About Us
We help organisations meet AI on their own terms
Thoughtform was founded on the idea that AI adoption works better when it starts with listening — to your people, your processes, and the specific pressures your industry faces.
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Built from practical experience, not theoretical enthusiasm
Thoughtform grew out of frustration with how AI was being sold to organisations — as a category of promises rather than a set of tools with real trade-offs. The founders had spent years working in data and technology roles across finance and professional services in Hong Kong, watching well-intentioned AI projects stall because the expectations set at the start bore no relation to what was actually possible.
We started small, working with two clients who were willing to let us take things slowly and honestly. Both projects delivered what they promised. That foundation shaped everything about how we work: discovery before proposals, iteration before finality, documentation before handover.
Today, Thoughtform works with organisations across finance, legal, healthcare, and communications. We're a deliberately small team — enough to bring real expertise, small enough to give every engagement personal attention.
Our Mission
To make AI adoption in Hong Kong organisations more honest, more considered, and more durable — by prioritising understanding over speed.
Our Vision
A business landscape where AI tools are understood by the people who use them, accountable to the outcomes they produce, and adaptable as those outcomes evolve.
Our Promise
We won't recommend what we can't honestly justify. Every engagement starts with a candid assessment of whether AI is the right approach for your situation.
The Team
People who've worked on both sides of the table
Our team combines applied machine learning experience with firsthand knowledge of how organisations in Hong Kong operate — including their constraints and their obligations.
Rachel Mak
Founder & Principal Consultant
Over a decade in data strategy and applied ML, previously with a regional bank's analytics team. Leads client discovery and solution architecture.
James Tong
NLP Engineer
Specialist in natural language processing for financial and legal text. Background in computational linguistics, with experience across Cantonese and English datasets.
Ada Wong
Training & Literacy Lead
Designs and delivers the AI Literacy Program. Former corporate trainer with a research background in human-AI interaction and workplace technology adoption.
How We Work
Standards we hold ourselves to
These aren't aspirational statements. They're practices embedded in how we scope, build, and hand over every piece of work.
Data Privacy Compliance
All client data handling follows Hong Kong's Personal Data (Privacy) Ordinance (PDPO). We work within your existing data governance policies and document every access point.
Clear Project Agreements
Every project begins with a written scope document outlining deliverables, timelines, and data handling responsibilities. No ambiguity at the start means fewer surprises later.
Iterative Review Process
Clients review and provide feedback at each project milestone. We incorporate feedback before proceeding to the next phase — not after the project is already delivered.
Comprehensive Documentation
Every deliverable includes clear documentation written for the people who will use it, not just the people who built it. Technical details are available separately on request.
Ethical AI Principles
We embed considerations of fairness and transparency into our technical work — not just as a checkbox, but as a design criterion discussed openly with clients throughout the project.
Continuing Professional Development
Our team participates in ongoing training in machine learning, data ethics, and sector-specific AI applications to ensure our advice reflects current best practice.
Our Values
Thoughtform is built on candour, care, and craft
Candour means telling clients when an AI approach is the right fit and when it isn't. It means writing reports that acknowledge limitations alongside results, and it means scoping projects realistically rather than optimistically. Organisations in Hong Kong operate in competitive and regulated environments. They deserve honest advice more than enthusiastic pitches.
Care means attending to the people side of technology adoption. Tools that staff don't understand, don't trust, or don't find helpful tend not to be used — regardless of how technically sound they are. Our AI Literacy Program and our commitment to plain documentation exist because we believe adoption succeeds when people feel prepared, not pressured.
Craft means doing the technical work well. Clean data pipelines. Appropriate model selection. Outputs that are interpretable and maintainable. We take pride in building things that continue to work after we've left the room.
Curious about what we'd recommend for your situation?
A short call is usually enough to point you in the right direction — even if that direction doesn't involve us.
Get in Touch