Curious Endeavor White Space — AI Strategy Brief
Call Debrief — Mar 24, 2026

White Space
AI Strategy

Aytan (CEO) and Menash (Israel Sales) want to reposition White Space from design/construction firm to tech-forward AI company. This is the operational brief from the call.

Participants Aytan, Menash, Assaf
Tasks 7 open
Questions 3 unresolved
Status Active — validate before building
Strategic Context

The Shift

White Space in 2026 needs to move beyond "design and construction firm." The goal is to speak the language of tech — value engineering, global supply chain intelligence, AI-powered operations — without losing credibility on the $20M/month traditional business.

The Positioning

Hospitality clients don't need more furniture. They need intelligence. White Space wants to be the company that brings AI directly to hotel sales teams — instant estimates, automated quotes, real-time recommendations. "Ahead of the curve" for the legacy-system crowd.

The Mandate

Validate before building. No full product investment until the market signals demand. Run LinkedIn A/B tests, test with Betty and franchisees, and watch what creates awareness. Only then commit resources to the full WS Estimator platform.

The Core Tension

Aytan's concern: "How do you develop conversations around AI technology while customers are currently buying $20 million/month in traditional services?" Answer from the call: don't sell AI. Sell solutions. The AI is the mechanism, not the message. Lead with what it does for the client in the room — instant estimates, smarter sourcing decisions, faster quotes.

The Product — WS Estimator

Course Estimator
by White Space

AI-powered quotation platform for construction and design projects. Generates instant price estimates, automated RFQ processing, and investment justifications. Lives at whitespace.com/pipeline.

  • RFQ ProcessingAutomated intake
  • Price IntelligenceMarket data layer
  • Catalog ManagementProduct + pricing DB
  • Cost AnalysisKD, net benefit, ROI
  • Automated RecommendationsYes/no investment logic
  • ExportRFI, Excel, PDF
85%
Automation rate on quotes
15%
Human involvement needed
$20M
Monthly traditional revenue at stake
$200
LinkedIn test budget to validate
Live at: whitespace.com/pipeline — password protected, demo-ready
Tasks — Operational Breakdown
01
Create Marketing Materials for WS Estimator
Build the pitch deck, one-pager, and demo visuals that make the tool feel cinematic. Aerial hotel photography, real-time demo feel, "new and innovative" on screen.
CE High Priority Deliverable
+
Steps
  • Source 8–12 high-quality hotel aerial images (licensed)
    Unsplash Pro, Getty, or commission. Look for rooftop pools, lobbies, dramatic exteriors. No stock photo vibes.
  • Create a 1-page PDF product brief — "Course Estimator by White Space"
    Value prop, 3 key benefits, how it works in 3 steps, and a CTA to request access. Design = hotel luxury meets tech precision.
  • Build a demo screen recording or animated mockup of the tool in action
    Show: enter hotel location → instant estimate → recommendation output. This is the "theater" moment Aytan described. Loom or screen capture + light animation.
  • Build a 5-slide deck for Jennifer meetings
    Slide 1: The problem (hotels waste time on manual quotes). Slide 2: The product. Slide 3: Live demo embed. Slide 4: Validation stats. Slide 5: CTA / next step.
  • Prepare LinkedIn visual assets (3x post visuals)
    For the A/B test campaign. Formats: 1:1 and 4:5. Clean, bold, no generic AI look.
Done When

PDF brief + demo video + 5-slide deck + 3 LinkedIn visuals ready. Aytan can walk into a Jennifer meeting and close with the materials on screen.

02
Run LinkedIn A/B Testing Campaign
$200–300 budget. Test 3 messaging angles before building anything. Aytan's direct instruction: "validate before investing."
CE High Priority Validate First
+
Steps
  • Define 3 messaging angles to test head-to-head
    Angle A: "AI estimator for hotels" (product-led). Angle B: "Hospitality needs intelligence, not just furniture" (positioning-led). Angle C: "The end of manual RFQs" (pain-led). Write 2 post variants per angle = 6 posts total.
  • Define audience targeting for LinkedIn Campaign Manager
    Targets: Hotel GMs, Procurement Directors, Hotel Ownership Groups, Hospitality Development. Geo: US, Middle East, Europe. Company size: 200–5000.
  • Set up campaigns with $50 per angle ($150 total), 7-day run
    Objective: engagement + link clicks. Track: CTR, comment sentiment, save rate, DM requests.
  • Define success criteria before launching
    Pass: CTR >1.5% OR 30+ meaningful comments OR 5+ DM requests about the product. Fail: under all three. Go/no-go decision after 7 days.
  • Post results summary to Aytan — recommendation on which angle to double down on
    1-page report: winner angle, engagement data, and recommendation for next investment step.
Done When

Campaign ran, data collected, winner angle identified, and Aytan has a clear go/no-go recommendation with evidence. Total spend: under $300.

