Solution initiatives

Practical solutions, clear stages.

Each initiative starts with a real challenge. We explain what is built, where AI may help, who remains accountable and what still needs to be measured.

Concept Defined, not built
Prototype Parts built, not yet evaluated
Pilot Tested with real users, measured
Operational Running routinely

Stage assignments are provisional pending owner confirmation. They describe current implementation evidence, not verified AI performance or outcomes.

EducationService operational · assistant prototype

Guided learning support for working students

Human-led coaching with a guided start and an assistant for first questions.

Visit Sleek Academia

Problem: Working students need support between sessions and a clearer route into a study plan.
Beneficiaries: Working students using guided academic support.
Intervention: A human-led service, onboarding and plan pages; an early assistant supports first questions.
Why AI: It may help with first-response guidance where it is useful and safe.
Human oversight: Human coaches remain responsible for support and any academic guidance.
Evidence: Live site, onboarding and plan pages. Assistant behaviour has not been evaluated; no outcome data is published.
Success measures: Inquiry-to-plan time, on-time submission rate and student confidence.
Next milestone: Set baseline measures with consenting students.

EducationConcept

Feedback and admin support for educators

Support draft feedback and routine admin while educators keep control.

Problem: Feedback and administration take time away from teaching.
Beneficiaries: Educators and the learners they support.
Intervention: Draft feedback against a rubric and assist with routine administration.
Why AI: It may prepare a starting point for educator review.
Human oversight: An educator approves every output; no automated grading.
Evidence: Concept only; no pilot or outcome data.
Success measures: Minutes saved per batch, draft acceptance rate and turnaround time.
Next milestone: Find one scoped pilot partner.

Small businessesPrototype

Inquiry capture and follow-up for service businesses

Structured intake, routing and reminders so fewer customer inquiries are missed.

Problem: Inquiries get lost, answered late or followed up inconsistently.
Beneficiaries: Service businesses and prospective customers.
Intervention: Structured intake, routing and follow-up prompts.
Why AI: It may help organise an inquiry into a useful, reviewable draft.
Human oversight: An owner approves replies; no autonomous customer messaging.
Evidence: Structured Maxie intake is implemented in this local preview. Public Sleek Beauty booking and concierge, plus Skylarks inquiry routes, exist. AI behaviour has not been evaluated.
Success measures: Response time, percentage followed up within 24 hours and inquiry-to-booking.
Next milestone: Set a baseline at Sleek Beauty, an internal venture.

Small businessesConcept

Organised business information and operations visibility

Turn scattered messages, receipts and notes into records an owner can use.

Problem: Business information is scattered and reporting takes too long.
Beneficiaries: Owners and teams in small businesses.
Intervention: Organise records, then make plain-language questions possible over a business's own data.
Why AI: It may extract structured records from messages and receipts.
Human oversight: The owner verifies records and remains responsible for decisions.
Evidence: Concept only; no implementation or outcome data.
Success measures: Admin hours per week, report preparation time and data completeness.
Next milestone: Map one business's information flow.

Sustainable developmentConcept · seeking partners

Digital readiness for micro and small enterprises

A low-cost bundle delivered with training through partner organisations.

Problem: Micro and small enterprises may lack affordable digital tools and practical support.
Beneficiaries: Micro and small enterprises participating through partner organisations.
Intervention: A low-cost offer page, inquiry handling and simple records with training. Business data stays with the business.
Why AI: It may help create useful drafts and organise information with owner review.
Human oversight: Partners and business owners guide delivery and verify use of data.
Evidence: Concept only; seeking a co-design partner. Alignment with SDG targets 8.3 and 9.3 is not measured impact.
Proposed indicators: Enterprises active after 90 days, records kept, response time and self-reported finance applications.
Next milestone: Co-design a pilot with a development partner.