a private VIF instead to optimize deployment costs. However, if you plan to implement a hub-spoke network transit hub interconnecting multiple VPCs, we recommend the use of a transit gateway and a transit VIF for a more scalable approach. Refer to the Amazon Virtual Private Cloud Connectivity Options whitepaper and AWS Direct Connect Quotas for the pros and cons of each approach. Conclusion Salesforce and AWS continue to innovate together to provide multiple connectivity approaches to meet customer requirements. This post demonstrated how AWS Direct Connect can be used in conjunction with Salesforce Private Connect to secure end-to-end exchanges of data in industries where the use of the internet is not an option. 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

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July 19, 2024in Hyperforce
AI Agents in Line at HR
03Jul

AI Agents in Line at HR

AI Agents in Line at HR may only be a satirical cartoon for a very short time. Sorry, Farside, but your AI bits may not be able to keep up with AI. July, 2034 — A new software unicorn has just emerged inbehind a bar in a pub in East London. Unicorn, by the way, descibes a startup company valued at over $1 billion, not necessarily with a billion dollar concept. Back to East London behind the soggy bar. Hey, its our fantasy. Besides if Amazon can start in a garage, isn’t anything possible? The CEO logs in as usual and gathers daily updates from the team. The Chief Technology Officer is suggesting a new feature to deploy. The Chief Product Officer wants to redesign the CRM (or whatever CRM has evolved to) integration. The Chief Revenue Officer is showing off the new pipeline, forecast by Accountant in a Box. The Chief Customer Officer is discussing the latest customer levitation tools and product feedback. The Chief Information Security Officer has found a new privacy conflict, which they are addressing with a newly-revised infrastructure set-up. And the Head of HR is fretting about the latest round of IT candidates. This sounds like every software business you’ve ever heard of. But the difference is that the CEO’s teammates are entirely AI, not human: The CTO is Lovable. The CPO is Cogna. The CCO is Gradient Labs. The CRO is 11x. The CISO is Zylon. Back to 2024: The Rise of AI Agents In 2024, the hottest topic in software is AI agents, or Agentic AI. Founders are rapidly standing up agentic applications that can solve specific needs in functions like sales and customer services — without a human required. Software buyers, seeing real opportunities to quickly improve their P&L, are swiftly building or purchasing these agentic products. Investors have poured hundreds of millions of dollars into startups in this space in recent months. Even Salesforce wasn’t launched with a silver AI spoon in its mouth. Salesforce began investing in artificial intelligence (AI) in 2014, when the company started acquiring machine learning startups and announced its Customer Success Platform. In 2016, Salesforce launched Einstein, its AI platform that supports several of its cloud services. Einstein is built into Salesforce products and includes features like natural language processing, machine learning, and predictive analytics. It helps organizations automate processes, make decisions based on insights, and improve the customer experience. YouTube How To Increase Revenue Using AI for CRM: Salesforce … Feb 12, 2024 — What is Salesforce Einstein? Salesforce Einstein is the first trusted artifici… TechForce Services How does Salesforce Use AI for Business Growth? Jan 31, 2024 — Powered by technologies like Machine Learning, Natural Language Processing, im… saasguru · LinkedIn · 7mo History of Salesforce AI From Predictive to Generative – LinkedIn Published Nov 27, 2023. In 2014, Salesforce, under the visionary leadership of… Twistellar AI in Salesforce: History, Present State and Prospects Organizations generate tons of data on marketing and sales, and surely your sales managers… Wikipedia Salesforce – Wikipedia In October 2014, Salesforce announced the development of its Customer Success Platform. Less than ten years ago, folks. Salesforce’s large database of data has helped the company address AI challenges quickly and with quality. The company’s data cloud offering provides AI with the right information at the right time, which can reduce friction and improve the customer experience.  Salesforce’s AI-powered solutions include: To catalyze this evolution, Salesforce strategically acquired RelateIQ in 2014. This move injected machine learning into the Salesforce ecosystem, capturing workplace communications data and providing valuable insights. Europe is home to many of these exciting companies. For example, H, a French AI agent startup, raised a $220 million seed round in May. Beyond RPA: The New Wave of AI Agents AI agents represent a significant step-change from Robotic Process Automation (RPA) bots, which, as explored last year, have several limitations due to their deterministic nature. Next-generation AI agents are non-deterministic, meaning that instead of stopping at a “dead end,” they can learn from mistakes and adjust their series of tasks. Not entirely unlock the mouse running the same maze over and over for the cheese. Eventually Mr. Squeakers learns which paths are dead ends and avoids them by making better choices at intersections. In AI Agents this makes them suited to complex and unstructured tasks and means they can transform the journey from intent to implementation in software development. They can deliver “pure work,” rather than acting only as a helpful co-pilot. The rise of AI agents is not only an opportunity to expand automation beyond what is possible with RPA but also to broadly redefine how knowledge work is performed. And by who. And even how is it defined. Given the right guardrails, next-generation AI agents have the potential to effectively and safely replace knowledge workers in many business scenarios. AI Agents in Action These agents are about to revolutionize the world of work as we know it and are already getting started. For example, Klarna recently revealed that its AI agent system handled two-thirds of customer chats in its first month in operation. While HR may not be swamped with AI CVs yet, it is certainly fathomable. One would suppose those candidates would have to be reviewed and interviewed by IT, not just HR. Here’s another deep thought. The internet of things (IoT) first appeared in a speech by Peter T. Lewis in September 1985. The Internet of Things (IoT) is a network of physical devices that can collect and transmit data over the internet using sensors, software, and other technologies. IoT devices can communicate with each other and with the cloud, and can even perform data analysis and be controlled remotely. The IoT concept was smart homes, health care environments, office spaces, and transportation. Only recently have we begun to think of the IoT as including the actual computers, or AI, in addition to sensored devices. It isn’t exactly a chicken and the egg question, but more of a

