Apurv Raveshia’s Post

Discover the architecture behind AI assistants! From understanding language to executing tasks, each component plays a vital role in creating a smart, efficient AI assistant. Key components of AI Assistant architecture includes: 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐔𝐈: The Frontline of User Engagement 𝐋𝐚𝐫𝐠𝐞 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 (𝐋𝐋𝐌𝐬): The Cognitive Core 𝐓𝐡𝐞 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐒𝐭𝐨𝐫𝐞: The Memory Module 𝐏𝐫𝐨𝐟𝐢𝐥𝐢𝐧𝐠 𝐌𝐨𝐝𝐮𝐥𝐞: Defining the Assistant’s Role 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧 𝐋𝐨𝐠𝐢𝐜: Maintaining Context and Coherence 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠 𝐌𝐨𝐝𝐮𝐥𝐞: Mapping Future Actions 𝐀𝐜𝐭𝐢𝐨𝐧 𝐌𝐨𝐝𝐮𝐥𝐞: Executing Decisions 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐀𝐏𝐈: Connecting to External Systems 𝐂𝐚𝐜𝐡𝐞: Speeding Up Responses with Precomputed Data 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞: Managing Data and Interaction Histories Get more detail on Technical Architecture Behind AI Assistants https://lnkd.in/emmFx_3d and see how it works. If you’re looking to take your SaaS to the next level with AI Assistants Alphabase™ is here to help! We build custom AI Assistants designed to enhance your SaaS product and give you that extra edge. Book a meeting with us to see how we can make it happen! You can also book a 30-minute consultation with us. #alphabase #ai #aiAssistants #aiAgents #aiAssistantsForSaas #aiAgentsforSaas #aiForBusiness #aiForSaas #saasProduct

🚀 Unlocking the Power of AI in Financial Services Architecture Artificial Intelligence (AI) is now a game-changer for financial institutions, helping to enhance decision-making, optimise operations, and improve customer experiences. However, the challenge for many financial services firms is integrating AI across their complex environments without compromising security, regulatory compliance, or efficiency. 🔍 The Problem: Legacy systems, siloed data, and outdated processes are often barriers to adopting AI at scale. Without a cohesive architecture, AI initiatives may lead to fragmented solutions, inefficiencies, and missed opportunities. 🏛 How Business, Enterprise, and Solution Architecture Can Help: 1) Business Architecture ensures that AI solutions align with the broader business strategy. It helps financial services firms identify where AI can add the most value - whether it's improving customer engagement, risk management, or operational efficiency - and ensures these initiatives are tied to measurable business outcomes. 2) Enterprise Architecture creates the overall blueprint for AI adoption. It ensures that systems, data, and technology platforms are integrated, scalable, and secure. By providing a framework for aligning AI with existing technologies, enterprise architecture reduces the complexity of implementation and supports regulatory compliance from the ground up. 3) Solution Architecture focuses on the technical implementation of AI-driven systems. It designs the specific components and integrations needed to bring AI into day-to-day operations - whether through AI-driven decision-making models, customer service automation, or fraud detection systems. Solution architects ensure that AI systems are flexible, secure, and able to evolve with future needs. 💡 Key Takeaway: To unlock the full potential of AI in financial services, it’s essential to build a solid architectural foundation. By leveraging business, enterprise, and solution architecture, financial institutions can not only drive innovation but also ensure that AI initiatives are scalable, compliant, and deeply integrated with their operational goals. 🔗 Let’s discuss: How are you integrating AI across your business, enterprise, and solution architecture? What challenges or opportunities do you see? #AI #FinancialServices #DigitalTransformation #EnterpriseArchitecture #BusinessArchitecture #SolutionArchitecture #Innovation #CustomerExperience Affinity Reply

🚀 Internal machine customers are coming for your data — are your analytics teams ready? 🤖 The rise of autonomous AI agents acting on behalf of departmental business users will create an explosion of data query and analytical requests. Analytics, BI, and data science teams already struggling to meet human demand must prepare for this shift, now. 💡 This means updating your data and analytics operating model: 1️⃣ Pilot AI agents capable of handling multistep data-to-insight workflows with minimal intervention. 2️⃣ Build discoverable and reusable data products with strong metrics and semantic layers, machine-readable data contracts as interfaces and active metadata. 3️⃣ Design modular, open, and headless APIs optimized for agentic analytics that can be function called / invoked by software and AI engineers. 4️⃣ Communicate this change of value proposition for D&A to sponsors and stakeholders to secure funding to build the “next” version of your organization. 📊 Build agentic analytics process that can scaling to meet the machine demand— enabling a system where data, insights, and decisions flow more seamlessly and autonomously, with #AgenticAI. #AgenticAnalytics isn’t a distant vision; it’s what needs operationalizing for analytics at scale in 2025. How are you addressing the need for AI-ready #DataProducts and analytics services when workflow demand is driven by internal #MachineCustomers acting on behalf of business units?

