Alden Do Rosario’s Post

ML-powered SaaS applications are powered by machine learning algorithms that can learn from data and identify patterns. Once the algorithms have identified patterns, they can be used to automate tasks, provide personalized recommendations, and make better decisions. https://lnkd.in/e6XMaFzU #predictiveanalytics #data #help #AI #machinelearning #machinelearningengineer #machinelearningalgorithms #microsoft #aws #google #productivity #gpt #power #automation #analytics #enterprise #nvidia #google #software #saas #industry #ml #security #business #technology #artificialintelligence #development #algorithms 

Machine learning (ML)-powered SaaS applications are revolutionizing industries across the board. By automating tasks, providing personalized recommendations, and making better decisions, ML-powered SaaS applications are helping businesses improve their efficiency, customer experience, and profitability. #generativeai #enterprisesoftware #enterpriseai #ai #machinelearning #saas #efficiency #personalisation #riskmanagement #ml #success #growth #creativeai

Tray Universal Automation Cloud™ gives you three options for the way you work, whether you're a builder, coder, or simply seeking answers that move at the speed you do. Learn about its elements: ✴️ Build ✴️ Code ✴️ Chat Just visit our site. tray.io #LowCode #automation

👷 Whether building in-house solutions or commercial SaaS apps, you can use Tray Code��with programmatic access to the Universal Automation Cloud—to move faster. It provides a single, flexible JSON schema and a standard REST interface, which unlocks a gateway to our library of more than six hundred applications, databases, and services, all with just three API calls. Learn more today. Tray.io #DevOps #SaaS #B2B

Re:Invent's AWS has showcased AppFabric's new potential, leveraging generative AI to boost productivity in a significant way. This could change how we interact with our day-to-day applications. Here's the scoop: → Simplifying Integration: AppFabric aims to be the connective tissue between your staple apps like Salesforce, Slack, and Microsoft 365, by normalizing disparate data and streamlining operations. → Breaking Down Silos: It converts unique log formats to a common schema, enhancing security incident detection. No need to juggle formats; AppFabric has you covered. → Beyond Security: AppFabric isn’t just for security. It now provides APIs to mesh tasks and calendars across platforms. Picture seamlessly crafting emails or tasks without jumping from app to app. → Developer-Focused: The APIs are a golden ticket for SaaS developers, allowing applications to interoperate smoothly, which spells efficiency and an integrated user experience. → The Challenge Remains: Skepticism bubbles up around the efficacy and value addition. There are concerns about the service depth and the ever-present switch between apps for full features. → Aiming for Efficiency: AWS insists AppFabric can cut through the complexity and offers a unified platform, easing the many-to-many integration headache plaguing developers. #aws #generativeai #ai

An artificial intelligence platform that promises safe application building, a conversational, out-of-the-box AI assistant and deeper integrations with Google and Amazon Web Services (AWS) are among the eight biggest announcements from Salesforce’s annual Dreamforce event this week. Learn about them all here: #DF23 #generativeAI #GenAI

We invite you to read this interesting article on how to boost innovation in the age of AI with ISV Success... #TheATeam #business #work #itrecruitment #itconsultingservices #itprojectmanagement #success #development #quality #microsoft

Machine learning (ML) is rapidly transforming the enterprise software market. ML-powered applications are becoming increasingly sophisticated and capable of automating tasks, providing personalized recommendations, and making better decisions than ever before. https://lnkd.in/eKkZkUBx #predictiveanalytics #data #help #AI #machinelearning #machinelearningengineer #machinelearningalgorithms #microsoft #aws #google #productivity #gpt #power #automation #analytics #enterprise #nvidia #google #software #saas #industry #ml #security #business #technology #artificialintelligence #development #algorithms 

Microsoft Co-pilot has become the Kleenex for RAG. In all of our customer conversations, we always discuss Copilot and how a company should think about it vs. using another GenAI application like Nesh. Here's what I tell them: All RAG systems are architected differently for the use cases they serve. Consider the use-case and choose accordingly. If it's for the legal team, there is Harvey. If it's for R&D, there is Causaly. If it's a general-purpose search, there's Glean and Perplexity. If it is technical sales and knowledge management, there's Nesh. Copilot is an excellent productivity tool and supports many use cases (writing emails, summarizing meetings, creating designs). Consider how to measure the value of a software investment when everyone in the company uses it differently. Copilot is designed for everyone, everywhere. Consumers, small businesses, medium-sized businesses, and large enterprises, everyone can use it. Consider the unique value it provides to your team. Consider if it knows anything about your industry, your function and your workflows. Think of a parallel scenario of when you'd want to use a specific financial accounting software vs. Excel. Copilot follows the M365 security architecture so if you are using a multi-tenant environment, Copilot is also using the same pattern. Consider the risks of putting your private and sensitive data on a multi-tenant RAG architecture. Copilot is a Microsoft tool and it plays well with all things Microsoft. Consider the implication of using it if your tech stack includes data sources and software from Salesforce, AWS, Google, and other vendors. Microsoft has a $3T market cap and your team's success isn't aligned with their success. Consider the service quality, support, turn-around time, and white-glove treatment that you'll receive from them. This is not about throwing shade; it's about finding your perfect fit and offering a framework to tailor your tech stack to your needs, even if that means mixing and matching multiple systems.

ML can help businesses to innovate by providing them with new insights into their data and operations. This can help businesses to develop new products and services, improve their existing products and services, and enter new markets. #generativeai #enterprisesoftware #enterpriseai #ai #machinelearning #saas #efficiency #personalisation #riskmanagement #ml