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AbhinavGupta707/README.md
Abhinav Gupta

Hi, I'm Abhinav 👋

Builder working across finance, healthcare, video, and consumer apps.

Focused on agentic AI: how to design workflows that solve real consumer and business problems.

  • Financial markets (research, trading, microstructure)
  • Consumer tech for emerging markets, India in particular
  • Agent protocols (MCP, A2A)
  • Hackathons (best way to learn fast)

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  1. IMC-Prosperity IMC-Prosperity Public

    Quantitative algorithmic trading engine that placed top 0.7% of 19,000+ teams in IMC Prosperity 4. Modular core, BSM options pricing, basket arbitrage, cross-day robustness sweeps.

    Python

  2. Fundamental-Research-AutoPilot Fundamental-Research-AutoPilot Public

    Autopilot for equity research: pulls SEC filings, scores 13 fundamental signals, then stress-tests Buy candidates with bull/bear/forensic AI agents and writes the investment memo.

    Python

  3. RunwayOps RunwayOps Public

    Agentic cash management platform for SMEs that turns financial signals into action.

    TypeScript

  4. miraya-engine miraya-engine Public

    Production virtual try-on engine for Indian menswear. ~1,000× cheaper and ~10× faster than image-generation APIs.

    Python

  5. Vigil Vigil Public

    Workspace-scale adverse-event horizon scanner — BOCPD + Poisson z-score + CUSUM ensemble with Benjamini–Hochberg FDR control. Workspace-scope A2A agent, signed FHIR DetectedIssue output.

    Python

  6. Crucible Crucible Public

    Founder-led GTM cockpit that turns a rough startup idea + cold email into a self-improving outbound system. Simulates buyer personas, rewrites copy, ranks leads by signal strength, sends a controll…

    TypeScript