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July 3, 2024in Generative AI
Hubspot Hacked
01Jul

Hubspot Hacked

HubSpot recently disclosed a “security incident” where unauthorized access was attempted on several customer accounts. HubSpot is an American software company that provides tools for inbound marketing, sales, and customer service. It was founded in 2006 by Brian Halligan and Dharmesh Shah, and is today best-known for its all-in-one growth platform that helps businesses attract visitors, convert leads, and close customers.. The CRM company detected the incident on June 22, though it was publicly acknowledged six days later by Alyssa Robinson, Chief Information Security Officer at HubSpot. HubSpot seems to have suffered a data breach, but claims to have everything in hand – for now. Robinson stated that the incident involved bad actors targeting a limited number of HubSpot customers, aiming to gain unauthorized access to their accounts. Upon detection, HubSpot promptly activated its incident response procedures and has since been in contact with affected customers, taking necessary steps to revoke unauthorized access and safeguard customer data. HubSpot Hacked With how the statement was worded, it would seem that the attackers, whoever they are, tried to break into the account – but not necessarily succeeded. Still, the company proceeded with the usual practice in case of a cyberattack: “HubSpot triggered our incident response procedures, and since June 22 we have been contacting impacted customers and taking necessary steps to revoke the unauthorized access and protect our customers and their data,” said Robinson. As of Friday, June 28, HubSpot has not disclosed any communication from the hacking group, nor has it specified the full scope of the incident or the exact number of impacted customers. Despite having over 100,000 paying customers and achieving significant financial milestones, such as breaking the billion annual recurring revenue (ARR) mark, HubSpot’s stock price remained stable amid the news, which surfaced through TechCrunch. Ironically, this incident follows HubSpot’s recent announcement of new data protection capabilities for its Smart CRM users. However, it underscores the ongoing challenges faced by major enterprise tech providers regarding cybersecurity. HubSpot says fewer than 50 customer accounts were victims of a breach in late June, all impacted customers were notified and all has been quiet since the initial incident. As of May 2024, HubSpot had more than 216,000 customers, so an incident that impacts fewer than 50 doesn’t seem like a big deal, unless of course you’re one of the accounts involved. What we know:  The company is not releasing many details about the incident other than the basic facts. The company said in a June 28 release that it detected a security incident on June 22, 2004, where bad actors were attempting to gain access to customer accounts without authorization. HubSpot’s detection of the breach triggered its incident response procedures and the company notified impacted accounts. On June 28 and again on July 1, 2024, the company reported no further signs of a problem. What’s not known at this time is whether the attack was targeting a specific group of HubSpot customers. Back in March 2022, fewer than 30 HubSpot customers were impacted by a data breach, but all of the impacted customers were in the cryptocurrency business. HubSpot joins a growing list of enterprise tech firms experiencing cybersecurity incidents. While recent arrests, such as that of the alleged ringleader behind attacks on Twilio, LastPass, and Mailchimp, offer some hope, cybersecurity threats continue to evolve with the proliferation of digital devices and AI accessibility. This trend poses new risks, including the misuse of AI technologies like deepfakes, as highlighted by concerns raised by organizations like OpenAI. As businesses expand their digital presence and adopt new technologies, they must remain vigilant against evolving cybersecurity threats to protect sensitive information and maintain customer trust. HubSpot is an American software company that provides tools for inbound marketing, sales, and customer service. It was founded in 2006 and is today best-known for its all-in-one growth platform that helps businesses attract visitors, convert leads, and close customers. Impact for Marketers As marketers, our martech stacks are heavily reliant on cloud-based SaaS applications (like HubSpot) and cloud-based data storage from vendors like Amazon’s AWS and Google Cloud. Even on-premise applications and data are a security risk. The applications running in the cloud and the data stored there are at arm’s length from your data security professionals. More than 80% of the data breaches recorded in 2023 involved data stored in the cloud, according to the Harvard Business Review. Big breaches impacting millions of consumers get a great deal of attention, like those that struck Sony or Target in years past. But smaller, targeted attacks can be devastating to the businesses that have their data exposed, though they fly under the radar of the national press. The number of reported data breaches increased 78% from 2022 to 2023. The cost of the average breach surpassed $4 million in 2023 and is up 15% since 2020. How secure is HubSpot? Is my data secure with HubSpot? All communications between a web client and HubSpot servers are protected using TLS (1.0, 1.1, 1.2) protocol encryption using 2048 bit keys. We also provide customers with the ability to enable Two-Phase Authentication (2FA) to prevent unauthorized use of their portals. Another July Hack One of the most significant data leaks in recent history is reported to have occurred on July 4. The leak, dubbed RockYou2024 by the original poster, “ObamaCare”, on a leading hacking forum, compiled 9,948,575,739 unique passwords into plain text. This means close to ten billion passwords were leaked. That said, the RockYou2024 is primarily a compilation of all previous password leaks and is built on a prior RockYou2021 compilation of 8.4 billion passwords. That means between RockYou2021 and RockYou2024, about 1.5 billion passwords were added to the list. Further, according to the hacker, at least a few of these passwords were cracked using RTX 4090, a tactic that was warned about earlier. According to Cybernews researchers, “In its essence, the RockYou2024 leak is a compilation of real-world passwords used by individuals all over the world. Revealing that many

