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paulsunnypark/README.md

Paul Sunny

Enterprise AI for real-world operations

I design and productize enterprise AI systems for contact centers, knowledge operations, speech, and business workflows.

현장의 제약을 이해하고, 온프레미스·하이브리드 환경에서 실제 운영 가능한 AI 제품과 플랫폼으로 연결합니다.

What I work on

  • On-premises and hybrid AI: private deployment, model routing, GPU operations, data residency
  • Voice and contact-center AI: streaming speech, dialog orchestration, agent assistance, quality assurance
  • Knowledge systems: RAG, enterprise search, content governance, knowledge assetization
  • Operational analytics: interaction analytics, QA signals, observability, auditability
  • Business integration: CRM/SFA, quotation, subscription, billing, and settlement workflows
  • Security and governance: trust boundaries, secrets, PKI, RBAC, retention, and verified deletion

Public reference architecture

Enterprise Contact Center AI Reference Architecture

A security-first, vendor-neutral blueprint for integrating speech, hybrid dialog, retrieval, model gateways, agent assistance, QA, analytics, and data governance across on-premises and hybrid environments.

Engineering principles

  1. Operational reality first: latency, availability, fallback, observability, and recovery are product features.
  2. Security before scale: identity, secrets, PKI, data classification, retention, and deletion define the platform boundary.
  3. Deterministic where required: workflows and policy remain explicit; generative models operate inside controlled decisions.
  4. Knowledge with provenance: enterprise answers need source authority, freshness, access control, and traceability.
  5. Product over project: reusable capabilities, stable interfaces, measurable outcomes, and clear ownership.

Architecture themes

Contact Center AI · On-Prem AI · Speech AI · RAG · Knowledge Platform · Model Gateway · QA & Analytics · Enterprise Integration · Security & Governance

Collaboration

I am interested in practical collaboration around enterprise AI platforms, contact-center transformation, secure private AI, knowledge productization, and operational business systems.

For public architecture discussions, use the reference repository issues.

Pinned Loading

  1. enterprise-contact-center-ai-reference enterprise-contact-center-ai-reference Public

    Security-first reference architecture for on-premises and hybrid contact-center AI platforms.

  2. RealtimeSTT RealtimeSTT Public

    Forked from KoljaB/RealtimeSTT

    A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.

    Python 1

  3. AgentGPT AgentGPT Public

    Forked from reworkd/AgentGPT

    🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.

    TypeScript

  4. awesome-mcp-servers awesome-mcp-servers Public

    Forked from wong2/awesome-mcp-servers

    A curated list of Model Context Protocol (MCP) servers

  5. self-hosted-ai-starter-kit self-hosted-ai-starter-kit Public

    Forked from n8n-io/self-hosted-ai-starter-kit

    The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for creating secure, self-hosted AI workflows.

  6. myshell-ai/MeloTTS myshell-ai/MeloTTS Public

    High-quality multi-lingual text-to-speech library by MyShell.ai. Support English, Spanish, French, Chinese, Japanese and Korean.

    Python 7.7k 1.1k