Build AI Operations Intelligence SaaS

# ORBIT — Intelligent Business Operations Control Plane ## Development of an AI-Powered Operational Intelligence and Automated Recovery Platform ### PROJECT VISION I am looking to develop ORBIT, an innovative enterprise SaaS platform that connects business applications, monitors operational processes, detects anomalies, investigates failures, identifies probable root causes, and recommends or executes controlled corrective actions. Unlike conventional automation platforms that simply connect triggers and actions, ORBIT focuses on understanding how business operations function, identifying where processes break, measuring their impact, and helping organizations restore normal operations. The goal is to create a commercially viable, scalable software product with a functional MVP and a clear path toward enterprise deployment. ### 1. CORE PRODUCT MODULES **A. Business Process Intelligence Graph** - Map relationships between business applications, workflows, events, and dependencies. - Visualize operational processes. - Track process execution and dependencies. - Identify disconnected integrations and bottlenecks. **B. Operational Intelligence Engine** - Monitor incoming events from connected systems. - Detect missing events, unusual delays, duplicate records, and abnormal activity. - Establish configurable operational thresholds. - Generate real-time incident notifications. **C. AI-Assisted Root Cause Analysis** - Correlate events across connected applications. - Identify probable causes of operational failures. - Generate evidence-backed incident explanations. - Recommend appropriate corrective actions. **D. Business Impact Analysis** - Estimate the financial and operational impact of incidents. - Prioritize incidents according to severity. - Provide scenario-based impact estimates. - Display operational performance indicators. **E. Controlled Recovery Engine** - Generate recovery recommendations. - Execute approved corrective actions through APIs. - Support human approval for sensitive operations. - Implement retries, idempotency, and execution verification. - Maintain complete action histories. **F. Unified Intelligence Dashboard** - Real-time operational overview. - Interactive process visualization. - Incident management. - Root cause investigation. - Recovery status. - Performance analytics. - Integration management. ### 2. INITIAL USE CASE The first implementation should focus on digital agencies and service businesses. Example: A customer submits an enquiry through a website. The CRM receives the information, but an integration fails to notify the sales team. ORBIT should detect the missing notification, investigate the event chain, identify the failed integration, estimate the potential business impact, recommend a solution, and execute an approved recovery action. The system must then verify that the operation succeeded. ### 3. PREFERRED TECHNOLOGY STACK Frontend: - Next.js - React - TypeScript - Tailwind CSS - React Flow - ECharts Backend: - Python - FastAPI - REST APIs - Background workers Data Infrastructure: - PostgreSQL - Redis - Event processing architecture AI & Intelligence: - LLM API integration - Structured AI outputs - Anomaly detection - Root cause analysis - Evidence-based recommendations Integration & Infrastructure: - n8n - Webhooks - Docker - GitHub - Cloud deployment Security: - OAuth2 - Role-based access control - Encrypted credentials - Audit logging - Human approval policies Freelancers may recommend alternatives if they provide a clear technical justification. ### 4. DEVELOPMENT MILESTONES **Milestone 1 – Architecture and Foundation** - Technical architecture. - Database design. - Authentication. - Initial application structure. **Milestone 2 – Integration and Monitoring** - Three to five initial integrations. - Event collection. - Process mapping. - Monitoring infrastructure. **Milestone 3 – Intelligence Engine** - Anomaly detection. - Event correlation. - Root cause analysis. - Incident prioritization. **Milestone 4 – Recovery and Automation** - AI-assisted recommendations. - Controlled execution. - Approval mechanisms. - Verification and recovery history. **Milestone 5 – Dashboard and Deployment** - Complete interface. - Analytics and reporting. - Security testing. - Deployment. - Technical documentation. - Final handover. ### 5. EXPECTED DELIVERABLES The selected development team must provide: - Fully functional web application. - Complete frontend and backend source code. - Database schema and migrations. - Working API integrations. - AI-powered operational intelligence. - Automated monitoring and recovery capabilities. - Administrative dashboard. - Authentication and authorization. - Docker deployment configuration. - Automated tests. - API and technical documentation. - Deployment instructions. - Source code ownership and intellectual property handover. ### 6. QUALITY AND ACCEPTANCE REQUIREMENTS The platform must demonstrate: 1. Successful ingestion of events from connected applications. 2. Detection of configured operational anomalies. 3. Correlation of relevant events. 4. Evidence-backed root cause recommendations. 5. Controlled execution of authorized recovery actions. 6. Verification of actual recovery outcomes. 7. Complete audit trails. 8. Reliable handling of duplicate events and temporary failures. AI-generated conclusions must be distinguishable from verified system facts. The system must never execute sensitive or irreversible operations without appropriate authorization. ### 7. IDEAL FREELANCER PROFILE I am looking for experienced professionals or a small specialist engineering team with demonstrated experience in: - Enterprise SaaS development. - Distributed systems. - Python and backend engineering. - AI and LLM integration. - Event-driven architectures. - API integrations. - Database engineering. - Cybersecurity. - Production deployment. Applicants should provide relevant previous work, proposed architecture, technical approach, and realist