01 ◆
A 14-field form is a wall. Visitors who would have completed a 3-question chat won't scroll past field 7.
AI quote engine · WordPress
A WordPress quote engine that talks like a sales rep.
A custom AI quote engine for WordPress: a RAG-grounded conversational widget that asks the questions a salesperson would, returns a priced quote band, and pushes the lead into your CRM with the full transcript attached. Replaces static forms — converts higher.
Book a 20-min scope call → See selected work
◆ RAG · OpenAI / Anthropic / Gemini · CRM-native · GDPR-aware
Why static forms underperform
Where the forms-only approach loses leads.
Five reasons your "Get a Quote" form is leaking high-intent traffic that a conversational quote engine would have captured.
02 ◆
Static forms can't handle conditional questions well. A solar lead and a generator lead need different intake — but you can't branch a static form without making it worse for both.
03 ◆
Visitors with edge cases bounce. "I need 30 yards of mulch but also tree removal" doesn't fit the form, so they leave instead of submitting.
04 ◆
Forms don't pre-qualify. Your sales team gets the same low-intent submission as a high-intent buyer; you sort it out by phone.
05 ◆
Forms don't answer questions. A visitor with one objection ("do you serve my zip?") often won't submit the form to find out — they just leave.
What ships
What's in the build.
Custom WordPress plugin (you own it). RAG indexed against your service docs, FAQs, and pricing rules. Branded, embeddable on any page or post.
- ◆ WordPress plugin (your repo, your IP, no SaaS lock-in).
- ◆ RAG knowledge base from your service docs, FAQs, and pricing rules — indexed via OpenAI embeddings or local sentence-transformers.
- ◆ Conversational widget — branded, accessible (WCAG 2.2 AA), keyboard-navigable, mobile-first.
- ◆ Pricing logic — same conditional/per-unit/per-package rules as a multistep calculator, but conversationally elicited.
- ◆ CRM push — HubSpot, Pipedrive, Zoho, Salesforce, ActiveCampaign, generic webhook. Full transcript + structured fields.
- ◆ Email + Slack notification with the lead's answers, transcript, and projected job value.
- ◆ GA4 + Meta + LinkedIn conversion events.
- ◆ Admin panel for non-developers to update pricing rules + add knowledge base docs.
- ◆ GDPR-aware: per-conversation data retention rules, right-to-delete, no PII to the LLM by default.
- ◆ 14 days post-launch monitoring + iteration.
Packages
Two AI quote-engine tiers.
Standard Most chosen
From $4,800
Delivery 3-4 weeks
- WordPress plugin (your IP)
- RAG over your existing site content
- Conditional pricing (per-unit, per-package, conditional discounts)
- CRM webhook + email + Slack
- GA4 + Meta + LinkedIn events
- Admin panel for prices + KB
- 14 days post-launch support
Custom
From $12,000
Delivery 6-10 weeks
- Multi-language (EN/ES/DE/FR/AR + others)
- Voice input + voice output
- Stripe deposit at quote acceptance
- Native CRM integration (Salesforce / HubSpot Enterprise)
- Multi-tenant for agencies / franchises
- A/B-testable variants
- 30 days post-launch + retainer option
FAQ
AI quote engine FAQs.
No fluff — the specifics buyers want before booking a call. If yours isn't here, ask on the call.
Does the AI hallucinate prices?
No — pricing comes from your structured rules engine, not the LLM. The LLM's job is conversational: ask the right questions, interpret the answers, and route them to the deterministic pricing logic. The visitor sees a chat; behind the scenes it's the same calculator math you'd run in a spreadsheet.
Which LLM provider does it use?
OpenAI by default (GPT-4o for cost-effective, GPT-5 for higher-quality). Anthropic Claude (Sonnet 4.6 / Haiku 4.5) and Google Gemini (Pro 2.5) are drop-in alternatives. We can also run local models for sensitive industries — slower, but data never leaves your infrastructure.
How does the RAG knowledge base get built?
Plugin crawls your site (or you upload PDFs/docs), chunks the content, embeds it via OpenAI or sentence-transformers, stores in pgvector or a local index. The conversation retrieves relevant chunks before generating each response so the AI quotes from your actual content, not generic training data.
What are the per-month running costs?
Token cost: typically $0.05-0.40 per completed conversation depending on model and conversation length. For a site doing 1,000 quotes/month: $50-400/mo. RAG embeddings are one-time + delta on content updates. We can cap monthly spend with rate-limits.
Will it work in languages other than English?
Yes — the LLM handles 50+ languages natively. Standard tier supports English; Custom tier configures the system prompt and KB embeddings per language. Multi-language sites typically pick a primary language and gracefully degrade for others.
Is this GDPR-compliant?
GDPR-aware by default: per-conversation retention windows, right-to-delete, encrypted storage, no PII passed to the LLM unless you explicitly enable it (some industries need it). For pure GDPR strict mode we run a local-LLM variant where data never leaves your infrastructure. Custom tier includes a compliance review.
How is this different from a Calendly + Typeform stack?
Calendly + Typeform forces visitors through a static flow regardless of intent. The AI quote engine reads intent and routes — a visitor asking a single question gets a quick answer + a calendar link; a visitor in deep-buy mode gets a full quote conversation. Conversion rate on the latter is typically 2-3x the static-form baseline.
Can I switch the LLM provider later?
Yes — the plugin is provider-agnostic via an adapter layer. Switching from OpenAI to Anthropic or Gemini is a config change, not a rebuild. Useful when pricing or capability shifts among providers.
Keep reading
Related pages & posts.
Spec your AI quote engine
Replace your quote form with a conversation.
Tell me what you sell and how you currently qualify. I send back a wireframe + fixed quote inside 48 hours.