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working on portfolio projects
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working on portfolio projects

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Aparnap2/README.md

Hi, I'm Aparna Pradhan 👋

Code‑First Automation Architect | Full‑Stack & AI Agents

"Outcomes over demos. Governance over hype."

I modernize brittle, legacy/no‑code automations into reliable, scalable, cost‑efficient systems. I don't just write scripts; I build production-ready architectures with binary acceptance tests, P95 latency targets, and live ROI dashboards.


🛠️ The "Senior" Stack

I bridge the gap between AI research and Enterprise reliability.

Category Technologies
Language Python TypeScript
AI Orchestration LangGraph LiteLLM RAG (Graph/Vector)
Backend FastAPI NestJS Pydantic
Data & Vector PostgreSQL Redis Neo4j
Infrastructure Docker Langfuse GitHub Actions

🚀 Flagship Engineering Capabilities

I build systems that hit specific Service Level Objectives (SLOs).

1. Finance Inbox & Procurement (AP/AR)

Automated reconciliation with 100% duplicate detection.

  • Scope: Docling OCR + Pydantic validators + Anomaly digests.
  • Metric: ≥98% field accuracy on 200‑doc test sets.
  • Stack: Python, FastAPI, GraphRAG.

2. Generative Support Workforce

Email/WhatsApp resolution with strict governance.

  • Scope: Citations required, QA gating, Sentiment routing.
  • Metric: P95 response < 2 minutes; Breach alerts < 30s.
  • Stack: LangGraph, Redis Queues, LiteLLM.

3. Booking & Lead Ops

Idempotent calendar operations.

  • Scope: Intake → Qualifier → Slot Picker → Reminders.
  • Metric: +20% show‑rate vs baseline; < 60s write latency.

🧠 Engineering Principles

  • Predictability: Typed data flows end‑to‑end (TypeScript/Zod/Pydantic). No "stringly typed" code.
  • Security: Least privilege, audit logs, and PII redaction by default.
  • Observability: If it isn't logged in Langfuse/Phoenix, it didn't happen.
  • Ownership: Code‑first, no lock‑in. I build systems your team can extend.

🤝 Engagement Models

I work best with ops‑minded founders who value clear scope and sustainable systems over throwaway prototypes.

  1. 10‑Day Modernization Audit: Latency/cost baselines, SLAs, and a fixed pilot SOW.
  2. Pilot Build (10–14 days): Pass/Fail delivery based on acceptance criteria.
  3. Ongoing Ops: Monthly SLOs and change-managed improvements.

📬 Connect

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  1. clarification_agent clarification_agent Public

    an AI-powered agent that clarifies ambiguous user queries, gathers missing information, and provides actionable, context-aware responses. It leverages LangGraph to create a modular and extensible a…

    Python 2

  2. agentstack agentstack Public

    Shell

  3. autoadmin-APP autoadmin-APP Public

    Python

  4. invoicify invoicify Public

    A comprehensive AP (Accounts Payable) invoice processing system using Docling for intelligent document extraction, validation, and export capabilities.

    Python

  5. pmf_agent pmf_agent Public

    AI-powered framework for managing AI deployment decisions, experiments, and governance at scale. It combines multi-agent AI orchestration with human-in-the-loop approvals to ensure safe, data-drive…

    TypeScript

  6. supplygraph supplygraph Public

    multi-tenant SaaS platform that automates the "Procurement-to-Pay" cycle for SMEs using AI-driven workflows, real-time collaboration, and intelligent decision-making.

    Python