AI Integration Sprint • 6 weeks
AI vision inspection for Real estateMuscat, Oman
Classify, extract, and flag issues from photos/documents with a review lane for low confidence.
Founding cohort: $1,500 (50% off) for first 5 clients • Standard: $3,000 one-time
Explore: all real estate pages in Muscat • ai vision inspection across industries in Muscat
Week 1: Map workflows
Constraints, data, tools, and success metrics.
Weeks 2–5: Build prototype
Implement the use case with guardrails and iterative testing.
Week 6: Framework + rollout
Implementation framework, SOPs, and a rollout plan.
Common bottlenecks in Real estate
- • Leads go cold due to slow follow-up
- • Manual qualification and scheduling wastes agent time
- • Listing/tenant paperwork creates admin overload
Workflows we typically touch
- • Lead qualification
- • Appointment scheduling
- • Listing document intake
Integrations: WhatsApp, Email, CRM exports, Calendars
What you get
- • Working prototype tailored to real estate
- • Implementation framework (architecture + SOPs + rollout plan)
- • Human-in-the-loop guardrails (escalation + auditability)
How this use case works
Outcomes
- • More consistent checks
- • Faster reviews
- • Better traceability
Guardrails
- • Manual review for low confidence
- • Evidence retention
- • Clear thresholds
Implementation approach
- • Define classes/issues to detect
- • Prototype on sample images
- • Add review lane + evidence logging
More use cases in Muscat
Same city + industry (real estate), different workflows.
Same use case, other industries
Same ai vision inspection approach, adapted to different vertical workflows.
FAQ
Do you operate in Muscat?
We work remotely with teams across regions. The free assessment clarifies whether the sprint is a fit for your workflows.
Is this only for Real estate?
No — this page is tailored to real estate, but the sprint works for any SMB with repeatable workflows.
Can it handle WhatsApp inquiries?
Yes. We can design safe routing + escalation so hot leads get immediate attention without losing control.
Do we need perfect images?
No—prototype first, then define capture standards if needed.