My colleague David Pidsley shares some cool insights on the importance of good data and Agentic analytics to serve Machine Customers - a form of AI Agent. Machine customers are already here. Are your data and analytics capabilities ready?

𝐇𝐨𝐰 𝐀𝐈 𝐢𝐬 𝐑𝐞𝐝𝐞𝐟𝐢𝐧𝐢𝐧𝐠 𝐃𝐚𝐭𝐚 𝐋𝐢𝐧𝐞𝐚𝐠𝐞: 𝐀 𝐒𝐭𝐨𝐫𝐲 𝐨𝐟 𝐂𝐥𝐚𝐫𝐢𝐭𝐲 𝐀𝐦𝐢𝐝 𝐂𝐡𝐚𝐨𝐬 Imagine you’re rolling out a critical report, and suddenly the numbers don’t add up. Data lineage—the map of how data flows and evolves—is supposed to help, but without the right tools, it’s chaos. Now, picture this: You type a query, and an AI-powered lineage agent generates a real-time, interactive map of your data’s journey, from origin to transformation. It highlights dependencies, transformations, and anomalies in seconds—clarity that once took weeks of manual effort. 𝐖𝐡𝐲 𝐃𝐚𝐭𝐚 𝐋𝐢𝐧𝐞𝐚𝐠𝐞 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 Lineage isn’t just about compliance—it’s about trust. AI learns patterns, detects anomalies, and maps dependencies effortlessly. It scales with your systems, provides real-time insights, and ensures accuracy. Tools like Neo4j, OpenLineage, or Apache Atlas bring lineage to life with visualizations you can explore. Clients I’ve worked with struggled to trace sensitive data for regulatory reporting. After adopting AI-powered solutions, they transformed their ecosystems in weeks—manual tasks replaced with seamless automation. 𝐓𝐡𝐞 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐨𝐟 𝐀𝐈 𝐢𝐧 𝐃𝐚𝐭𝐚 𝐋𝐢𝐧𝐞𝐚𝐠𝐞 1️⃣ Automation: AI scans metadata, logs, and workflows to create lineage maps effortlessly. 2️⃣ Scalability: Handles single databases or multi-cloud environments with ease. 3️⃣ Accuracy: Detects patterns humans often miss. 4️⃣ Real-Time Insights: Keeps lineage updated dynamically. 5️⃣ Interactive Visualizations: Explore lineage in real time. When you trust your data’s origins and transformations, you enable faster decisions, reduced risks, and better collaboration. How are you handling data lineage today? Let’s discuss how AI can transform your approach. #AIinData #DataLineage #DataGovernance #AIInnovation #DataTrust #Automation #DigitalTransformation

👉 Introducing an enhanced tech stack to bridge today's AI Agent Stack with tomorrow's Agentic Mesh implementations. This adaptive architecture delivers enterprise-grade capabilities while embracing the evolving AI tooling landscape. ------ ✍️ The 8 essential layers provide: ● Clear separation of concerns ● Modular implementation patterns ● Flexible tool integration ● Enterprise-grade security ● Advanced learning capabilities 🔑 As the AI Agent ecosystem rapidly matures, organizations need an infrastructure that's both enterprise-ready today and adaptable for tomorrow's innovations. The Agentic AI Control Plane delivers this foundation. 🧐 Want to learn more: ✨ Join the the industry-first AI Agent Ops Evaluation Linkedin Group https://lnkd.in/dMDFZMJa ------ 🌈 Agentic Systems are the future of AI - what's needed are performance evaluation metrics best practices, standards, i.e. Agent Ops Evaluation Framework (AOF)™ --- 🚀 Key Components of Agent-Based Systems 1️⃣ VERTICAL AGENTS Industry-Specific Implementations 2️⃣ AGENT API GATEWAY 2.1 Discovery Protocol 2.2 Security Controls 2.3 Transaction Management 2.4 LLM Access Orchestration 3️⃣ AGENT HOSTING & SERVING 3.1 Deployment Management 3.2 State Management 3.3 Service Orchestration 4️⃣ AGENT LEARNING & ADAPTATION 4.1 Core Learning Methods 4.2 Advanced Learning 4.3 Learning Operations 5️⃣ AGENTOPS & SECURITY 5.1 Monitoring & Analytics 5.2 Lifecycle Management 5.3 Security Operations 6️⃣ INTEGRATION & COMMUNICATION 6.1 System Integration 6.2 Agent Communication 6.3 Protocol Adaptation 7️⃣ AGENT FRAMEWORKS & TOOLS 7.1 Development Frameworks 7.2 Tool Libraries 7.3 Sandbox Environments 8️⃣ INFRASTRUCTURE 8.1 Model Serving 8.2 Memory Systems 8.3 Storage Solutions 🤔 What do you think? Are these the right layers? What's missing? --- #AgenticAI #EnterpriseAI #AIArchitecture #AIInfrastructure #Innovation #TechStack #AIAgents #FutureOfAI

