Two years ago, I watched someone I love struggle through grief alone. Not because they didn't have people around them — they did. But because grief...
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I think the world needs more projects like this. Could be a good idea to expand it into an app that links to your biometrics (smart watch), if it sees you're stressed, just gives you a notification with some thoughtful advice (Just breathe, it'll be okay, I'm here, you'll make it through this, we can talk about it later). Or could expand further into the AI-companion side, for old age homes. My grandmother had Alzheimer's and for the longest time, it was a struggle to find the time to be there for her daily, for my mother. If she had 'someone to talk to', and can help explain her confusion to her in a kind, gentle manner, not clinical "you have stage 2 alzheimer's, you simply dont remember, because the brain pathways...", a simple "I know you're confused, but it's alright, your name is xyz, you are here, in your room at zyx, my name is abc, I'm here to help you, what exactly is confusing for you, maybe I can help?" with a knowledgebase it builds up over time on the person, so it can both help the person and in her case, report back to the doctors on her reaction to medication and to the nurses on her current state of mind. That way it'd be both a nice to have and something truly useful to those who are left forgotten (or atleast feel that way).
But that's a whole different ball-game. The mobile interface app that links to a smart watch for vitals tracking for notifications though is something I believe can help alot of people with anxiety. They often just need a bit of comfort and if they grow an attachment to their companion (in a non-creepy way), then that notification brings them the calm they need to push through it.
Your grandma's story really touched me. Thank you for sharing it.
You're absolutely right — there are two important dimensions here:
SOULCHAT was built with the second one in mind — especially for people who are lonely, grieving, or simply don't have someone to talk to in their daily lives. What you described — someone to sit with your grandma, talk about shared memories, and gently help her remember the good times — is exactly why I started this.
The first dimension is important too. We're thinking about how to integrate health data in the future (heart rate, stress detection, etc.) so that the companion can respond more contextually. But for now, I want to focus on getting the companionship and memory part right.
Your story gave me a lot to think about. If you're open to it, I'd love to stay in touch — would be great to hear your thoughts as this evolves. You can DM me here
Sure thing, something I'd say would give alot of insight into the potential of it, is Big Hero 6. Yes, that's a kids movie with a nanny bot, but in principle, it's the same concept, taking care of people, by assessing the situation. For biometrics, LLMs tend to be smart enough to understand the context of it, just create an api for it and anomaly events, eg. heart rate suddenly spikes, it sends the data to the LLM to interpret, should be a good starting point and very minimal effort to integrate?
Big Hero 6 — that's actually a great parallel. Baymax was never about replacing human care, just being there when no one else could be. That's the same line I'm holding with SOULCHAT.
And you're right about the API approach — LLMs are already good at interpreting context. The challenge isn't the tech, it's the design: how do we make sure alerts feel like care, not noise? How do we keep the tone warm, not clinical?
This is genuinely helpful. I'm going to think more about the biometrics integration as a lightweight layer rather than a full rebuild.
Thanks for pushing my thinking on this. I'll keep you posted as it evolves.
Essentially, biometrics are just a db and mcp calls. It adds context, not overrides, so it's a pretty easy hook with some open standard apis. The tone, etc. you have 2 options, either you can use a system instruction, or you can use a LoRA is you own the model and the runtime. Though imo, stick to system instruction and skills files, that way you dont dilute it's intelligence.
Hello Glad to see you, I am Kane Lim from Hong Kong. I have over 10 years of development experience. I am writing this because your post was interesting.
The architecture is compelling, especially the combination of persistent memory, persona consistency, and proactive orchestration. I would strengthen it with a dedicated safety middleware layer that evaluates every interaction before generation and after generation.
For memory, I would use semantic retrieval with recency weighting, confidence scores, explicit consent metadata, encryption key rotation, and selective forgetting. For persona stability, contradiction detection and automated behavioral evaluation could continuously measure drift.
I would also reconsider the end to end encryption terminology around PBKDF2 and Fernet. If the server can access plaintext memory, it is application level encryption rather than true end to end encryption.
The project has serious engineering potential. I would be happy to exchange ideas around the memory and safety architecture.
Kane, thank you for this — truly appreciate the depth of your review. 🙏
Honestly, most of my energy right now is going into making the product feel more human — getting the memory right, making the conversations warmer, building something that actually feels like a companion rather than a tool. The encryption layer is something I haven't dug deep into yet — your suggestions are incredibly helpful and give me a clear direction to explore.
I'd really love to stay in touch and exchange ideas as this evolves. Would you be open to connecting? You can reach me at [17621119762@163.com] — I'd be happy to continue the conversation there or here on DEV.
Looking forward to learning from you.
I am glad to hear that my reply was of some help.
I would like to get to know you better. Would you please contact me? You can find contact information in my Bio.
On a technical note though, I'd suggest for memory data, keep it in PostGreSQL, they upgraded ALOT and there's even vector search now, so it's blazing fast for LLM knowledge bases. For the encryption, just remember you need encryption in transit and encryption at rest. AES + PostGreSQL would give you a hardware accelerated stack that keeps it safe E2E without degrading performance, while being scalable to millions of users.
Great technical insights — thank you for taking the time to share this. 🙏
On PostgreSQL + vector search: you're absolutely right, it's a solid choice and the hardware-accelerated encryption aspect is compelling. I'm currently using sentence-transformers with a different backend, but I'll definitely look into PG's vector capabilities — especially if it can simplify the stack while scaling better. Appreciate the tip.
On encryption: agreed on both in-transit and at-rest. I'm using PBKDF2 + Fernet currently. AES + PG is an interesting thought — I'll run some benchmarks.
your writing skills are amazing
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Thanks for reading! I'll be writing more technical deep dives on memory, identity, and encryption in the coming weeks. If you have questions or ideas, I'd love to hear them. 🧡