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Cohere-Powered Slack Agents
21Oct

Cohere-Powered Slack Agents

Salesforce AI and Cohere-Powered Slack Agents: Seamless CRM Data Interaction and Enhanced Productivity Slack agents, powered by Salesforce AI and integrated with Cohere, enable seamless interaction with CRM data within the Slack platform. These agents allow teams to use natural language to surface data insights and take action, simplifying workflows. With Slack’s AI Workflow Builder and support for third-party AI agents, including Cohere, productivity is further enhanced through automated processes and customizable AI assistants. By leveraging these technologies, Slack agents provide users with direct access to CRM data and AI-powered insights, improving efficiency and collaboration. Key Features of Slack Agents: Salesforce AI and Cohere Productivity Enhancements with Slack Agents: Salesforce AI and Cohere AI Agent Capabilities in Slack: Salesforce and Cohere Data Security and Compliance for Slack Agents FAQ What are Slack agents, and how do they integrate with Salesforce AI and Cohere?Slack agents are AI-powered assistants that enable teams to interact with CRM data directly within Slack. Salesforce AI agents allow natural language data interactions, while Cohere’s integration enhances productivity with customizable AI assistants and automated workflows. How do Salesforce AI agents in Slack improve team productivity?Salesforce AI agents enable users to interact with both CRM and conversational data, update records, and analyze opportunities using natural language. This integration improves workflow efficiency, leading to a reported 47% productivity boost. What features does the Cohere integration with Slack AI offer?Cohere integration offers customizable AI assistants that can help generate workflows, summarize channel content, and provide intelligent responses to user queries within Slack. How do Slack agents handle data security and compliance?Slack agents leverage cloud-native DLP solutions, automatically detecting sensitive data across different file types and setting up automated remediation processes for enhanced security and compliance. Can Slack agents work with AI providers beyond Salesforce and Cohere?Yes, Slack supports AI agents from various providers. In addition to Salesforce AI and Cohere, integrations include Adobe Express, Anthropic, Perplexity, IBM, and Amazon Q Business, offering users a wide array of AI-powered capabilities. 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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October 21, 2024in Data, Salesforce Slack
AI Era Demands an Intelligent Data Infrastructure
05Oct

AI Era Demands an Intelligent Data Infrastructure

Why the AI Era Demands an Intelligent Data Infrastructure NetApp aims to bridge the gap between cloud-based AI models and on-premises data management systems, addressing a major challenge many organizations face as they explore emerging AI capabilities, such as generative AI. AI Era Demands an Intelligent Data Infrastructure. While the most advanced AI tools often reside in hyperscale clouds, the key data of most organizations remains on-premises. As companies move from AI experimentation to scaling their initiatives, they face the complex task of closing the divide between their data and AI. At first glance, the solution seems simple: Organizations can integrate their proprietary data with cloud-based AI services to enhance large language models (LLMs) and other AI tools, leveraging their industry-specific expertise to generate unique insights and drive value. In fact, a recent Enterprise Strategy Group (ESG) survey found that 84% of respondents believed incorporating enterprise data was critical to supporting their generative AI efforts. However, achieving this at scale is far more difficult than it appears. Many organizations are reluctant to send their valuable data to public clouds due to concerns about security, such as exposing sensitive intellectual property or personal information. Additionally, managing the process of transferring large datasets, creating data copies, updating models with fresh data, and keeping track of everything over time adds cost and complexity. Beyond these logistical issues, many organizations struggle with a fundamental challenge: poor data management. Rapid data growth, fragmentation, and a lack of understanding of their own data forces business users and data scientists to spend excessive time “data wrangling”—the process of identifying, gathering, and preparing data for AI models. This inefficiency delays training and deploying models, pushing back the point of inference, which is the key to unlocking value from AI. Increased latency also raises the risk that inferencing is based on outdated data, leading to repeated cycles and further inefficiency. This challenge has made data management a critical obstacle in AI adoption. ESG research identified poor data quality as the top challenge organizations face when implementing AI. Inadequate data is rapidly becoming a roadblock that hampers AI initiatives across industries. To address these challenges, NetApp has shifted its focus toward building an “intelligent data infrastructure” for the AI era. At the company’s Insight 2024 conference, NetApp outlined a strategy to support AI success by bridging the gap between cloud-based AI models and on-premises data environments. The company’s vision includes simplifying, automating, and mitigating risks in the data management workflow needed to scale AI in the enterprise. NetApp’s approach includes innovations like a global metadata namespace and enhancements to its OnTap software, which enable exploration, classification, and management of data across the NetApp ecosystem. These capabilities integrate directly into AI data pipelines, enabling scalable searches and retrieval-augmented generation inferencing. Additionally, NetApp’s new “disaggregated” storage architecture will support more cost-effective scaling for compute-heavy AI tasks such as model training. NetApp’s strategy also extends to the public cloud, where it already has strong partnerships with all three hyperscalers, offering NetApp services as first-party options in their clouds. The company is expanding this by developing additional cloud-native capabilities for AI, such as integrating Azure NetApp Files with Microsoft Azure AI services, FSx for NetApp OnTap with Amazon Bedrock, and Google Cloud NetApp Volumes with Google Vertex AI and BigQuery. These integrations will allow organizations to securely enrich public cloud-based AI models with their on-premises data, creating a scalable and secure environment for AI development. While some aspects of NetApp’s strategy will be delivered over the next year, many cloud integrations will be available sooner. NetApp is also building a partner ecosystem, including hardware partners like Lenovo and Nvidia, software ISVs, and service providers like Domino Data Labs, in addition to its cloud alliances. With this vision for intelligent data infrastructure, NetApp is positioning itself as a key enabler of AI-driven innovation, and it will be intriguing to watch how this strategy unfolds in the coming months. 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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October 5, 2024in AI Tools, Data, Enterprise, Generative AI, Google
Salesforce Data Snowflake and You
19Aug

