Safety-Critical AI · Private client
Safety-Critical AI for a Regulated Practice
Healthcare client, details withheld
Challenge
Assist a professional in real time in a setting where one component of the system is safety-critical and a wrong output can cause harm.
My role
Architecture and build across the assistant, the safety layer and the data-retention model, working under the client's compliance regime.
Evidence
Engagement in progress. Further detail available on request, subject to client approval.
Some products contain one component that is different in kind from everything around it: if it is wrong, someone can be harmed. The engineering question is not how to make that component clever, it is how to make it predictable, explainable and fast, and how to keep everything clever firmly outside it.
The principle I work to is a hard split between a safety layer and a support layer. The safety layer is deterministic, rule-based and auditable, with no language model anywhere in its decision path, because a model is non-deterministic, cannot be explained to a regulator after an incident, adds latency that a real-time path cannot afford, and introduces an injection surface where the input itself could suppress an alert. The support layer, where a wrong answer is an inconvenience rather than a harm, is where a model earns its place, with a human reviewing before anything acts.
The same discipline runs through data handling. In a regulated setting the retention model is a design decision rather than a configuration detail, and infrastructure ownership sits with the client's organisation from day one so that the legal data controller is unambiguous and closing an engagement means revoking access rather than migrating credentials.
This engagement is live and the client's product, architecture and compliance specifics are not mine to publish. I am happy to talk through the approach in a call.
Outcomes
- Safety-critical path built with no LLM dependency, auditable rule by rule
- Deterministic detection fast enough for a real-time window
- Automated test gate blocking release on any safety-path regression
- Retention and data-controller model designed for the client's regime
Stack
Direct Project Enquiry
Tell me what you are building
Share what you are building and where it is stuck. If a managed platform already solves it, I will say so. I review every enquiry personally and reply within about four hours.
- 1Send your project goal and the services you think you need.
- 2I review the context and whether I am the right fit.
- 3You get a direct reply with a practical next step.
International projects welcome
I work in English by email, video call or through Upwork, from GMT+7 with overlap hours for US and EU teams.
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