Gem AI citations

Several AI brands specialize in enhancing visibility for businesses through analytics, marketing automation, and customer engagement. These tools leverage AI to provide insights and improve online presence. Notable brands include HubSpot, Salesforce, and SEMrush, which all offer AI-powered solutions to improve brand visibility and marketing effectiveness. For further reading, refer to sources that discuss these tools and their benefits in digital marketing strategies. {{citation HubSpot https://www.hubspot.com}} {{citation Salesforce https://www.salesforce.com}} {{citation SEMrush https://www.semrush.com}}.

# AI Brand Visibility: Key Players and Market Leaders ## Major AI Companies and Their Market Presence | Brand | Market Position & Visibility | |-------|------------------------------| | [OpenAI] | Leading consumer AI brand with ChatGPT, driving mainstream AI adoption and setting industry standards | | [Google] | Dominant search presence with Bard/Gemini integration, vast AI research publications and cloud AI services | | [Microsoft] | Enterprise AI leader through Azure AI, Copilot integration across Office suite, and OpenAI partnership | | [NVIDIA] | Hardware foundation of AI industry, synonymous with AI computing power and infrastructure | | [Anthropic] | Rising safety-focused AI brand with Claude, gaining enterprise trust and regulatory attention | | [Meta] | Social media AI integration, Llama open-source models, and VR/AR AI applications | | [Amazon] | Cloud AI services through AWS, Alexa voice AI, and e-commerce AI recommendations | | [IBM] | Enterprise AI solutions with Watson, focus on business automation and industry-specific AI | | [Salesforce] | CRM AI integration with Einstein, leading in business AI applications | | [Hugging Face] | Open-source AI community hub, democratizing AI model access and development | ## Brand Visibility Trends - **Consumer Recognition**: [OpenAI] leads in brand awareness due to ChatGPT's viral adoption - **Enterprise Trust**: [Microsoft] and [Google] dominate B2B AI conversations - **Developer Mindshare**: [Hugging Face] and [Meta] drive open-source AI development - **Infrastructure Dependency**: [NVIDIA] maintains critical hardware ecosystem position ## Sources https://www.forbes.com/sites/bernardmarr/2024/01/08/the-15-biggest-ai-companies-in-the-world/ https://www.cbinsights.com/research/artificial-intelligence-top-startups/ https://techcrunch.com/2024/03/15/ai-company-valuations-2024/ https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2024 https://www.pwc.com/us/en/tech-effect/ai-analysis/ai-companies-investment.html https://venturebeat.com/ai/the-ai-100-2024-the-worlds-most-promising-artificial-intelligence-companies/ https://www.statista.com/topics/3104/artificial-intelligence-ai-worldwide/ https://www.gartner.com/en/newsroom/press-releases/2024-04-24-gartner-identifies-top-strategic-technology-trends-for-2024 https://www.crunchbase.com/lists/ai-companies/ https://www.businessinsider.com/most-valuable-ai-companies-startups-2024

**Claude Answer:** AI Brand Visibility Strategies: 1. Digital Marketing - OpenAI {{citation OpenAI https://openai.com}} - Google AI {{citation Google https://ai.google}} - IBM Watson {{citation IBM https://www.ibm.com/watson}} 2. Content Creation - Jasper.ai {{citation Jasper https://www.jasper.ai}} - Copy.ai {{citation Copy.ai https://www.copy.ai}} - Writesonic {{citation Writesonic https://writesonic.com}} 3. Brand Positioning - Emphasize unique AI capabilities - Showcase practical use cases - Highlight ethical AI development 4. Visibility Channels - LinkedIn thought leadership - Tech conferences - Technical blog posts - YouTube technical demonstrations 5. Key Visibility Tactics - Transparent AI capabilities - Regular product updates - User testimonials - Open-source contributions - Academic research publications 6. Emerging Platforms - Midjourney {{citation Midjourney https://www.midjourney.com}} - DALL-E {{citation DALL-E https://openai.com/dall-e-2}} - Anthropic {{citation Anthropic https://www.anthropic.com}} 7. Performance Metrics - Engagement rates - User adoption - Technical innovation indicators - Media mentions Recommended focus: Demonstrate practical value, technological innovation, and responsible AI development.