Building an effective AI tech stack goes beyond tools—it's about aligning technology with strategy to drive real impact💡 In today’s rapidly evolving landscape, crafting a tech stack that aligns with your strategic goals ensures you’re not just keeping up with trends but leading with purpose. From data pipelines to deployment frameworks, each layer contributes to unlocking AI's full potential🔍✨ #ai #techstack #innovation #digitaltransformation #artificialintelligence #machinelearning #dataanalytics #futureoftech #aitechnology #datascience #bigdata #automation #deeplearning #smarttech #mlops #cloudcomputing #techinnovation #businessgrowth #aidevelopment #techtrends #innovationstrategy #aiapplications #techstackoptimization #businessintelligence #digitalsolutions #dataengineering #predictiveanalytics #advancedanalytics #nextgenai #aiforbusiness #digitalstrategy #emergingtech #aiplatform #intelligentautomation #techstrategy #industry40 #cloudinfrastructure #futureofai #smartbusiness #machinelearningmodels #businesssolutions #aiinbusiness #technologytrends #enterprisetech #aiintegration #datainfrastructure #aipowered #digitaltransformationstrategy #aiforeveryone #aiinsights #techsolutions #dataarchitecture #cloudtechnology #innovationdriven #datainnovation #digitalecosystem #aifuture #techoptimization #aiadoption #aiopportunities #futuretech #aiadvancements #appliedai #digitalgrowth #scalability #dataplatforms #businessintelligenceai #artificialintelligencetechnology #techsuccess #machinelearningai #cloudsolutions #machinelearningops #aistack #innovativetech #datastrategy #businessintelligenceanalytics #digitalevolution #aiforsuccess #aiengineering #predictivetech #aialgorithms #aiimplementation #aiinfrastructure #mlsolutions #dataforgood #digitaltransformationai #dataandai #smartanalytics #futurebusiness #aiinsightsforbusiness #businessai #digitalintelligence #smartdata #intelligentdata #aiinspired #aiforinnovation #mlstack #digitalai

We've been dropping some exciting announcements lately! Here's the latest on the new Data Integration features: ⚛️ Vector Database Support to allow for processing unstructured data supporting all sorts of AI applications. 🪄 Merlin Intelligent Document Processing to simplify data extraction from complex documents like invoices or resumes. 🧮 Inline Functions for code-free flexibility with complex data transformations. ✨ AI-generated Workflow Summaries for real-time, hassle-free documentation. 📁 Unified Data Integration to combine traditional workloads with AI-related tasks into a single platform. We're building the future of data integration for the AI era. Now all your business data can share a platform regardless of the app it starts in. That means easier data transformations, faster development cycles, and better collaboration. In other words, the latest features help you turn data into action, and action into value. #AI #integration #VectorDatabase

Transform your operations with iOPS, the AI-driven platform by UNIQ. Our cutting-edge solution offers AI-driven monitoring, comprehensive tracking, workflow automation, data analytics, real-time reporting, and performance management. With iOPS, make your operations smarter & more efficient. #UNIQ #AI #Automation #DataAnalytics #iOPS #Innovation #Efficiency

Rethinking Success: The AI-Centric Architecture for Business Growth In today’s fast-evolving business landscape, AI has the potential to revolutionize how organizations operate, but without a clear strategy, it risks being underutilized. To truly capitalize on AI’s capabilities, businesses need an AI-centric architecture that integrates real-time insights, streamlines workflows, and drives execution excellence. #AI #BusinessTransformation #SalesExecution #RevenueGrowth https://lnkd.in/eS28JMZY