Responsible AI
Personal intelligence should remain personal.
Section Labs builds AI that works on intimate parts of everyday life—your face, your body, your health, your habits. That means privacy, transparency, and user control are engineering requirements, not marketing lines.
Principles
Six commitments we design against.
Every product explains what it collects, why it needs it, and what happens next—before a single photo, message, or measurement is captured.
You can review, export, and delete your images, inputs, and history at any time. Deletion is real deletion, not a hidden flag.
Sensitive inputs are encrypted in transit and at rest, scoped to the specific product, and never sold to advertisers or data brokers.
Our results are informational insights. We label confidence, surface uncertainty, and direct users to qualified professionals when it matters.
Models are evaluated across skin tones, ages, body types, and languages. When a model underperforms for a group, we ship the fix or hold the feature.
A cross-functional review board revisits every product's data flows, prompts, and evaluation results on a regular cadence.
Safeguards
What we actually do, not just what we believe.
Principles matter when they turn into engineering practice. These are the safeguards embedded in every Section Labs product.
Products that touch health, wellness, or the body carry explicit disclaimers, avoid diagnostic language, and route emergencies to appropriate resources.
New models pass documented evaluations for accuracy, bias, safety, and hallucination rate before they reach a single end user.
Reviewers monitor sampled outputs, feedback signals, and edge cases—so problems surface from real usage, not just internal tests.
Each product uses AI only for the task it was built for. We don't quietly reuse your data to train unrelated general-purpose models.
Lifecycle
Responsibility across the full product lifecycle.
Responsible AI isn't a launch checklist. It's a set of decisions made at every stage—from the first sketch to the tenth release.
We define the user, the decision the product supports, and the information it must never ask for.
Data minimization, on-device processing where possible, and least-privilege access are default engineering choices.
Accuracy, bias, robustness, and safety are measured against benchmarks representative of the actual user base.
Products ship with plain-language disclosures, in-app controls, and a visible path to contact a human.
Live signals, user feedback, and periodic audits inform updates, deprecations, and—when needed—rollbacks.
Reporting
See something that doesn't sit right?
If a Section Labs product produced a result that felt biased, unsafe, or misleading, tell us. Reports go directly to our responsible-AI review board.