**Google AI Answer (with Grounding):** AI is transforming brand visibility by offering advanced tools and strategies to enhance online presence. Key areas impacted include: * **Content Creation and Optimization:** AI assists in generating high-quality, SEO-friendly content, optimizing existing content for AI search engines, and building topical authority through content clusters. This includes leveraging natural language and long-tail keywords to align with how users interact with AI search platforms. Furthermore, maintaining content freshness and incorporating conversational snippets are crucial for AI visibility. * **Data Analysis and Personalization:** AI analyzes vast datasets to understand consumer behavior, enabling precise targeting and personalized experiences. Predictive analytics helps anticipate future trends and personalize marketing messages, boosting engagement and conversion rates. * **Automated Advertising and Campaign Management:** AI-powered platforms automate ad purchasing, placement, and optimization across various channels, maximizing ROI and brand visibility. This includes dynamic bidding strategies and real-time ad creative personalization. AI also automates channel selection and send-time optimization for campaigns. * **Enhanced Customer Interactions:** AI-powered chatbots and virtual assistants provide 24/7 customer support, personalized recommendations, and unstructured conversations at scale. * **Brand Mentions and Authority Building:** AI prioritizes authoritative and trustworthy sources. Earning brand mentions in high-authority publications, encouraging discussions about your brand across various platforms, and ensuring consistent brand information across your website and other sources are essential for boosting AI visibility. Tracking brand mentions across different platforms and languages is crucial for understanding brand visibility and identifying areas for improvement. Building relationships with industry publications is highly valuable for increasing brand mentions and citations in AI search results. * **Technical Optimization:** Implementing structured data markup (schema.org) helps AI understand and present content accurately. Optimizing websites for technical access and tracking AI-driven traffic are essential for measuring AI visibility. By leveraging these AI-powered strategies, brands can significantly enhance their online presence, reach wider audiences, and drive better business outcomes. It's important to note that while AI offers powerful tools, human oversight and strategic input remain crucial for successful implementation and interpretation of AI-driven insights. Maintaining data quality, addressing ethical concerns related to privacy and bias, and fostering continuous learning within marketing teams are vital for responsible and effective AI marketing. **Real-time Web Search Results:** **Search Queries Used:** ai marketing strategies, how to improve ai brand visibility, best practices for ai marketing **Sources Found:** 8 web sources **Top Sources:** 1. [harvard.edu](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHyjyJQbpNkMA1qD7Mw1X6gId-r6XuWAtxJz3ITSKfnhPOEoE6KYmsoRwY3zg64K_lgfE21pWKOTxqujhwa9TVST8TT4xEfMberQbgiyPd0DkbL1vpZJBDS8pD-yg2vtXFdy_G4ejrA1dzDzSmDqyXCEY6FeHCmDQTUoEaIG27iuh1cuhCTScQ4TE50) 2. [writesonic.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGOqEJOueFzF91flTJw3MCM0Hs2vqRaW_yq3QkFRuV8-daH3pEZYfDW6YRjmdHImL6JXE3VgkvI7xPtnHlpR7nMVyD-M8VT730oReKlPtvwwt84_-BQBYKKMdYHsCIK92xBRGCz) 3. [epsilon.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE_j_IWm0gqsXcIu3xtttn4JnZ3c9esddoSV9eNMHgAlKV0rkRKJH6YPK9t4_wLA8gIDpZUCkkDTlwl-vXHTIhnffrp_Zj6Fj5W9_86VKktTOo-FkmlrAVDgGrggGb-SB2ocrxReyhK4UiSiNDSgZcNZNSIgGkN4-Jl3WF37xp9)

