Ask.Q

Overview

Ask.Q is an internal AI-powered knowledge assistant and business intelligence layer designed to make user manuals, technical drawings, instructions, and product documentation searchable, conversational, and actionable. Built as a prototype for Qcells, it functions like a company-aware ChatGPT for product and operations teams while also serving as a practical support and routing tool.

Key Features

• Manuals You Can Chat With: Converts dense user manuals, drawings, and instructions into a conversational assistant experience.
• Knowledge Retrieval: Helps teams find the right answer quickly without digging through fragmented product documentation.
• Translation Support: Makes information easier to consume across language barriers when users need translated guidance.
• Ticket Submission by Chat: Allows users to submit support tickets directly through chat instead of calling or manually routing issues.
• Operational Context: Connects documentation to product, support, and operations workflows so answers lead to action.

Tech Stack

• Frontend: Next.js App Router, React, TypeScript
• Backend Services: Cloud Run services for chat and ingestion workflows
• AI Layer: Vertex AI-powered enterprise knowledge assistant
• Core Pattern: Retrieval-augmented generation (RAG)
• Document Processing: Ingestion pipeline for manuals, drawings, and instruction documents
• Content Layer: Structured product data and knowledge assets

Technical Highlights

• Reframed static product documentation into an interactive AI assistant experience.
• Positioned knowledge access as both a product enablement problem and a business intelligence problem.
• Designed an internal prototype that could scale beyond one company or one documentation set.
• Structured the system around real workplace friction: information overload, document sprawl, phone-based support, and delayed decision-making.
• Used chat as an interface not just for answers, but also for issue intake and guided routing.

Approach

Ask.Q is essentially a hybrid of enterprise chat, document intelligence, and operational support. Instead of forcing teams to search manually through PDFs, drawings, and fragmented instructions, it turns product knowledge into a structured AI interface that supports users contextually, translates information when needed, and helps drive action.

Impact

Ask.Q shows how AI can move from novelty to operational leverage. It improves how teams consume product knowledge, reduces time-to-answer, supports multilingual information access, and creates a path for support workflows where users can raise tickets through chat instead of relying on phone calls or manual escalation.