Co-founder · Product & compliance architecture
Yash leads product and compliance-aware system design at Brandlabs — HIPAA/DPDP sequencing, trust UX for health products, and the operating cadence that turns AI prototypes into production software.
Chunking, redaction, retrieval filters, and eval hooks so regulated AI answers without stuffing patient data into every context window.
Practical notice, purpose limitation, and consent patterns for AI products selling to Indian regulated buyers — without freezing the roadmap.
A decision tree for LLM vendors, subprocessors, and when synthetic data is enough — before anyone pastes real patient data into a prompt.
Shared primitives for regulated AI — access control, logs, minimization — and the jurisdiction-specific deltas US and Indian buyers actually diligence.
What to log for HIPAA-aware LLM systems, what never to log, how long to keep it, and who can open the trail.
FDE, senior engineers, product design, and compliance-as-needed — roles and anti-patterns for shipping regulated AI in 12–20 weeks.
Diligence questions on BAA fluency, eval discipline, and clinical workflow empathy — before you hire a studio to ship your AI product.
Questions CFOs and compliance officers should ask before signing an AI vendor — DPDP, updates, liability, and evidence — not just a demo.
Privacy, language, and stigma-aware product patterns from shipping telehealth for women’s health — so care feels safe enough to start.
Latency, vernacular STT/TTS, and when voice beats chat — lessons from rebuilding Myna Voice AI for rural women’s health support.
A pattern for weekly demos that are evidence, not theatre. What we ship, what we don't, and what we say out loud.
HIPAA and DPDP shouldn't be a last-mile checklist. Here's how we bake them into the first commit.