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AI Enhancement for Enterprise Troubleshooting

AI Enhancement for Enterprise Troubleshooting

Pending
💰 INR 12500–37500 👤 Unknown 🕒 22d ago status: new
Java Script Install Troubleshooting Splunk Data Analysis Automation API Development Predictive Analytics AI Chatbot Development AI Development
Bid Proposal: AI-Driven Troubleshooting and Efficiency Enhancement Objective To design and implement AI-assisted solutions using existing enterprise tools to reduce troubleshooting time, improve system visibility, and automate repetitive operational tasks. --- Scope of Work The following solutions are proposed for implementation: 1. AI-Powered Log Analysis Assistant - Integrate Splunk with Copilot or FAB AI - Automatically analyze logs and suggest potential root causes - Provide concise, actionable insights for faster debugging --- 2. Intelligent Incident Summary Generator - Aggregate data from Splunk, Glowroot, Jira, and Salesforce - Generate structured summaries for incidents - Share summaries via Outlook or Microsoft Teams --- 3. Unified Monitoring Dashboard - Combine data from Grafana, SolarWinds, and SQL Server - Provide a centralized view of system health and performance - Highlight anomalies and trends for proactive monitoring --- 4. Microsoft Teams Troubleshooting Assistant - Develop a Teams-based bot for quick access to system data - Retrieve logs, traces, and ticket details on demand - Provide AI-driven troubleshooting suggestions --- 5. AI-Based Knowledge Repository - Convert historical Jira tickets and Salesforce cases into a searchable knowledge base - Enable faster issue resolution using past solutions - Improve knowledge sharing across teams --- Approach and Timeline Phase 1 (2–3 weeks): - Develop prototypes for log analysis and incident summarization - Create initial monitoring dashboard Phase 2 (3–5 weeks): - Build Teams troubleshooting assistant - Implement knowledge repository Phase 3 (Ongoing): - Enhance solutions with predictive insights and automation --- Expected Outcomes - Reduction in troubleshooting time by 25–40 percent - Faster incident resolution and improved SLA adherence - Improved visibility across systems - Increased efficiency through automation - Better knowledge reuse and reduced dependency on individuals --- Deliverables - Functional prototypes and tools - Documentation and user guidelines - Demonstration sessions - Periodic reports on impact and improvements --- Dependencies - Access to required tools and data sources (Splunk, Grafana, Jira, Salesforce, SQL Server) - Coordination with relevant teams for integration - Approval for use of AI tools such as Copilot and FAB AI --- Request Approval is requested to proceed with Phase 1 implementation and demonstrate initial results within a short timeframe. ---
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