Work

Illustrative engagements — honest stories, no logo wall

The scenarios below are anonymised composites from past enablement work. They describe approach and constraints — not promised outcomes for your team.

Illustrative · Calgary brokerage · Lead scoring

A forty-agent desk drowning in portal imports

Situation. A Calgary brokerage had accumulated roughly forty thousand contacts from portal feeds, open-house tablets and legacy spreadsheets. Agents spent Monday mornings manually sorting "who might be warm" with no shared definition. Hot leads from Saturday open houses often waited until Wednesday for a call.

Approach. We audited their CRM fields, defined a scoring rubric with the ops manager and wired engagement events — email opens, showing requests, repeat portal views — into a nightly refresh. A weekly review meeting calibrated weights when the market shifted. Agents received a daily shortlist of fifteen contacts, not an overwhelming sortable grid.

Human review & compliance. Scoring rules excluded proxies for protected characteristics. When sample bias appeared in certain quadrants, we widened geography rather than over-fitting. PIPEDA retention schedules were applied to stale contacts — archive, not silent delete.

Outcome framing. Triage time dropped for teams that adopted the shortlist habit. Conversion rates varied by agent and season — we reported that honestly in the close-loop review rather than publishing a universal "3× leads" claim.

Client review session walking through lead scoring dashboard with brokerage operations lead

Scoring review · anonymised engagement

Listing desk with edited property descriptions and content approval queue

Listing workflow · content desk

Illustrative · Alberta team · Listing content

Evening writers who still sounded human on MLS

Situation. A regional team of twelve agents drafted listings after showings, often past ten pm. Rushed copy repeated the same adjectives; compliance disclaimers were inconsistent across rural and urban listings.

Approach. We built a structured draft template — neighbourhood hook, feature block, honest condition notes, CTA — with AI generating a first pass from agent bullet points. A part-time editor batch-reviewed each morning; agents could accept, edit or rewrite before MLS submission. Version history lived in a shared folder, not a mystery inbox.

Human review & compliance. Every published description passed a human. Square footage and room counts were never invented by the model — agents confirmed measurements. Fair-housing language was checked for coded neighbourhood signalling.

Outcome framing. Time-to-publish shortened for agents who used the template. Quality was measured by fewer MLS rejection notes, not vanity readability scores. We did not guarantee faster sales or higher prices.

Illustrative · Property manager · Enquiry automation

Rental enquiries that stopped duplicating on three channels

Situation. A property manager handling mid-rise rentals in Edmonton received the same availability question through website chat, email and a third-party listing site — often three times from one prospect. Staff copied answers manually; after-hours messages sat until morning.

Approach. We unified intake into one CRM pipeline with source tags, deployed a chat bot for hours, parking and pet policies within approved scripts and routed viewing requests to an on-call coordinator with SMS alert. Transcripts attached to the contact record so the next agent saw full context.

Human review & compliance. Escalation fired on sentiment keywords and on any mention of accommodation needs — those threads went straight to a human with fair-housing training. Consent for follow-up email was captured at first contact per PIPEDA expectations.

Outcome framing. Duplicate responses fell for teams that kept the CRM discipline. Occupancy timelines still depended on market rent and unit turnover — automation reduced noise, not vacancy rates by fiat.

Illustrative · Boutique brokerage · Ops integration

Listing launch checklists that actually fired in sequence

Situation. A six-agent boutique used separate tools for photography booking, e-signatures and social scheduling. Listing launches missed steps — lockbox ordered but social post forgotten — because checklists lived on paper.

Approach. We mapped their launch sequence into triggered tasks: signed listing agreement creates photography ticket, edited photos drop into a content approval queue, approved assets schedule to social with human final click. Error alerts pinged the ops lead when a step stalled more than forty-eight hours.

Outcome framing. Missed-step incidents decreased during the pilot quarter. We documented the integration so they could maintain it without our studio on every call — retainers covered tuning, not dependency.

Disclaimer. RealEstateAICo Inc. provides PropTech enablement services — not brokerage, portal or course offerings. Illustrative engagements describe past approaches; they are not guarantees of leads, sales or returns. AI-assisted outputs are human-reviewed. Our work follows PIPEDA and fair-housing requirements.

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