Our Solutions
Three ways AI can move
from concept to practice.
Each offering is designed to deliver tangible value within a defined scope — with pricing and timelines agreed before work begins.
← Back to HomeHow every engagement begins
Before any technical work starts, we spend time understanding your situation. What is the business question? What data exists and in what state? Who will be using the output, and how?
These conversations shape the scope document — a short, plainly written agreement that defines what we will build, how it will be evaluated, and what a successful outcome looks like. Nothing happens until that is agreed.
This front-loaded process takes a little longer at the start. It also means that misalignment is addressed early, and that both parties know what they are working towards.
Discovery Conversation
We listen to your context, data environment, and business objectives before suggesting any approach.
Scope Document
Deliverables, timelines, pricing, and success benchmarks are written and agreed before development starts.
Development & Reviews
Structured progress check-ins throughout the engagement. Adjustments are documented and agreed in writing.
Delivery & Handover
A working deliverable, written documentation, and a plain-language outcome report. Followed by a handover session with your team.
Image Recognition and Classification
We develop custom image recognition systems that can identify, categorise, and tag visual content specific to your domain. Applications range from product identification in retail to defect detection in manufacturing, and from medical image triage to document classification.
We work with your existing image data — or help you build a dataset — and deliver a trained model with an API endpoint your applications can call. Accuracy benchmarks and confidence thresholds are established together with your team.
- Custom model trained on your image data and domain
- API endpoint for integration with existing applications
- Dataset assistance if needed
- Pre-agreed accuracy benchmarks and confidence thresholds
- Written documentation for model operation and maintenance
Typical use cases
- Retail product identification and inventory tagging
- Manufacturing defect and quality inspection
- Document classification and routing
- Medical image triage support
Typical use cases
- Customer segmentation for marketing precision
- Churn prediction for retention campaigns
- Lifetime value estimation for acquisition decisions
- Support ticket pattern analysis
AI-Enhanced Customer Insights
Go beyond traditional analytics by applying AI to your customer data — purchase history, interaction logs, support tickets, feedback forms — to uncover patterns that standard reporting tools may miss.
We build segmentation models, churn prediction tools, and lifetime value estimators that help your marketing and customer success teams act with greater precision. Results are presented in visual dashboards with clear, non-technical explanations.
- Works with purchase history, interaction logs, and feedback data
- Segmentation, churn, and lifetime value modelling
- Visual dashboards with plain-language annotations
- Results framed for marketing and customer success teams
Proof-of-Value Engagement
For organisations that want to explore AI but prefer to start small, this low-commitment engagement focuses on delivering tangible value within a defined scope. We work with you to identify a single, well-bounded problem, apply AI techniques to address it, and measure the outcome together.
The engagement lasts two to four weeks and concludes with an candid evaluation of results, including our candid perspective on whether scaling the approach would be worthwhile for your specific situation.
- Two to four week timeline with clear milestones
- Single, well-bounded problem scope
- Outcome measured against agreed criteria
- Candid evaluation — including if scaling is not advised
- Low-commitment entry into AI exploration
This engagement is well suited for
- Organisations new to AI investment
- Teams that need internal evidence before a larger proposal
- Businesses with a specific hypothesis to test
- Leaders who want an candid external perspective
Which option suits your situation?
| Image Recognition | Customer Insights | Proof-of-Value | |
|---|---|---|---|
| Starting price | HK$11,600 | HK$8,400 | HK$3,200 |
| Typical duration | 6–12 weeks | 4–8 weeks | 2–4 weeks |
| Commitment level | Full project | Full project | Exploratory |
| Best for | Visual data problems | Customer data problems | Organisations new to AI |
| Deliverable | Trained model + API | Models + dashboards | Outcome report + recommendation |
Not sure which fits? A Proof-of-Value engagement is often the most practical starting point. Let's talk it through.
Professional standards we apply
Data Security
Formal data processing agreement on every engagement. Your data is not retained after project completion.
Written Scope
Every engagement begins with a signed scope document. Changes are handled formally, not informally.
Pre-Agreed Benchmarks
Success metrics are established before development begins. No ambiguity at delivery.
Full Documentation
Every deliverable comes with documentation your team can use without relying on us.
Named Partner
A senior practitioner is responsible for delivery. You know who to speak to throughout.
Candid Assessment
If outcomes are not what was hoped, we say so clearly — and explain what the evidence means.
We start with a conversation, not a proposal
Tell us a little about your situation and what you're hoping to explore. We'll let you know whether we think we can help, and what a sensible starting point might look like.
Request a Conversation