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July 1, 2024in Salesforce Shield
Improve Patient Care and Trust
09Jun

Improve Patient Care and Trust

A recent survey conducted by Kyruus Health and shared with HealthPayerIntelligence reveals that consumers are demanding more accurate online provider data from payers to enhance access to care. Healthcare solutions from Tectonic and Salesforce improve patient care and trust by improving data accuracy. The survey, fielded by Wakefield Research in April 2024, involved 1,000 healthcare consumers. Nearly three-quarters of respondents (72%) had private health insurance, with Medicare being the second most common form of coverage (18%). The participants represented an even distribution across U.S. regions and age groups, with 57% identifying as women. Payers have historically struggled to maintain up-to-date provider directories, and this survey highlights the significant impact of these challenges. About 30% of consumers reported skipping care due to inaccurate provider information, with 70% of them seeking this data online. Consumers primarily rely on health plan websites or apps for provider information, with 32% naming these platforms as their first resource. Medicaid enrollees were particularly dependent on their plan’s digital resources, with 64% turning to these tools first. Besides health plan websites and apps, consumers also used general internet searches, provider or clinic websites, and healthcare information sites like WebMD. Social media platforms were also popular for care searches, with 77% of users turning to Facebook and 61% to YouTube. The survey also revealed that payers often fail to provide accurate cost predictions. Only 32% of respondents said their health plans offered accurate cost information. Price transparency tools are particularly important to younger generations, with 76% of Millennials and 80% of Gen Z respondents using these tools. However, 40% of Baby Boomers were unsure if their plans even offered such tools. Among those who did use them, 34% found that the tools presented incorrect provider data, with 45% of Gen Z reporting this issue. Inaccurate provider information can lead to significant negative consequences for consumers, including delays in accessing care, difficulties contacting preferred providers, and higher costs. Some consumers even reported accidentally receiving out-of-network care or forgoing care altogether due to these inaccuracies. These experiences not only hinder access to care but also damage consumer trust in their healthcare providers and payers. Overall, 80% of respondents said that inaccurate provider data affected their trust, with 27% losing trust in their health plans and 22% losing trust in their providers. The survey results underscore a clear call to action. Over 60% of consumers, and nearly 75% of Gen Z specifically, want their health plans to provide more accurate data. Tectonic has decades of experience applying Salesforce solutions to health care providers and payers. To address these concerns, the report recommends that health plans take three key steps: First, engage with members through appropriate channels, including social media. Second, unify and validate their provider data to ensure accuracy. Third, introduce self-service capabilities within their digital platforms to empower consumers. Reach out to Tectonic today if your organization needs help applying these three steps. 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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June 9, 2024in Mulesoft, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Implementation Services, Salesforce Managed Services, Salesforce Optimization
AI Outage
04Jun

