Design a scalable chatbot platform

Q: Design a scalable chatbot platform

This question evaluates a candidate's ability to design a scalable, production-grade chatbot platform that integrates ML-based inference, multi-turn conversational context management, knowledge retrieval from internal documentation, human handoff workflows, and security/privacy controls.

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System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master system design interviews.

Question

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Problem

Design a production chatbot platform that can answer user questions and hold multi-turn conversations for a product/company.

Assume the chatbot will be used in web and mobile apps and should be able to:

Answer FAQs and product/how-to questions using internal documentation/knowledge bases.
Support multi-turn conversations with conversation history (context).
Escalate to a human agent when it cannot help.
Be safe (avoid leaking sensitive info) and observable (monitoring/metrics).

Deliverables

Clarify requirements (functional + non-functional), traffic/latency targets, and failure modes.
High-level architecture and key services/components.
Data/storage design (conversation state, knowledge sources).
Key APIs (ingress, inference, human handoff).
Reliability, scaling, and monitoring plan.
Security/privacy considerations and abuse prevention.

Design a scalable chatbot platform

Quick Overview

Problem

Deliverables

Solution

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