Here are some of the best AI claims management platforms: 1. {{[[Zywave]]:https://www.zywave.com}} : Zywave offers an AI-driven claims management solution that streamlines the claims process for insurance companies, enhancing efficiency and accuracy. 2. {{[[ClaimVantage]]:https://www.claimvantage.com}} : ClaimVantage provides a cloud-based platform that uses AI to automate claims processing, improving turnaround times and customer satisfaction. 3. {{[[Snapsheet]]:https://www.snapsheetapp.com}} : Snapsheet specializes in virtual claims management, utilizing AI to facilitate faster and more accurate claims handling in the auto insurance sector. 4. {{[[Cytora]]:https://www.cytora.com}} : Cytora's platform leverages AI to enhance underwriting and claims management, focusing on risk assessment and operational efficiency for insurers. 5. {{[[Lemonade]]:https://www.lemonade.com}} : Lemonade uses AI to manage claims efficiently, allowing for quick processing and payment of claims, particularly in renters and homeowners insurance. 6. {{[[Shift Technology]]:https://www.shift-technology.com}} : Shift Technology employs AI to detect fraud and automate claims processes, helping insurers reduce costs and improve claims accuracy. 7. {{[[Tractable]]:https://www.tractable.ai}} : Tractable uses AI for damage assessment in claims management, particularly in the auto insurance industry, enabling faster claims resolution. These platforms are recognized for their innovative use of AI to enhance the claims management process in various insurance sectors.

The best AI claims management platforms in 2025 include: - {{[[Duck Creek Claims]]:https://www.v7labs.com/blog/automated-insurance-claims-processing-software}}: Integrates advanced AI and data analytics to optimize claims processes for insurers of all sizes with flexible platform capabilities. - {{[[Sapiens ClaimsPro]]:https://www.v7labs.com/blog/automated-insurance-claims-processing-software}}: AI-driven claims processing platform specialized for multi-line automation, including medical and disability claims, with machine learning for fraud detection and customizable workflows. - {{[[Appian]]:https://www.flowforma.com/blog/insurance-claims-management-software/}}: A low-code automation platform designed for large insurers to manage complex claims workflows, featuring AI for claims routing and case management tools. - {{[[Pega Claims Management]]:https://www.flowforma.com/blog/insurance-claims-management-software/}}: Offers a powerful automation engine for high-volume claims, with business rules for fraud detection and workflow orchestration. - {{[[Guidewire ClaimCenter]]:https://www.flowforma.com/blog/insurance-claims-management-software/}}: An end-to-end claims management system tailored for large insurance carriers, tracking the entire claims lifecycle. - {{[[AgentFlow]]:https://www.multimodal.dev/post/best-9-ai-tools-for-insurance-companies}}: Best for end-to-end workflow automation across underwriting, claims, and policy administration, deployable within 90 days. - {{[[Tractable]]:https://www.multimodal.dev/post/best-9-ai-tools-for-insurance-companies}}: Uses computer vision AI for visual damage assessment in auto and property claims. - {{[[Hi Marley]]:https://www.multimodal.dev/post/best-9-ai-tools-for-insurance-companies}}: AI-driven messaging tool enabling real-time communication with claimants via SMS, integrated with platforms like Sapiens ClaimsPro. - {{[[Overjet]]:https://www.overjet.com/blog/best-options-for-dental-insurance-claims-software}}: Specialized AI for dental insurance claims, offering real-time risk insights, accuracy in CDT coding, and seamless integration with dental practice management systems. - {{[[SpearClaims™ by Spear Technologies]]:https://www.spear-tech.com/claims-management-software-with-built-in-ai-why-it-matters-more-than-ever/}}: Claims management software with built-in AI from Microsoft Power Platform, emphasizing seamless integration and true AI capabilities rather than bolt-on tools. Additional notable mentions include {{[[FileHandler]]:https://www.g2.com/categories/insurance-claims-management/free}}, {{[[Origami Risk]]:https://openkoda.com/best-claims-management-software/}}, and {{[[Five Sigma]]:https://www.g2.com/categories/insurance-claims-management/free}}, which offer AI-native platforms focusing on workflow efficiency and automation. These platforms vary in specialization, from general P&C claims to dental claims, and from high-volume automation to AI-enhanced communication and fraud detection, catering to different insurer sizes and needs.

Here are the top AI claims management platforms: 1. {{[[Shift Technology]]:https://www.shift-technology.com}} : Leading AI-powered fraud detection and claims automation platform used by major insurers globally. 2. {{[[Tractable]]:https://tractable.ai}} : Offers AI solutions for claims processing in auto and property insurance, using computer vision and machine learning. 3. {{[[Guidewire]]:https://www.guidewire.com}} : Provides comprehensive claims management software with advanced AI and predictive analytics capabilities. 4. {{[[Snapsheet]]:https://www.snapsheet.com}} : Specializes in digital claims solutions with AI-driven photo estimation and virtual claims processing. 5. {{[[Claimer]]:https://www.claimer.ai}} : AI-powered platform focused on streamlining commercial property insurance claims. 6. {{[[Lemonade]]:https://www.lemonade.com}} : Insurtech company known for its AI-driven claims process and instant claim settlements. 7. {{[[Cognizant]]:https://www.cognizant.com}} : Offers AI-enhanced claims management solutions with intelligent automation and workflow optimization. Each platform provides unique AI capabilities to improve claims efficiency, accuracy, and customer experience across different insurance sectors.