AI Outage

Unlike the recent mobile device network outage recently, where affected users were screaming fowl within minutes, AI experienced an outage today and you probably didn’t even know about it. AI Outage with three systems down simultaneously. Following a prolonged outage in the early morning hours, OpenAI’s ChatGPT chatbot experienced another disruption, but this time, it wasn’t alone. On Tuesday morning, both Anthropic’s Claude and Perplexity also encountered issues, albeit these were swiftly resolved compared to ChatGPT’s downtime. ChatGPT had seemingly recovered from what OpenAI described as a “major outage” earlier today, which hit millions of users worldwide. As of 3PM ET, the generative AI platform reported “All Systems Operational.” Reports indicate that Google’s Gemini was operational, although there were some user claims suggesting it might have briefly experienced downtime as well. The simultaneous outage of three major AI providers is uncommon and could suggest a broader infrastructure issue or a problem at an internet-scale level, akin to the outages affecting multiple social media platforms concurrently. Alternatively, the issues faced by Claude and Perplexity might have been a result of an overwhelming surge in traffic following ChatGPT’s outage, rather than inherent bugs or technical glitches. What has happened to all the AI platforms? An unknown glitch has affected the activity of most of the chatbots based on generative artificial intelligence (GenAI) on Tuesday, led by OpenAI’s ChatGPT and Google’s Gemini. What has happened to all the AI platforms? An unknown glitch has affected the activity of most of the chatbots based on generative artificial intelligence (GenAI) on Tuesday, led by OpenAI’s ChatGPT and Google’s Gemini. Although they have not yet reached the status of critical services such as a search engine, email or an instant messaging application, the scope of use of AI platforms is on a steady rise, for private use, work or studies. During ChatGPT’s outage, users were unable to message the AI chatbot from its landing page. The disruption began at approximately 7:33 AM PT and was resolved around 10:17 AM PT, marking another instance of multi-hour downtime. Like1 Related Posts 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 Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more

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June 4, 2024in Salesforce Einstein
Salesforce Field Service Lightning
02Jun

Salesforce Field Service Lightning

Many companies worldwide seek quality services associated with Salesforce Field Service Lightning (FSL) to differentiate between lacking customer experiences and excellent ones. Satisfied customers associate such services with high-quality ratings, gradually building trust with the company and recommending it to others. The ability of any business to generate successful recognition and experience with clients helps establish an invaluable competitive advantage. Salesforce Field Service Lightning We are here to assist you in mapping and quoting various FSL Salesforce services such as equipment installation, repair, general customer service management, and maintenance. Field Service technicians, also known as mobile technicians, play a crucial role in delivering these tasks. They receive notifications on mobile devices and quickly find users in need of speedy solutions to their problems. What is Salesforce Field Service? Salesforce Field Service (formerly known as Field Service Lightning) is designed for the automation and optimization of work offered by dispatchers and field service agents. It ensures that no employee sacrifices any functionality of the related services when working outside the company. This system is part of the FSL Salesforce Service Cloud and aims to create a seamless workflow and avoid mistakes with the help of service technicians. Integral Parts of Salesforce Field Service After implementing Salesforce Field Service Lightning, clients can immediately see the benefits reflected in the increased efficiency of developed services. Advantages of Salesforce Field Service Lightning Bottom Line We hope this comprehensive guide on Salesforce Field Service Lightning has provided valuable insights into its aspects and benefits. Our experienced executives offer valuable advice and risk-free solutions for managing projects involving field service. You can contact Tectonic 24/7 for error removal and maintaining Salesforce FSL service deployments. Tasks such as project management and exception diagnosis are easily handled with the Service Cloud platform. We offer a strong framework for different service models and prepare reports for various service territory designs, ensuring a seamless and efficient operation. 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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June 2, 2024in Salesforce Service Cloud
Advances in AI Models
11May

