AI Integration Sprint • 6 weeks
AI vision inspection for ConstructionJohannesburg, South Africa
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 construction pages in Johannesburg • ai vision inspection across industries in Johannesburg
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 Construction
- • Progress updates and documentation are inconsistent
- • Site issues get reported late
- • Back-office workflows are fragmented across tools
Workflows we typically touch
- • Daily site reporting
- • Issue triage
- • Document intake (RFIs, photos, notes)
Integrations: Email, WhatsApp, Shared drives, Spreadsheets
What you get
- • Working prototype tailored to construction
- • 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 Johannesburg
Same city + industry (construction), different workflows.
Same use case, other industries
Same ai vision inspection approach, adapted to different vertical workflows.
FAQ
Do you operate in Johannesburg?
We work remotely with teams across regions. The free assessment clarifies whether the sprint is a fit for your workflows.
Is this only for Construction?
No — this page is tailored to construction, but the sprint works for any SMB with repeatable workflows.
Do we need perfect data to start?
No. We start with workflow mapping and a prototype using sample data, then define the rollout requirements.
Do we need perfect images?
No—prototype first, then define capture standards if needed.