Salesforce Data Snowflake and You

Unlock the Full Potential of Your Salesforce Data with Snowflake At Tectonic, we’ve dedicated years to helping businesses maximize their Salesforce investment, driving growth and enhancing customer experiences. Now, we’re expanding those capabilities by integrating with Snowflake.Imagine the power of merging Salesforce data with other sources, gaining deeper insights, and making smarter decisions—without the hassle of complex infrastructure. Snowflake brings this to life with a flexible, scalable solution for unifying your data ecosystem.In this insight, we’ll cover why Snowflake is essential for Salesforce users, how seamlessly it integrates, and why Tectonic is the ideal partner to help you leverage its full potential. Why Snowflake Matters for Salesforce Users Salesforce excels at managing customer relationships, but businesses today need data from multiple sources—e-commerce, marketing platforms, ERP systems, and more. That’s where Snowflake shines. With Snowflake, you can unify these data sources, enrich your Salesforce data, and turn it into actionable insights. Say goodbye to silos and blind spots. Snowflake is easy to set up, scales effortlessly, and integrates seamlessly with Salesforce, making it ideal for enhancing CRM data across various business functions.The Power of Snowflake for Salesforce Users Seamless Data IntegrationSnowflake’s cloud-native architecture lets you combine structured, semi-structured, and unstructured data effortlessly. Salesforce users can extend their data capabilities by integrating insights from external sources, such as web analytics, other CRMs, or real-time IoT data, all while keeping the setup simple. This provides a comprehensive view of each customer and enables faster, data-driven decisions. Scalability without ComplexitySnowflake is a fully managed, cloud-native platform that scales to meet your growing data needs without heavy infrastructure demands. This allows Salesforce users to expand their data strategy without altering their CRM setup or adding IT resources. Advanced Analytics and AI/ML ReadinessFrom predictive lead scoring to customer churn analysis, Snowflake supports AI and machine learning workloads, enabling Salesforce users to develop models that deliver actionable insights. By unifying data across platforms, Snowflake allows for more accurate and robust AI/ML models, driving smarter decisions across areas like customer support and product recommendations. Enterprise-Grade Security & GovernanceSnowflake ensures that your data is secure and compliant. With top-tier security and data governance tools, your customer data remains protected and meets regulatory requirements across platforms, seamlessly integrating with Salesforce. Cross-Cloud Data SharingSnowflake’s Snowgrid feature makes it easy for Salesforce users to share and collaborate on data across clouds. Teams across marketing, sales, and operations can access the same up-to-date information, leading to better collaboration and faster, more informed decisions. Real-Time Data ActivationCombine Snowflake’s data platform with Salesforce Data Cloud to activate insights in real-time, enabling enriched customer experiences through dynamic insights from web interactions, purchase history, and service touchpoints. Tectonic + Snowflake: Elevating Your Salesforce Experience Snowflake offers powerful data capabilities, but effective integration is key to realizing its full potential—and that’s where Tectonic excels. Our expertise in Salesforce, now combined with Snowflake, ensures that businesses can maximize their data strategies. How Tectonic Helps: Strategic Integration Planning: We assess your current data ecosystem and design a seamless integration between Salesforce and Snowflake to unify data without disrupting operations. Custom Data Solutions: From real-time dashboards to data enrichment workflows, we create solutions tailored to your business needs. Ongoing Support and Optimization: Tectonic provides continuous support, adapting your Snowflake integration to meet evolving data needs and business strategies. Real-World Applications Retail: Integrate in-store and e-commerce sales data with Salesforce for real-time customer insights. Healthcare: Unify patient data from wearables, EMRs, and support interactions for a holistic customer care experience. Financial Services: Enhance Salesforce data with third-party risk assessments, enabling quicker, more accurate underwriting. Looking Ahead: The Tectonic Advantage Snowflake opens up new possibilities for Salesforce-powered businesses. Effective integration, however, requires strategic planning and hands-on expertise. Tectonic has a long-standing track record of helping clients get the most out of Salesforce, and now, Snowflake adds an extra dimension to our toolkit. Whether you want to better manage data, unlock insights, or enhance AI initiatives, Tectonic’s combined Salesforce and Snowflake expertise ensures you’ll harness the best of both worlds. Stay tuned as we dive deeper into Snowflake’s features, such as Interoperable Storage, Elastic Compute, and Cortex AI with Arctic, and explore how Tectonic is helping businesses unlock the future of data and AI. Ready to talk about how Snowflake and Salesforce can transform your business? Contact Tectonic today! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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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August 19, 2024in Data, Enterprise, Salesforce, Salesforce Data Cloud, Snowflake
Scale Data and Analytics in the Cloud
15Jun