Advances in AI Models

Advances in AI Models Let’s take a moment to appreciate the transformative impact large language models (LLMs) have had on the world. Before the rise of LLMs, researchers spent years training AI to generate images, but these models had significant limitations. Advances in AI Models. One promising neural network architecture was the generative adversarial network (GAN). In a GAN, two networks play a cat-and-mouse game: one tries to create realistic images while the other tries to distinguish between generated and real images. Over time, the image-creating network improves at tricking the other. While GANs can generate convincing images, they typically excel at creating images of a single subject type. For example, a GAN that creates excellent images of cats might struggle with images of mice. GANs can also experience “mode collapse,” where the network generates the same image repeatedly because it always tricks the discriminator. An AI that produces only one image repeatedly isn’t very useful. What’s truly useful is an AI model capable of generating diverse images, whether it’s a cat, a mouse, or a cat in a mouse costume. Such models exist and are known as diffusion models, named for the underlying math that resembles diffusion processes like a drop of dye spreading in water. These models are trained to connect images and text, leveraging vast amounts of captioned images on the internet. With enough samples, a model can extract the essence of “cat,” “mouse,” and “costume,” embedding these elements into generated images using diffusion principles. The results are often stunning. Some of the most well-known diffusion models include DALL-E, Imagen, Stable Diffusion, and Midjourney. Each model differs in training data, embedding language details, and user interaction, leading to varied results. As research and development progress, these tools continue to evolve rapidly. Uses of Generative AI for Imagery Generative AI can do far more than create cute cat cartoons. By fine-tuning generative AI models and combining them with other algorithms, artists and innovators can create, manipulate, and animate imagery in various ways. Here are some examples: Text-to-Image Generative AI allows for incredible artistic variety using text-to-image techniques. For instance, you can generate a hand-drawn cat or opt for a hyperrealistic or mosaic style. If you can imagine it, diffusion models can interpret your intention successfully. Text-to-3D Model Creating 3D models traditionally requires technical skill, but generative AI tools like DreamFusion can generate 3D models along with detailed descriptions of coloring, lighting, and material properties, meeting the growing demand in commerce, manufacturing, and entertainment. Image-to-Image Images can be powerful prompts for generative AI models. Here are some use cases: Animation Creating a series of consistent images for animation is challenging due to inherent randomness in generated images. However, researchers have developed methods to reduce variations, enabling smoother animations. All the use cases for still images can be adapted for animation. For example, style transfer can turn a video of a skateboarder into an anime-style animation. AI models trained on speech patterns can animate the lips of a generated 3D character. Embracing Generative AI Generative AI offers enormous possibilities for creating stunning imagery. As you explore these capabilities, it’s essential to use them responsibly. In the next unit, you’ll learn how to leverage generative AI’s potential in an ethical and effective manner. 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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May 11, 2024in Generative AI
Train On Your Own Data
29Apr

Train On Your Own Data

General-purpose large language models (LLMs) offer businesses the convenience of immediate use without requiring any special setup or customization. However, to maximize the potential of LLMs in business environments, organizations can achieve significant benefits by customizing these models through training on their own data. Custom LLMs excel at handling organization-specific tasks that generic LLMs—such as OpenAI’s ChatGPT or Google’s Gemini—may not manage as effectively. By training an LLM on data unique to the enterprise, businesses can fine-tune the model to produce responses that are highly relevant to specific products, workflows, and customer interactions. To determine whether to customize an LLM with organization-specific data, businesses should first explore the various types of LLMs and understand the advantages of fine-tuning a model on custom data sets. Following this, they can proceed with the necessary steps: identifying data sources, cleaning and formatting the data, adjusting model parameters, retraining the model, and testing it in production. Generic vs. Customized LLMs LLMs can be broadly categorized into two types: Training an LLM on custom data doesn’t imply starting from scratch; instead, it often involves fine-tuning a pre-trained generic model with additional training on the organization’s data. This approach allows the model to retain the broad knowledge it acquired during initial training while enhancing its capabilities in areas specific to the business. Benefits of Customizing an LLM The primary reason for retraining or fine-tuning an LLM is to achieve superior performance on business-specific tasks compared to using a generic model. For example, a company that wants to deploy a chatbot for customer support needs an LLM that understands its products in detail. Even if a generic LLM has some familiarity with the product from public data sources, it may lack the depth of knowledge that the company’s internal documentation provides. Without this comprehensive context, a generic LLM might struggle to generate accurate responses when interacting with customers about specific products. Generic models are optimized for broad usability, which means they may not be tailored for the specialized conversations required in business scenarios. Organizations can overcome these limitations by retraining or fine-tuning an LLM with data related to their products and services. During this process, AI teams can also adjust parameters, such as model weights, to influence the type of output the model generates, making it more relevant to the organization’s needs. Steps to Customize an LLM with Organization-Specific Data To customize an LLM with your organization’s data, follow these steps: By following these steps, organizations can transform a generic LLM into a powerful, customized tool tailored to their unique business needs, enhancing efficiency, customer satisfaction, and overall operational effectiveness. 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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April 29, 2024in Salesforce
Salesforce OmniStudio Summer 24 Release Notes
24Apr