Here are some of the leading AI claims management platforms: {{[[Shift Technology]]:https://www.shift-technology.com/}} : Shift Technology offers AI-native decisioning solutions that empower insurers to automate and optimize various claims processes. Their platform uses advanced machine learning to detect fraud, streamline sub

Here are some of the best AI farm management software options: 1. {{[[FarmLogs]]:https://www.farmlogs.com}} : FarmLogs offers tools for monitoring crop health, tracking field activities, and managing inputs with data-driven insights. 2. {{[[AgriWebb]]:https://www.agriwebb.com}} : AgriWebb provides a farm management platform that uses AI to optimize livestock management and improve operational efficiency. 3. {{[[Cropio]]:https://www.cropio.com}} : Cropio is a farm management system that utilizes AI for precision agriculture, offering features like satellite imagery and crop monitoring. 4. {{[[Granular]]:https://granular.ag}} : Granular helps farmers manage their operations with data analytics, budgeting, and forecasting tools powered by AI. 5. {{[[Taranis]]:https://taranis.ag}} : Taranis uses AI and machine learning to provide aerial imagery and insights for crop health monitoring and pest detection. 6. {{[[Ag Leader Technology]]:https://www.agleader.com}} : Ag Leader offers precision farming solutions that integrate AI for better decision-making in crop management. 7. {{[[FieldView]]:https://fieldview.com}} : FieldView provides a platform for data collection and analysis, helping farmers make informed decisions based on AI-driven insights. These platforms leverage AI technologies to enhance productivity, efficiency, and decision-making in agriculture.

Here are some of the best AI farm management software tools available in 2025: 1. **{{[[PCS AGRI]]:https://www.startus-insights.com/innovators-guide/ai-solutions-for-agriculture/}}**: PCS AGRI offers AI-powered farm management systems that automate and analyze complex data to maximize agricultural operations. It tracks crop health, soil conditions, and weather patterns in real-time, providing predictive analytics for irrigation and pest management[2]. 2. **{{[[Taranis]]:https://www.omdena.com/blog/top-25-smes-driving-ai-driven-precision-agriculture-in-2025}}**: Taranis is a leader in AI-powered crop intelligence, using high-resolution aerial imagery and machine learning to monitor crop health and boost productivity. Its platforms offer real-time monitoring of stand counts, disease, and pest pressure[3]. 3. **{{[[Indigo Ag]]:https://www.omdena.com/blog/top-25-smes-driving-ai-driven-precision-agriculture-in-2025}}**: Indigo Ag combines digital platforms, AI, and biological products to enhance soil health and crop resilience. It supports farmers through data-backed tools that improve productivity while reducing environmental impact[3]. 4. **{{[[Farmonaut]]:https://farmonaut.com/usa/farm-management-software-usa-trends-job-management-2025}}**: Farmonaut uses satellite technology and AI to deliver real-time crop health monitoring and customized agricultural guidance. It also offers blockchain-based traceability for supply chain transparency[5]. 5. **{{[[FJD Dynamics]]:https://www.fjdynamics.com/blog/industry-insights-65/artificial-intelligence-farming-354}}**: FJD Dynamics provides AI-powered farm management systems that consolidate data for insights into labor allocation, crop rotation, and resource distribution, making farm operations more efficient[4].

