QuoteXai: An AI-Assisted Quotation Tool Concept Project
This is a concept project, not a shipped commercial product. QuoteXai was our internal exploration into AI-assisted quotation generation for service businesses (agencies, contractors, freelancers). We built UI designs and frontend samples; the product was never launched commercially.
The problem we explored
Service businesses spend disproportionate time on quotation/proposal documents. The work pattern is repetitive: pull scope from a discovery call, estimate hours, apply rate cards, write justification copy, format as a PDF, send. Most agencies do this 5–20 times a month, and the time cost runs 1–3 hours per quote when stacked across the team.
The QuoteXai concept explored what an AI-assisted quotation tool looks like when designed around the actual workflow — not around being a CRM or proposal platform that has quotation as a feature. The hypothesis: dramatically reduce per-quote time by using AI to draft based on past quotes, with the human reviewing and adjusting rather than starting from scratch.
Design decisions
Quote drafting starts from a discovery transcript
The user pastes (or uploads) the discovery call transcript. The AI extracts the apparent scope, deliverables, and timeline. The user reviews and corrects. Estimating, rates, and document generation happen on top of this validated scope.
The estimate as a structured editor, not a free-form AI output
The AI doesn’t produce a complete proposal in one shot. It produces structured line items (deliverable, hours estimate, rate, justification) that the user can edit individually. This makes the AI’s contribution auditable and easy to correct. “AI drafted, human reviewed” beats “AI generated, human checked” because the editing surface is clearer.
Past-quote pattern matching
The system learns from accepted quotes. If similar scope items have been priced before, the AI surfaces that as a reference. Over time, the user’s pricing becomes more consistent and the drafting becomes faster, because the AI builds an institutional memory of the team’s pricing patterns.
Output that doesn’t look AI-generated
The PDFs are typographically clean and use the team’s branding. The justification copy is plain professional prose, not the slightly-too-eager voice that AI defaults produce. Several rounds of prompt design went into making the output sound like it came from the team, not from an LLM.
What we built
- UI design system covering quote drafting, line-item editor, rate card management, past-quote browsing, PDF preview, settings
- HTML/CSS samples of the drafting workspace and the PDF output
- React component samples for the structured-AI-output pattern (line items as editable cards with AI provenance indicators)
- Prompt design specifications for the LLM components
Why we never shipped it commercially
Two reasons. First, the category started getting crowded as we were exploring — several established proposal tools (PandaDoc, Better Proposals, Bonsai) shipped AI features that ate the differentiation. Second, the unit economics for a tool at this price point in this category looked difficult relative to other product opportunities. We’ve retained the design system as a reference and incorporated the structured-AI-output patterns into client work where they apply.
Want a similar concept exploration?
EtherLabz runs paid concept design projects when you’re not yet ready to commit to a full build. Book a discovery call to discuss the right scope for your idea.
Concept project by Sanya, Mradul, and the EtherLabz team. QuoteXai is an unshipped concept; not a commercial product.