Salesforce OmniStudio Summer 24 Release Notes

In Summer ’24, OmniStudio (when the Managed Package Runtime setting is disabled) supports features from OmniStudio for Vlocity, including filling address fields in omniscripts with Google Map data, using Salesforce private connect for HTTP actions in integration procedures, and choosing whether to merge entries within a list in an integration procedure list action. Also, DataRaptor is now Omnistudio Data Mapper. For Winter ’25 upgrades, disable New Order Save Behavior. To prepare for future releases, remove organization and profile standard objects from data mappers, remove OmniStudio components with unlocked packages, and check the impact of the date change in the ADDDAY function return. Salesforce OmniStudio Summer 24 Release Notes. 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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April 24, 2024in Salesforce, Salesforce Data Cloud, Salesforce Experience Cloud
Paradox of Writing With AI
14Apr

Paradox of Writing With AI

It seems like some people honestly believe they can spot AI-generated content immediately, but that’s not always the case. Well-written content isn’t inherently AI-generated, and if it is AI-generated, that doesn’t necessarily mean it’s well-written. The quality of writing often depends more on the writer’s skill than the tools they use. Paradox of Writing With AI is that it will make a good writer better. And it will make a bad writer worse. The real difference in human versus AI content lies in the accessibility of writing tools and the lack of proper ethical regulation for their use. This ease of access makes it simple for people to feel entitled to judge written content. True, if you publish your writing – online or elsewhere – you open it up for judgement. But imagine if UX design or data applications were graded as indiscriminately—those discussions would likely be confined to experts rather than becoming public debates on social media condemning all well-written content. Good writing requires creativity, flair, and uniqueness, among other skills, to truly impress readers. Good writing is well-organized and flows well with consistent style or voice from beginning to end. Good writing is also free from mistakes and errors in spelling, punctuation and grammar. But that alone doesn’t make it engaging or meaningful. A good writer will brainstorm for great ideas and follow them up with research. A good writer can think of fresh angles to view a topic. A good writer is sure to re-write and self-edit to make a better draft. AI has been integrated into various tools and applications long before ChatGPT was launched. Search engines use it to provide relevant results; social media algorithms keep your favorite content visible; Siri and Alexa rely on natural language processing and speech recognition; Netflix and Spotify use AI recommendation systems to cater to your tastes, and so on. AI enhances human ideas, not just in writing, but across many fields. Writing With AI is Inevitable For instance, Chinese Nobel laureate Mo Yan surprised everyone at the 65th-anniversary celebration of Shouhuo magazine by revealing he uses ChatGPT. During his speech praising fellow author Yu Hua, he mentioned that he struggled to write a commendation and asked a doctoral student to use ChatGPT for help. This revelation caused quite a stir, as it was unexpected for a Nobel Prize winner to use AI for writing. Why shouldn’t he? If AI makes a good writer better, then most of us should be employing it. Mo Yan isn’t alone. Rie Kudan, the 17th winner of Japan’s Akutagawa Prize, admitted to using ChatGPT for her novel, Tokyo-to Dojo-to. She stated that about 5% of the book consists of AI-generated sentences. Kudan, who is introverted, shared that frequent interactions with the AI tool allowed her to express personal thoughts she couldn’t comfortably discuss with others. ChatGPT’s responses often sparked dialogue in her novel, adding a unique dimension to her writing process. Grammarly, another AI tool, is why some people’s writing doesn’t reflect their irritation when discussing AI-generated content online. Grammarly has been widely used for editing and proofreading, ensuring users’ writing maintains a promotional tone and corrects errors without sounding sarcastic or bored. The Problem with Sounding Alike & The Uniqueness of a Writer’s Voice A significant issue with AI-generated content is that many written works sound similar. Writers need to develop unique voices. While Jane Austen, Mary Shelley, and the Brontë sisters are admirable, emulating their ornate language can interfere with communication’s primary purpose. Excessive fanciness can make speech overly flamboyant, akin to Oscar Wilde’s works. However asking AI to work through your content and put it in the voice of a known writer, add humor, or change the tense is time saving. The problem isn’t that AI enables people to produce well-crafted content. Many individuals have exceptional writing skills and huge vocabularies. The real issue is the uniformity in everyone’s writing, a lack of diversity that AI can perpetuate. Yet, you only have to Google any topic and you will find many blog posts and articles that share the same view, and perhaps the same voice. Some discussions about AI resemble early 2000s conspiracy theories about cell phones. While the context has changed, the tone remains similar. The Importance of Creativity in Writing & Our Language Creativity is essential in writing. Even AI relies on human creativity. Without our input, machines would repeatedly generate the same content. Machine learning in AI is about learning from people. Our role is crucial, demonstrating the value of our unique voices. Developing a unique voice takes time and effort, which is why creatives like Kelly McKernan, Nicki Minaj, Elin Hilderbrand, and Jonathan Franzen are suing AI companies for copyright infringement. These unique voices significantly impact language evolution, and it’s vital for us to continue growing creatively. Writers play a crucial role in language evolution by creating new words or phrases that captivate readers. Over time, these innovations can enrich the language. A writer’s distinctive style can set trends, leading to significant changes in language use. This power must be used wisely. Famous writers’ narrative structures and dialogue usage can inspire others. For example, Dr. Seuss coined “nerd,” J.R.R. Tolkien introduced “tween,” Milton created “pandemonium”, novelist William Gibson first used “cyberspace”, Johnathon Swift gave us “yahoo” in Gulliver’s Travels, and Charles Dickens gave us “boredom.” The core of a good piece of writing is a great idea. With a strong core idea, the writer can easily layer the content around it. Content even can build the framework from which comes a whole new word. Content includes interesting examples to which the reader can relate. That content needs to be well-organized and clear in form so that the reader can easily see the message or find the intended meaning. In addition, the writing should have style and the right voice that matches its topic and theme while also reflecting what the author believes.  Writing Through the Centuries Writing has evolved over centuries, influencing language development. During