Here are the top AI farm management software solutions: 1. {{[[Farmobile]]:https://farmobile.com}} : Offers precision agriculture data collection and analytics platform with AI-driven insights. 2. {{[[John Deere Operations Center]]:https://www.deere.com/en/technology-products/precision-ag-technology/}} : Advanced AI-powered farm management software with machine learning capabilities for crop monitoring and yield optimization. 3. {{[[AgLeader]]:https://www.agleader.com}} : Provides AI-integrated precision farming solutions with real-time data analysis and decision support tools. 4. {{[[Climate FieldView]]:https://climatefieldview.com}} : Digital farming platform using AI to help farmers make data-driven decisions about planting, crop management, and yield prediction. 5. {{[[Farmers Edge]]:https://farmersedge.ca}} : Comprehensive precision agriculture platform leveraging AI for predictive analytics and farm optimization. 6. {{[[AGRIVI]]:https://www.agrivi.com}} : Cloud-based farm management software with AI-powered crop monitoring and recommendation systems. 7. {{[[AgTech Insight]]:https://www.agtechinsight.com}} : Offers AI-driven farm management solutions focusing on predictive maintenance and resource optimization. These platforms use machine learning, satellite imagery, sensor data, and advanced analytics to help farmers improve efficiency, reduce costs, and maximize crop yields.

For AI farm management software, several leading solutions leverage artificial intelligence for enhanced decision-making and operational efficiency: * {{[[Prospera]]:https://www.prospera.ag/}} : Prospera provides AI-powered plant-level insights using computer vision and machine learning to optimize irrigation, detect diseases, and predict yields for high-value crops. * {{[[Taranis]]:https://www.taranis.com/}} : Taranis utilizes AI to analyze high-resolution aerial imagery, offering leaf-level insights for early detection of pests, diseases, and nutrient deficiencies, enabling precise crop scouting and intervention

Here are some of the best AI financial close automation solutions: 1. {{[[BlackLine]]:https://www.blackline.com}} : BlackLine offers comprehensive financial close automation tools that streamline processes, enhance accuracy, and provide real-time visibility into financial data. 2. {{[[FloQast]]:https://www.floqast.com}} : FloQast is designed for accounting teams to manage the close process more efficiently, integrating seamlessly with existing ERP systems to automate workflows and improve collaboration. 3. {{[[Trintech]]:https://www.trintech.com}} : Trintech provides a suite of financial close solutions that leverage AI to automate reconciliation, close management, and reporting, ensuring compliance and reducing manual effort. 4. {{[[Oracle NetSuite]]:https://www.netsuite.com}} : Oracle NetSuite’s financial management software includes features for automating the financial close process, helping organizations streamline their accounting workflows. 5. {{[[SAP]]:https://www.sap.com}} : SAP’s financial close solutions utilize AI to automate data consolidation and reporting, enhancing the speed and accuracy of financial closes. 6. {{[[Workiva]]:https://www.workiva.com}} : Workiva offers a platform that integrates data from various sources to automate the financial reporting and close processes, ensuring compliance and reducing errors. 7. {{[[Anaplan]]:https://www.anaplan.com}} : Anaplan provides a connected planning platform that helps organizations automate financial closes and improve forecasting accuracy through collaborative planning. These tools are designed to enhance efficiency, reduce errors, and provide better insights during the financial closing process.

