What does consultance.ai build?

Production AI engines: agents, voice, vision, RAG, workflow automation, and predictive models — designed, deployed, and maintained end-to-end.

Who is consultance.ai for?

Real estate firms, property management companies, and operations-heavy businesses worldwide. Active clients across Dubai, London, Toronto, and Pakistan.

How long from idea to deployed engine?

Proof of concept in 1–2 weeks on your real data. Production engine deployed in weeks 3–6. Self-healing systems and team training included.

How does pricing work?

30-minute discovery call is free. Written audit follows in 1–3 days. Build is project-priced; ongoing partnership is a flat retainer with unlimited servicing.

Do you transfer code and IP?

Yes. Code and IP transfer at every milestone. No subcontractors, no offshore handoffs — direct line to the engineers building.

What stack do you build on?

OpenAI, Anthropic Claude, Vercel, Supabase, Next.js, React, Tailwind, Stripe, Linear, and GitHub — production-grade tools the team trusts.

Real estate developer · Dubai, UAE

Updated 2026-05-18

Palladium Developers: end-to-end AI sales stack — voice pods, CRM, and RAG.

Palladium Developers Dubai case study: end-to-end AI sales stack with voice pods, CRM automation, and RAG retrieval for closing teams.

Impact scorecard

post-implementation

Client

Palladium Developers

Region

Dubai, UAE

Focus

AI implementation

Problem

Palladium Developers run high-ticket Dubai projects where closers face technical, well-prepared buyers asking specific questions about payment plans, ROI, handover dates, floor plans, developer track record, escrow terms, and area comparables. The closing team was juggling disconnected tools: one CRM for leads, PDFs in shared drives for project specs, WhatsApp threads for client comms, and the brokerage's tribal knowledge for the rest. Closers walked into rooms either over-prepared (hours of reading) or under-prepared (wrong number quoted), and pipeline state was inconsistent across the team.

Solution

consultance.ai delivered a unified three-layer AI sales stack. Layer one — voice pods sit on every inbound channel (portals, web forms, paid social, WhatsApp), qualifying buyers within seconds and booking only serious intent into closer calendars. Layer two — CRM automation models the actual sales motion: lead → discovery → showing → reservation → SPA → handover, with auto-generated buyer briefs assembled before every meeting. Layer three — a RAG retrieval layer indexes every project brochure, payment-plan PDF, escrow doc, floor plan, and email thread, with permissioned access so closers can ask natural-language questions ("what's the 60/40 plan on tower B units?") and get cited, accurate answers in seconds. The three layers share one schema so a buyer question on WhatsApp can pull from project docs and write context back into the CRM record automatically.

Proof points

Dubai real estate developer with public presence across web, Instagram, LinkedIn, Facebook, and YouTube.
Three-layer stack (voice pods + CRM automation + RAG retrieval) in production.
RAG layer indexes project brochures, payment plans, escrow docs, floor plans, and email threads with permissioned access.
Pre-meeting buyer briefs auto-generated for every booked appointment.
Shared schema across voice + CRM + RAG so context flows in both directions.
Founder-led implementation through the GrowthGrid Dubai operating base.

View public reference

Outcomes

Closing rooms run on one unified engine instead of four disconnected tools

Inbound qualification handled by voice pods 24/7

Cited, accurate answers to buyer questions retrieved in seconds via RAG

Auto-generated buyer briefs before every meeting

Pipeline state consistent across the closing team

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