03
Betty Test — Franchisee Price Offer Pilot
Connect Aytan with Betty. Test whether non-technical franchisees can generate a price offer through the estimator without human help. This is the real A/B test for the product.
Menash / Aytan Product Validation
+
Steps
  • Prepare a 1-page brief for Betty explaining the tool in plain language
    No tech jargon. What it does: "You enter a hotel location and project scope, it gives you a price estimate in seconds." Include a link to the whitespace.com/pipeline demo + password.
  • Schedule a 30-min call with Betty — demo + feedback session
    Agenda: 10 min demo, 20 min honest feedback. Key questions: Can you see yourself using this? Would your franchisees use it without training? What would make you trust the output?
  • Run 3 test scenarios live during the call
    Scenario 1: New hotel, standard fit-out. Scenario 2: Renovation, existing brand standards. Scenario 3: Franchisee entering numbers independently (watch where they hesitate).
  • Collect brand standards + product catalog from Betty post-call
    The estimator needs this data to be accurate. Without brand standards, outputs are illustrative only. Treat this as a dependency for any real deployment.
  • Write up findings — can franchisees self-serve or not?
    Binary answer. If yes → product is ready for wider rollout. If no → what's blocking them? Is it UI, trust, data gaps?
Done When

Call happened, 3 scenarios tested, brand standards received, and a clear yes/no on franchisee self-serve viability. This result directly informs the next product build decision.

04
Send Retail Package — Hammer & Nail
Compile and send the full retail materials package. Aytan referenced "everything in the ASAPH package" — catalog, product info, delivery timelines, shop layout.
Aytan → CE Transfer
+
Steps
  • Aytan to compile: catalog, product list with prices, brand standards doc
    Everything that was in "the ASAPH package." If anything is missing, list it explicitly so CE can flag the gaps.
  • CE to inventory what currently exists in the retail website
    Review the live Hammer & Nail landing page: delivery timeline, project docs, shop layout by layers, catalog. List what's live vs. what's missing.
  • Identify which other clients need the same retail website treatment
    From the call: "Column" was mentioned as a client needing the same build. Map out which clients are in queue and what they need replicated.
  • Scope the replication work — timeline and scope per client
    Estimate: how long to replicate the H&N site for a new client if they provide catalog + brand standards? This becomes a productized service offering.
Done When

CE has the full retail package received from Aytan, inventory of live site is documented, and a client queue list with scope estimates exists.

05
Build "AI in Hospitality" Content via Signal
Use CE's Signal platform to research "AI in hospitality" and generate content assets. This feeds the LinkedIn campaign and positions White Space as the company that's thinking about this.
CE Content
+
Steps
  • Run Signal research on: "AI in hospitality," "hotel procurement AI," "hospitality intelligence"
    Pull from Twitter, LinkedIn, web. Looking for: emerging trends, competitor moves, what hotel operators are actually worried about.
  • Generate 10 post drafts from Signal output
    Mix: thought leadership (3), product-adjacent (4), industry signal reposts with commentary (3). All from White Space POV.
  • Select best 5 — one per week for a month of LinkedIn presence
    Criteria: does this make White Space sound like the smartest person in the room? Not "we built a thing," but "here's what's happening in your industry."
  • Create branded visual assets for each post
    AI-generated hotel imagery + White Space type treatment. Clean. Not generic. Should feel like editorial, not marketing.
  • Package for Jennifer — review and approve before scheduling
    1-page content calendar with post copy, visual, and scheduled date for each. Jennifer approves, CE schedules.
Done When

5 LinkedIn posts with visuals, approved by Jennifer/Aytan, scheduled for the next 5 weeks. White Space has a voice in the AI hospitality conversation before the product launches.

06
Get Brand Standards from Betty
The estimator can't be accurate without brand standards. This is a blocking dependency for the franchisee test and any real product deployment.
Menash Blocker
+
Steps
  • Menash drafts a clear, specific request to Betty
    Ask for: brand standards document (preferred materials, finishes, approved suppliers), product catalog with price ranges, any existing RFQ templates they currently use.
  • Set a 1-week deadline for response
    Frame it as: "We're preparing the estimator demo for your franchisees — we need this to make the outputs relevant to your brand." Urgency through context, not pressure.
  • Feed received data into the estimator catalog
    Whoever has SSH/access to the whitespace.com/pipeline server handles the data import. This unlocks realistic outputs for the Betty demo.
Done When

Brand standards received, loaded into the estimator catalog, and the system can produce franchise-accurate price estimates. This unblocks Task 3.

07
Replicate Retail Website for Additional Clients
The Hammer & Nail retail site (delivery timeline, project docs, shop layout, catalog) needs to be replicated for Column and other clients in queue.
CE Dev Ongoing
+
Steps
  • Map the H&N site components into a reusable template spec
    Sections: delivery timeline module, project docs upload, shop layout with layer search, catalog with product entry. Document what's static vs. client-configurable.
  • Confirm Column as the next client and get their data
    From the call: "That's about retail. I'll play with that. Maybe I need your help." — This is on Aytan to confirm Column's scope and provide their catalog + brand materials.
  • Build Column instance from the template
    Swap brand assets, load catalog, configure layers. Target: 2-day turnaround once all client assets are received.
  • Document the replication process as a CE productized offering
    If White Space is selling this to multiple hotel clients, CE should have a clear scope, price, and timeline for "retail site in a box." This becomes repeatable revenue.
Done When

Column site live, template documented, and CE has a defined productized offering for future White Space retail clients. Replication time: <2 days per client with assets.

Open Questions
Q1
How does Aytan open the AI conversation with clients buying $20M/month traditionally?
The call surfaced this tension clearly but didn't resolve it. Recommendation from Assaf: sell solutions, not AI. But Jennifer needs a specific talk track and objection script for this transition.
Q2
Without Betty's brand standards, the estimator produces illustrative-only numbers. Real deployment for any franchisee network is blocked until this is received. Menash owns this follow-up.
Does Betty have brand standards ready — and will she share them?
Q3
Who else besides Column needs the retail site build?
Aytan mentioned "maybe I need your help" on other retail clients but didn't name them. This needs a client queue list before CE scopes further development work.