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Client Agentic Research Accelerator

Client-side initiative within the same ecosystem as the OpenSearch retrieval platform, focused on document insights extraction and prompt-chain workflows for consulting and proposal support.

What I led

Designed and deployed the solution architecture and delivery approach, including workflow design, tool orchestration, and stakeholder alignment.

Stack

LangChainLangGraph

Highlights

  • Designed client-side agentic workflows for extraction and synthesis from document sets.
  • Implemented prompt-chain patterns to generate reusable insight outputs for consulting workflows.
  • Structured workflows so they could operate alongside retrieval/search capabilities in the same platform ecosystem.
  • Needed to balance speed with output quality and practical business relevance.
  • Closely related to retrieval/search platform work, so project boundary should be framed as "client-side extraction/prompt-chain capability" rather than internal deep-research product.
  • Quality measurement was primarily stakeholder acceptance/readiness-driven rather than a single formal benchmark KPI.
  • Delivered within broader AI consulting program context.

Outcomes

  • Reduced time-to-insight for client research and proposal development.
  • Improved delivery responsiveness for research-heavy consulting workstreams.
  • Current data-extraction POC has been accepted/greenlit for production progression.