SustematiQ works with research data, stakeholder evidence, personal context, and intelligent technology. We design our systems around a simple principle: collect and use only what is genuinely needed, explain what technology is doing, and preserve meaningful control for the people and organisations using it.
Privacy is not only about compliance. It is part of agency, dignity, and control.
Trust principles
The standards we use to think about data and control.
Purpose before collection.
We should be able to explain why information is needed before asking for it.
Collect less where possible.
We aim to minimise personal and stakeholder data rather than collect information simply because technology makes collection possible.
Local processing where it creates meaningful value.
Some SustematiQ products are deliberately designed so sensitive personal context can remain on the user's device.
No shared model training by default.
Personal or stakeholder data should not become training material for shared SustematiQ models by default.
Meaningful choice.
Where processing is optional, the choice should be understandable rather than hidden behind unnecessary complexity.
Visible AI.
When AI materially influences an output or action, its role should be proportionate and appropriately visible.
Human authority remains clear.
Suggestions, drafts, automated actions, and delegated authority should not be confused with one another.
Personalisation is not psychological diagnosis.
Behavioural preferences can improve a product without turning ordinary product activity into unsupported claims about personality or mental health.
AI position
AI is a capability within SustematiQ, not its identity.
AI is a capability within SustematiQ, not its identity. We use AI where it can improve understanding, personalisation, reasoning, or useful action. Its role should remain proportionate, visible, and accountable. We do not claim that AI is inherently unbiased. More automation is not automatically better. The intelligence of the system should increase the intelligence and capability of the stakeholder using it.
Plain language data
What data practices mean in context.
What do we collect? Only information needed for the particular website function, research activity, product, project, or connected service.
Why do we collect it? The purpose should be stated clearly before or when the information is collected.
Where does it go? This depends on the specific product or service. Some functionality may remain local. Other functionality may require SustematiQ infrastructure or an explicitly connected third party service.
Do we train AI on it? Personal and stakeholder data should not be used to train shared SustematiQ models by default.
What about third parties? Where a user or project uses an external service, that provider's infrastructure and data practices also matter.
Mate trust messaging
A stated design commitment for Mate.
This section describes SustematiQ's stated design commitment for Mate, not a description of shipped behaviour. The wording must be checked against actual production behaviour before launch.
SustematiQ's design commitment is local personal intelligence for Mate. Under that commitment, responsibilities, commitments, decisions, preferences, and personal context should remain on the user's computer by default. External services such as email, calendars, Slack, or Teams should be accessed only when the user chooses to connect them. Actions involving external systems should follow visible permission rules. The intended principle is that Mate learns from the user for the user. Personal Mate data should not be used to train shared SustematiQ models by default.
FoQus boundary
A recreational product with a clear learning boundary.
FoQus is a recreational product. It is not a medical device, therapy, diagnosis, or treatment.
FoQus learns preferences, not psychological labels. It may remember preferred duration, mode, visual theme, sound, breathing setting, or commonly skipped guidance. It should not infer anxiety, depression, ADHD, burnout, trauma, personality type, or emotional stability from ordinary product behaviour.
FoQus language: resets, attention objects, preferences, session configuration, optional reflection, carry forward choices, and local behavioural preferences.
Product boundaries
Capability should not be confused with authority.
Mate
Mate does not make decisions on behalf of the user merely because it can recommend something; does not guarantee productivity or decision quality; should not be presented as professional legal, medical, financial, or psychological advice; and external actions require appropriate authority.
Core trust message
Research grounded. Human controlled. Privacy conscious.
SustematiQ designs technology around meaningful human control. We minimise data where possible, explain why information is needed, use AI proportionately, and design personalisation so greater system intelligence strengthens the stakeholder rather than quietly increasing the system's authority.