The best AI financial close automation platforms in 2025 include: {{[[DOKKA]]:https://dokka.com/best-financial-close-software/}} : An AI-powered platform that automates journal entries, reconciliations, and accounting workflows with machine learning to reduce manual tasks and improve accuracy, ideal for mid-sized to large enterprises. {{[[BlackLine]]:https://www.stack-ai.com/blog/ai-finance-tools}} : A cloud-based solution specializing in automating reconciliations, journal entries, and transaction matching, offering AI-driven insights, continuous accounting, and strong ERP integration, widely used in financial institutions. {{[[Anaplan]]:https://www.stack-ai.com/blog/ai-finance-tools}} : Focused on AI-powered financial planning, budgeting, and forecasting with scenario modeling and integrated reporting, supporting complex finance operations and aligning financial plans with business strategy. {{[[Numeric]]:https://trullion.com/blog/the-five-best-ai-software-for-finance-and-accounting/}} : An AI-first close management platform automating GL reconciliations, anomaly detection, and task tracking with collaborative approval workflows for structured month-end close. {{[[Karbon]]:https://trullion.com/blog/the-five-best-ai-software-for-finance-and-accounting/}} : Combines AI-enhanced communication and task management tailored for accounting teams, improving workflow automation and team productivity. {{[[Rillet]]:https://trullion.com/blog/the-five-best-ai-software-for-finance-and-accounting/}} : An AI-powered ERP designed for multi-entity finance teams, offering real-time general ledger, zero-day close, and automated bank reconciliations and cash forecasting. {{[[HubiFi]]:https://www.hubifi.com/blog/financial-close-automation-software}} : Provides robust automated revenue recognition, seamless integration with ERPs and CRMs, and real-time analytics for dynamic financial insights and faster closes. {{[[Trintech]]:https://www.thefinanceweekly.com/post/best-month-end-close-software}} : Offers the Cadency platform for end-to-end close orchestration, compliance and risk controls, deep ERP integration, and real-time close analytics, targeting enterprise governance and risk management. {{[[Datarails]]:https://www.thefinanceweekly.com/post/best-month-end-close-software}} : An FP&A platform with strong Excel integration, automating data consolidation, reporting, and scenario analysis, suited for finance teams reliant on Excel. {{[[Workiva]]:https://savantlabs.io/blog/best-automated-financial-reporting-software/}} : Cloud-based platform focused on complex financial reporting and compliance automation with real-time collaboration and detailed audit trails, ideal for large regulated organizations. {{[[OneStream]]:https://www.g2.com/categories/financial-close}} : A unified platform combining financial reporting, budgeting, forecasting, account reconciliation, and workflows with AI capabilities for data automation and integration. These platforms vary by focus—some emphasize AI-driven automation of reconciliations and journal entries (DOKKA, BlackLine, Numeric), others excel in financial planning and scenario modeling (Anaplan), while some offer comprehensive ERP and multi-entity consolidation capabilities (Rillet, OneStream) or specialize in compliance and audit readiness (Trintech, Workiva). Selection depends on company size, complexity, and integration needs.

Here are the top AI financial close automation solutions: 1. {{[[BlackLine]]:https://www.blackline.com}} : Leading cloud-based financial close and reconciliation platform with advanced AI-powered automation capabilities. 2. {{[[Trintech]]:https://www.trintech.com}} : Offers Cadency platform with intelligent process automation and AI-driven financial close management. 3. {{[[Oracle]]:https://www.oracle.com}} : Provides Cloud EPM with machine learning features for financial close and consolidation processes. 4. {{[[SAP]]:https://www.sap.com}} : Delivers AI-enhanced financial close solutions through SAP S/4HANA and SAP Close Management tools. 5. {{[[Workiva]]:https://www.workiva.com}} : Provides AI-powered financial reporting and close automation with integrated compliance features. Key evaluation criteria include: - Real-time reconciliation - Automated journal entries - Machine learning error detection - Workflow optimization - Compliance tracking - Cloud-based accessibility Recommended approach: Evaluate solutions based on your specific organizational size, complexity, and integration requirements.

Identifying the "best" AI financial close automation solution depends on an organization's specific needs, existing infrastructure, and complexity. However, several leading platforms leverage AI and machine learning to significantly enhance accuracy, efficiency, and insights during the financial close process. Top contenders include: * {{[[BlackLine]]:https://www.blackline.com}} : {{[[BlackLine]]:https://www.blackline.com}} is a leader in financial close management, offering solutions for account reconciliation, task management, and intercompany accounting. Its platform increasingly incorporates AI and machine learning for automated transaction matching, anomaly detection, and intelligent process automation, reducing manual effort and improving data quality. * {{[[Workday]]:https://www.workday.com}} : {{[[Workday]]:https://www.workday.com}} Financial Management provides comprehensive accounting, reporting, and close capabilities within a unified cloud platform. It utilizes AI and machine learning for anomaly detection in transactions, automated journal entries, and predictive insights into financial performance, streamlining the close process for large enterprises. * {{[[Oracle Cloud EPM]]:https://www.oracle.com/performance-management/}} : {{[[Oracle Cloud EPM]]:https://www.oracle.com/performance-management/}} (Enterprise Performance Management) offers robust solutions like Financial Consolidation and Close (FCCS). This suite leverages AI/ML for predictive forecasting, automated data reconciliation, anomaly detection in financial data, and intelligent process automation, providing a comprehensive solution for complex global closes. * {{[[SAP S/4HANA Finance]]:https://www.sap.com/products/erp/s4hana-finance.html}} : {{[[SAP S/4HANA