Team Decrypton

AnchorCare + Engram Tagline: A memory companion for people living with dementia that only says what a caregiver has approved, and shows its evidence every time. The Problem For someone with dementia, simple questions like “Who’s visiting today?” or “Did I take my medication?” can trigger anxiety and be repeated many times a day. Typical AI assistants aren’t suitable because they can invent information, which creates confusion and distress. The Solution AnchorCare + Engram is an AI companion that never invents memories. Caregivers build a trusted Memory Ledger of approved facts, routines, medications, photos and family information. Nothing becomes visible to the patient without approval, and every change is fully audited. Patients use a simple Companion that answers questions using only approved records. Answers are generated with Meta Llama 4 and always cite the memory records behind them. If there’s no evidence, the Companion says so rather than guessing. When a patient needs help, one tap sends an SOS. Through Twilio, it rings a caregiver’s real phone, wherever they are. Key Features ✅ Caregiver-approved memory records ✅ Evidence-backed AI answers with citations ✅ Medication and routine reminders ✅ Familiar-face recall from approved photos ✅ SOS alerts plus real phone calls to caregivers via Twilio ✅ Complete audit trail for every memory update Real-World Use Cases Who is this? Help the patient recall family and friends from approved photos. Reassurance on repeat. Give the same calm, accurate answer every time a question is asked. Medication support. Timed reminders, with patient responses reviewed by caregivers. Care-team handoffs. Shared visibility across shifts and caregivers. Remote family involvement. Loved ones contribute memories for approval, and can be called from anywhere. Distress support. One-tap SOS alerts paired devices and phones a caregiver, even in another city. Why Meta Llama? Llama is open-weight, so the same models can run through Meta’s hosted API or on infrastructure a care provider controls. Smaller Llama models can even run on ordinary local hardware with Ollama. This enables: better privacy offline resilience low operating costs future multilingual responses, safety screening and automated care summaries Built With Meta Llama 4 · MongoDB Atlas · Twilio · React + TypeScript · Express What Makes It Different? AnchorCare’s core promise is simple: every answer is backed by caregiver-approved evidence. If the system doesn’t know, it says so. It never invents a memory. Built entirely using synthetic patient data. AnchorCare is a support tool, not a medical device, and does not provide clinical advice.