Private client/work PoC - sanitized case study · 2026
Customer Support RAG Callbot API PoC
Callbot-compatible RAG API PoC for a customer-support scenario, with benchmark notes separating answer relevance, source accuracy, cold latency, and warm/cache latency.
Business Problem
A support chatbot PoC needed to be adapted into a callbot-compatible API flow so stakeholders could evaluate whether RAG answers could support customer-service interactions.
Role Scope
Converted the web-chat RAG direction into an API PoC, packaged benchmark evidence, clarified integration flow, and prepared an honest technical narrative for demo and pre-sales discussion.
Solution Direction
Exposed a synchronous JSON API around the RAG core, preserved conversation IDs for multi-turn context, added cache paths for repeated/similar questions, and documented benchmark limits without presenting it as production call-center infrastructure.
Deliverables
- Callbot-style JSON API
- RAG answer workflow
- Latency/cache benchmark notes
- Private-safe case study
Impact
Created a demo-ready integration story: 90% answer relevance on sample benchmark runs, visible warm-cache latency improvement, and clearly documented source-accuracy/cold-latency limitations.
Description
Private client/work PoC - sanitized case study. Converted a customer-support RAG chatbot into a callbot-compatible API demo with response caching, multi-turn conversation IDs, and benchmark notes covering answer relevance, latency, and source accuracy limitations.
Source repository is private. This portfolio entry intentionally does not link the GitHub repository.
Output / Proof Signals
Case Study
Case in a 12-block structure
Overview
Private client/work PoC - sanitized case study. A customer-support RAG chatbot was adapted into a callbot-compatible synchronous JSON API for stakeholder demo and integration discussion.
Context
The source repository is private, so this public case study intentionally avoids customer names, private endpoints, raw logs, screenshots, and direct GitHub links.
Business Problem
Stakeholders needed to see whether a RAG answer workflow could fit a callbot-style customer-support scenario, not just a web chat UI.
Role Scope
Converted the RAG workflow into an API PoC, clarified the demo flow, packaged validation evidence, and framed limitations honestly for a pre-sales conversation.
Solution Direction
Expose a synchronous JSON API, preserve conversation IDs, add exact/similar/golden cache paths, and return callbot-style response metadata around the RAG core.
Architecture
Callbot-style request -> API-key guarded FastAPI route -> cache paths -> retrieval/answer generation -> response adapter -> benchmark notes.
Implementation
The PoC used a FastAPI API layer, RAG retrieval, response caching, query logging, and callbot-compatible response shaping. It should not be described as production telephony infrastructure.
Demo Scenario
A client sends a troubleshooting message, receives a structured bot response with conversation continuity, and reviewers inspect latency/cache behavior and answer relevance.
Deliverables
Callbot-compatible API PoC, RAG response flow, cache behavior notes, benchmark summary, and private-safe portfolio case study.
Impact
Sample benchmark evidence supports a conservative claim of 90% answer relevance, while also documenting weak source/URL accuracy and cold-latency limitations.
Risk & Trade-off
Answer relevance, source accuracy, cold latency, warm/cache latency, and multi-turn behavior must be reported separately. Blending them would overstate the PoC.
Consulting Takeaway
The value is not pretending the PoC is production-ready; it is showing stakeholders a working integration path, the validation evidence, and the next implementation roadmap.