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April 14, 2024in Salesforce Einstein
Where Will AI Take Us?
26Mar

Where Will AI Take Us?

Author Jeremy Wagstaff wrote a very thought provoking article on the future of AI, and how much of it we could predict based on the past. This insight expands on that article. Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn. These machines can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Many people think of artificial intelligence in the vein of how they personally use it. Some people don’t even realize when they are using it. Artificial intelligence has long been a concept in human mythology and literature. Our imaginations have been grabbed by the thought of sentient machines constructed by humans, from Talos, the enormous bronze automaton (self-operating machine) that safeguarded the island of Crete in Greek mythology, to the spacecraft-controlling HAL in 2001: A Space Odyssey. Artificial Intelligence comes in a variety of flavors, if you will. Artificial intelligence can be categorized in several ways, including by capability and functionality: You likely weren’t even aware of all of the above categorizations of artificial intelligence. Most of us still would sub set into generative ai, a subset of narrow AI, predictive ai, and reactive ai. Reflect on the AI journey through the Three C’s – Computation, Cognition, and Communication – as the guiding pillars for understanding the transformative potential of AI. Gain insights into how these concepts converge to shape the future of technology. Beyond a definition, what really is artificial intelligence, who makes it, who uses it, what does it do and how. Artificial Intelligence Companies – A Sampling AI and Its Challenges Artificial intelligence (AI) presents a novel and significant challenge to the fundamental ideas underpinning the modern state, affecting governance, social and mental health, the balance between capitalism and individual protection, and international cooperation and commerce. Addressing this amorphous technology, which lacks a clear definition yet pervades increasing facets of life, is complex and daunting. It is essential to recognize what should not be done, drawing lessons from past mistakes that may not be reversible this time. In the 1920s, the concept of a street was fluid. People viewed city streets as public spaces open to anyone not endangering or obstructing others. However, conflicts between ‘joy riders’ and ‘jay walkers’ began to emerge, with judges often siding with pedestrians in lawsuits. Motorist associations and the car industry lobbied to prioritize vehicles, leading to the construction of vehicle-only thoroughfares. The dominance of cars prevailed for a century, but recent efforts have sought to reverse this trend with ‘complete streets,’ bicycle and pedestrian infrastructure, and traffic calming measures. Technology, such as electric micro-mobility and improved VR/AR for street design, plays a role in this transformation. The guy digging out a road bed for chariots and Roman armies likely considered none of this. Addressing new technology is not easy to do, and it’s taken changes to our planet’s climate, a pandemic, and the deaths of tens of millions of people in traffic accidents (3.6 million in the U.S. since 1899). If we had better understood the implications of the first automobile technology, perhaps we could have made better decisions. Similarly, society should avoid repeating past mistakes with AI. The market has driven AI’s development, often prioritizing those who stand to profit over consumers. You know, capitalism. The rapid adoption and expansion of AI, driven by commercial and nationalist competition, have created significant distortions. Companies like Nvidia have soared in value due to AI chip sales, and governments are heavily investing in AI technology to gain competitive advantages. Listening to AI experts highlights the enormity of the commitment being made and reveals that these experts, despite their knowledge, may not be the best sources for AI guidance. The size and impact of AI