Memories.ai LVMM 2.0 / Project LUCI
https://memories.ai/blog/collaboration-with-qualcomm
Developer-first reference platform for AI wearables. LVMM 2.0 captures visual data through video, encodes it into frames on-device, and stores moments as searchable memories; companion app surfaces past conversations/decisions/experiences. Hardware-level security via Qualcomm partnership; cloud sync for enterprise tiers.
At a glance
- Type
- On-device Large Visual Memory Model for wearables
- Tier
- T2
- Section
- Voice-first / wearable AI memory
- Created
- 2024 (Memories.ai founded); 2025-07 LVMM 1.0; 2026-01 (CES) Project LUCI + LVMM 2.0
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS (proprietary model)
- GitHub
- not applicable — no GitHub repo (closed model)
- Pricing
- searched not found
- Funding
- $16M total ($8M seed Jul 2025 + $8M extension); Susa Ventures led; Samsung Next + Fusion Fund + Crane + Seedcamp + Creator Ventures
Taxonomy
- storage
- vector
- retrieval
- similarity
- persistence
- long-term
- update
- append-only
- unit
- episode
- governance
- user-controllable
- conflict
- none
When to use
Optimised for: on-device visual memory encoding for wearables; episodic recall of past conversations/decisions/experiences; privacy via local processing
Anti-fit: not for cloud-only / non-wearable contexts; not for text-only memory (visual focus); not for users requiring open model weights or auditable consolidation
Pros & cons
Pros
On-device visual encoding addresses cloud-bandwidth/privacy concerns of Humane AI Pin / Rabbit R1; Qualcomm + Nvidia Metropolis partnerships; ex-Meta-Ray-Ban founders bring direct wearable AI experience.
Cons
Closed model (no LVMM benchmarks public); pricing/SDK terms undisclosed; reference-platform model relies on third-party hardware partners shipping; LVMM 2.0 Qualcomm rollout ""later this year"" (2026) — not yet shipping at scale.
Claims & capabilities
World's first Large Visual Memory Model (vendor positioning); on-device inference on Qualcomm processors; Nvidia GTC collaboration uses Cosmos-Reason 2 + Metropolis
Technical surface
- API surface
- Developer SDK (positioned ""like Nexus phones"" for Android-style ecosystem)
- Backend storage
- Qualcomm SoC + on-device storage + cloud sync
- Deployment
- Hybrid (on-device LVMM 2.0 + cloud companion)
- Embedding model
- proprietary LVMM 2.0 visual encoder (no separate text embedder cited)
- Multi-tenancy
- per-user device
- MCP
- searched not found
- A2A
- searched not found
- OpenTelemetry
- searched not found
Similar systems
Other voice-first / wearable ai memory in the catalog, ranked by inbound references.
- Bee T1
Small wearable (pendant / clip / bracelet). Continuous capture; converts speech to text immediately; never stores raw audio . Daily summaries, personal fact sheet, to-do suggestions. Cloud processing on derived text only.
- Era Computer T5
Software platform / OS layer for AI wearables (glasses, rings, pendants, speakers) that abstracts hardware from AI orchestration. Memory and model providers are pluggable and user-controlled rather than cloud-locked; supports 130+ LLMs from 14+ providers. Founded 2025 by ex-Humane team.
- Friend T1
Pendant necklace (~2 inches). Always-on listening feeds a persistent AI companion persona. Companionship-framed rather than productivity / recall. Cloud LLM backend; no detailed encryption claims.
- Granola T1
Mac/iOS app (no hardware). Captures meeting audio via system-audio tap (no bot joining); generates notes from your shorthand + audio. Local audio processing claim; cloud for summaries. Enterprise tier opts out of model training.
- Limitless T1
Continuously captures screen + audio + wearable input; AI search across the timeline. Privacy-first (local-first storage). Originated as Rewind macOS app; pivoted to wearable + lifelog product.
- Omi T1
Wearable orb (necklace or clip) with open-source hardware + firmware. Continuous audio capture; real-time GPT-4o transcription; searchable memory graph. Supports app screen capture too. Hybrid privacy: cloud by default (SOC 2/HIPAA/AES-256), full local/self-hosted available under MIT.