--- title: "How We Built a Centralized AI Knowledge Platform to Power 71,000+ Questions" description: "EnactOn built a centralized AI knowledge platform for CrossEven that brings brand knowledge, AI agent training, and support workflows together, powering 71,000+ questions." keywords: ["AI knowledge base platform", "healthcare AI chatbot", "multi-brand AI agents", "MCP server integration", "AI agent training"] entityName: "EnactOn Technologies Private Limited" pageType: "CaseStudy" url: "https://www.enacton.com/case-studies/ai-chatbot-knowledge-base/" rawMdUrl: "https://www.enacton.com/case-studies/ai-chatbot-knowledge-base.md" lastUpdated: "2026-10-23" --- # How We Built a Centralized AI Knowledge Platform to Power 71,000+ Questions A discount changes. A service gets discontinued. A patient asks a question that only one person on the team knows how to answer. When information lives across scattered documents and systems, even simple questions become difficult to resolve. CrossEven needed a better way to manage knowledge across its multiple brands. EnactOn built a centralized platform that brings brand-specific information, AI agent training, and support workflows together in one place. ## Clients that have trusted us over the years DoctorNote, Frendo, Growlity, HouseMaxxing, Leadquity, LeafyDOC, ParkingMD, Proposalbiz, Sparissimo Food, WellnessWeg, Youmii ## Secure, high-speed products built for business growth Our software is engineered for speed, security and scalability — delivering dependable performance for businesses of every size. - **13+**: Years of Excellence - **350+**: Customers - **95%**: Repeat Client Rate - **65+**: Countries ## Every New Question Exposed Another Knowledge Gap. When information is scattered across documents, teams, and systems, finding the right answer becomes harder than it should be. For CrossEven, every brand had its own details to manage, and keeping AI agents accurate meant solving the knowledge problem first. ### Scattered Brand Knowledge CrossEven runs ParkingMD, WellnessWag and more. Each brand has its own services, regulations, promo codes and ways of working, so company knowledge lived in separate places. ### Outdated Information Services, discounts, and policies change regularly. Without a centralized source of truth, employees and AI agents risked sharing outdated information, creating confusion for customers and support teams. ### Limited Chatbot Control The previous support setup offered limited flexibility over chatbot behavior and knowledge management. Tuning responses was difficult, and the interface made everyday support operations harder than necessary. ### Repeating the Same Work Every new chatbot or AI agent needed access to the right information. Without reusable knowledge infrastructure, connecting data and maintaining consistent responses across brands became unnecessarily complicated. ## What If Every Agent Had Access to the Right Answers? EnactOn brought CrossEven’s brand knowledge, AI agents, and training workflows into one connected platform. Instead of managing information and chatbot behavior separately, the team gained a central system to keep knowledge organized, responses relevant, and support easier to scale. ### Centralized Knowledge Management We built one platform where CrossEven could organize documents by brand and service. Teams could add information, assign it to specific agents, and manage knowledge from one dashboard. ### Brand-Specific AI Agents We connected the knowledge base to patient support and internal support agents. Each agent could access brand-specific knowledge, shared information, or both, depending on its purpose. ### Live Pricing Integration Agents connected to the live pricing database could reflect current prices in their responses. This reduced reliance on manually maintained pricing documents and helped keep customer answers up to date. ### Continuous Agent Training Teams could review conversations and turn feedback into persistent instructions at brand or agent level. The system also consolidated duplicate or conflicting instructions to keep guidance consistent. ### Knowledge Gaps and Escalation When agents encountered unanswered questions, the platform logged knowledge gaps for review. Agents could provide partial answers where possible and route unresolved queries to human support. ### MCP and Support Integration We built an MCP server so compatible AI tools could update knowledge, revise instructions, and trigger supported actions. Changes were logged, giving teams another way to manage the platform. ## More Than 71,000 Questions Later, the Knowledge Was Working at Scale. With a centralized knowledge base powering patient and internal support agents, CrossEven gained a more consistent way to handle questions across its brands. And with around 