are already redirecting massive resources and creating new challenges. For example, AI’s demand for energy, chips, memory, and talent is immense, and the future of AI-driven applications depends on the availability of computing resources. The rise in demand for AI has already led to significant industry changes. Data centers are transforming into ‘AI data centers,’ and the demand for specialized AI chips and memory is skyrocketing. The U.S. government is investing billions to boost its position in AI, and countries like China are rapidly advancing in AI expertise. China may be behind in physical assets, but it is moving fast on expertise, generating almost half of the world’s top AI researchers (Source: New York Times). The U.S. has just announced it will provide chip maker Intel with $20 billion in grants and loans to boost the country’s position in AI. Nvidia is now the third largest company in the world, entirely because its specialized chips account for more than 70 percent of AI chip sales. Memory-maker Micro has mostly run out of high-bandwidth memory (HBM) stocks because of the chips’ usage in AI—one customer paid $600 million up-front to lock in supply, according to a story by Stack. Back in January, the International Energy Agency forecast that data centers may more than double their electrical consumption by 2026 (Source: Sandra MacGregor, Data Center Knowledge). AI is sucking up all the payroll: Those tech workers who don’t have AI skills are finding fewer roles and lower salaries—or their jobs disappearing entirely to automation and AI (Source: Belle Lin at WSJ). Sam Altman of OpenAI sees a future where demand for AI-driven apps is limited only by the amount of computing available at a price the consumer is willing o pay. “Compute is going to be the currency of the future. I think it will be maybe the most precious commodity in the world, and I think we should be investing heavily to make a lot more compute.” Sam Altman, OpenAI CEO This AI buildup is reminiscent of past technological transformations, where powerful interests shaped outcomes, often at the expense of broader societal considerations. Consider early car manufacturers. They focused on a need for factories, components, and roads.

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March 26, 2024in Generative AI
Communications Cloud Summer 24
24Mar

Communications Cloud Summer 24

Salesforce Communications Cloud Summer ’24 Release: Elevating Business Performance and Workflow Efficiency With its Summer ’24 release, Salesforce Communications Cloud unveils an array of powerful new capabilities designed to elevate business performance and optimize workflow efficiency. In this blog, we’ll explore some of our favorite new features, including Field Service improvements that provide technicians with better insights and user experiences, new TM Forum API integrations, and Enterprise Sales Management (ESM) enhancements. Field Service Field Service for Industries optimizes field operations by equipping service teams with advanced tools, enabling companies to maximize asset lifetime value and enhance customer satisfaction. This release includes unique capabilities tailored for field technicians to help with work order execution and asset management. TM Forum In the latest Summer ’24 release, Salesforce has delivered two additional TM Forum APIs, enabling seamless integration of Communications Cloud instances with external systems. These include the TMF620 outbound Product Catalog Management and TMF651 inbound Agreement Management APIs. Enterprise Sales Management Conclusion The main features in the Summer ’24 release allow businesses to operate more efficiently, enhance user experience, and create an open and flexible platform with TM Forum APIs. There are also many other exciting enhancements such as CPQ API improvements, built-in diagnostic tools for EPC configuration, and more. 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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March 24, 2024in Salesforce Communications Cloud

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