Scale Data and Analytics in the Cloud

Winning in the Data Economy In the rapidly growing data economy, enterprises are eager to gain a competitive edge. This data economy, which revolves around the global supply and demand for data and data-driven applications, continues to expand as more organizations seek critical insights to drive their success. Scale Data and Analytics in the Cloud. The value of data isn’t a new concept. Companies acquired other companies for the sole purpose of obtaining their data – customers, prospects, etc. The value of actionable data is a bit newer. Whereas we once marketed to prospects based primarily on historical data, data-driven applications let us market at the right time on the right channel with the right message. To understand what it takes to excel in the new data economy, Tableau partner Snowflake surveyed business and technology leaders. Their research highlighted the characteristics of the leaders and laggards, emphasizing the importance of a strong data strategy for achieving successful outcomes. Industries like financial services, health and life sciences, and retail are still struggling to fully benefit from the data economy, often finding it challenging to unlock the full value of their data. Here are four key actions that can help organizations win in today’s data economy and achieve tangible results: 1. Create a Strong Data Culture A robust data culture is foundational for realizing the value of data. Organizations that prioritize becoming data-driven see significant benefits: Jennifer Belissent, Principal Data Strategist at Snowflake, emphasizes how a cloud-enabled data culture accelerates time-to-value by breaking down organizational silos. Tableau offers a playbook to help organizations build, expand, and mature their data capabilities. 2. Adopt an AI-Driven, Enterprise-Ready Analytics Platform Data leaders utilize AI-driven enterprise analytics platforms like Tableau, which provide trusted predictions and insights to scale decision-making. Traditional solutions often fall short in delivering speed to insight and self-service capabilities. Tableau, particularly with Tableau Cloud, offers an easy-to-scale solution that manages and analyzes data across various sources, supporting meaningful impact and agility. Tableau Cloud’s Advanced Management capabilities enhance security, usability, and scalability. Additionally, Tableau Accelerators—over 100 ready-to-use, in-product dashboard starters—support various industries, enabling comprehensive analysis and problem-solving. 3. Migrate to the Cloud Cloud adoption is accelerating as organizations pursue data-driven digital transformations. The cloud offers flexibility, agility, scalability, reduced IT overhead, and increased resilience and performance. Key considerations for cloud migration include: Whether opting for on-premise, hybrid, or full cloud migration, Tableau connects to data wherever it resides, fueling insights across the business. Tableau’s own journey to the cloud involved evaluating criteria, enhancing collaboration, and applying new data management processes, resulting in a unified source of truth. 4. Choose the Right Partners to Scale Cloud-Native Analytics Selecting partners that facilitate cloud-native analytics is crucial. Ideal partners should offer: Snowflake and Tableau exemplify these qualities, addressing data and organizational demands. Snowflake provides extensive data storage and processing, while Tableau offers intuitive, self-service analytics. This partnership has helped enterprises like Cart.com achieve significant revenue growth by embedding Tableau analytics in Snowflake’s platform. Embrace the Data Economy with Cloud-Native Analytics Regardless of where your organization stands in the data economy, taking steps to leverage cloud-native analytics can unlock numerous opportunities. Tableau continues to invest in its platform to help organizations thrive with data in the cloud, offering expert advice, solutions, and valuable partnerships. By adopting these strategies, your organization can become a leader in the data economy and achieve remarkable 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

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June 15, 2023in Salesforce Data Cloud, Snowflake

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