71,000 questions handled overall, the platform gives the team a foundation to keep improving how information gets used. ### One Place for Knowledge CrossEven gained a centralized platform for managing information across brands, reducing the need to search through scattered sources or depend on individual team members for answers. ### Support at Scale The platform's analytics recorded approximately 17,000 questions handled in the last 30 days and around 71,000 questions across patient and internal support agents overall. ### A System That Learns Knowledge-gap tracking and conversation-based training gave the team a repeatable way to identify missing information, refine agent instructions, and improve responses as needs changed. ## Why It Made Sense for CrossEven CrossEven needed more than a chatbot. We built a connected knowledge platform that brings brand information, AI training, live data, and integrations together, creating a flexible foundation for current and future workflows. ### Centralized Multi-Brand Knowledge Base Organizes brand-specific and shared information in one dashboard, making knowledge easier to manage, update, and reuse across AI agents. ### AI-Powered Support and Live Pricing Integration Connects patient and internal support agents to relevant knowledge and live pricing data, helping them deliver accurate, up-to-date responses. ### Agent Training, Analytics, and Testing Uses conversation feedback, persistent instructions, performance analytics, and testing to identify knowledge gaps and continuously improve agent responses. ### MCP Integration and Human Escalation Enables compatible AI tools to update knowledge and instructions through MCP, while unanswered questions can be logged or escalated to human support. ## Client Testimonials & Reviews > "No matter it’s a day or night, there are responses to my inquiries and resolves my concerns in less than an hour." — **He Wang**, Founder at Cashbackist, Inc. > "Best thing about EnactOn is they have all under-one-roof solution for end-to-end business requirements." — **Tej Prakash**, Founder at AdGaem > "We appreciate their attention to detail and creative approach in bringing our new exhibit to life online." — **Y Sreekanth**, Founder at Cashkart365 > "EnactOn provided me with a more comprehensive proposal than I asked for, which helped me proceed smoothly with development." — **Tejas Ahobala**, Founder at Khareedhi > "All my worries and thinking turned in positive ways when I came across an expert team of EnactOn technologies." — **Aaksh Soni**, Founder at DealNo1 > "The technical approach to a solution has been their core strength. Overall domain and business expertise is truly remarkable." — **Quartzobr**, Founder at Kahle.com.br ## Frequently Asked Questions ### Can we use one knowledge platform across multiple departments and teams? Yes. A centralized knowledge platform can support customer service, sales, HR, and internal operations. Each team can access the information relevant to its role while reusing shared knowledge where appropriate. ### How do we prevent AI agents from confusing information across our brands? You can organize knowledge by brand, service, or category and control which information each agent can access. This helps agents respond using the right brand-specific context instead of mixing policies, pricing, or processes. ### What happens when our AI agent cannot answer a customer's question? You can configure workflows to log unanswered questions, identify missing information, and escalate unresolved queries to human support. These knowledge gaps can then be reviewed to improve future responses. ### Can we connect a knowledge platform to our existing tools and databases? Yes. Depending on your systems and available integration options, the platform can connect to existing databases, business applications, and compatible AI tools, helping you extend your current setup without rebuilding everything from scratch. ### How do we know if our AI support system is actually improving? You can track metrics such as question volume, unanswered queries, escalation rates, response accuracy, and resolution time. These insights help you identify recurring problems, prioritize improvements, and measure how well the system supports your team and customers. --- ## Company Entity & Canonical Verification - **Legal Business Name:** EnactOn Technologies Private Limited - **Headquarters:** 605, Luxuria Business Hub, Nr. V R Mall, Vesu, Surat, Gujarat, INDIA – 395007 - **Official Website:** https://www.enacton.com - **Direct Contact:** contact@enacton.com | +91 74260 60610 - **Career Enquiries:** careers@enacton.com | (+91) 90790 45453 - **Primary Service Category:** Custom Software Development, Startup MVP Engineering, White-Label Platform Development & IT Consulting