About this project
Project Aegis is a mathematical, closed-loop SRE control plane for FinTech that uses Agentic AI to prevent operational failure in high-concurrency Core Banking Systems. Traditional monitoring relies on static alerts that miss complex microservice degradation like database lock contention. Aegis replaces human response with sub-millisecond anomaly detection and an autonomous AI agent swarm, guaranteeing 99.999% availability and zero double-spend ledger corruptions.Aegis solves critical FinTech threats: thundering herd surges during payroll days, network latency double-spends, and batch process collisions. Aegis constructs a 4D state vector ($x_t = [\text{Queue Depth}, \text{Thread Occupancy \%}, \text{DB Saturation \%}, \text{Retry Rate}]^T$) and uses Frequent Directions matrix sketching to track subspace shifts via Incremental Singular Value Decomposition (SVD). Projecting telemetry onto a healthy subspace matrix ($P_S = V_k V_k^T$), Aegis calculates residual norm error:$$\text{Residual Norm} = \Vert{} (I - P_S) x_{\text{norm}} \Vert{}_2$$Spikes above 15.00 trigger immediate remediation.The Agentic AI swarm features five specialized NitroStack agents: PRIME (orchestration), ATLAS (traffic engineering), CERBERUS (security), LIBRAN (micro-reconciliation), and HERMES (SOC2 compliance). The swarm executes three defense shields: Single-Flight Query Coalescing to reduce database read locks by 92%, SHA-256 Idempotency Intercepts to block duplicate payment retries, and QoS Admission Control to guarantee 90% bandwidth for critical wire transfers. Built on Node.js, TypeScript, and Next.js 14, Aegis delivers self-healing FinTech infrastructure.
BFSI & FinTech track
Build AI solutions for banking, payments, insurance, fraud detection, lending, and financial inclusion.