Product / UX / UI & API

Maple AI

End-to-end encrypted, private AI chat assistant. Conversations are encrypted on the user's device and processed inside hardware-isolated Trusted Execution Environments (AWS Nitro Enclaves + Nvidia GPU TEEs) so that even the operator cannot read user data, with remote attestation that users can verify against open source builds. Maple is the flagship app built on the open OpenSecret confidential-computing platform (same team), serves a menu of open-weight models, and ships as web, iOS, Android, and desktop apps. The differentiator is cryptographically verifiable privacy rather than a policy promise.

Maple client is MIT-licensed; the underlying OpenSecret platform is AGPL-3.0 - both fully open so anyone can rebuild and compare hashes against the live attestation. Launched Jan 2025. Serves open-weight models (gpt-oss-120b, kimi-k2.5, deepseek-r1, llama-3.3-70b, qwen3-vl, gemma-3). The consumer offering at trymaple.ai is a paid hosted service - openness applies to the code/architecture, not free unlimited usage.

Openness

5 medium confidence

5.0

license: MIT(Maple-client)+AGPL-3.0(OpenSecret-platform),both-OSI
source: public(github.com/OpenSecretCloud)
models: open-weight
hosted-tier: paid(managed-enclaves)

Both halves of the stack are open under standard OSI licenses (Maple client MIT, OpenSecret platform AGPL-3.0) and the served models are open-weight - unusually clean for a "private AI" product. Scored open_source because the privacy guarantee is only credible because the code is open and attestable. A defensible alternative is open_core, since the delivered offering is a paid hosted service over managed enclaves.

https://github.com/OpenSecretCloud/Maple recorded 2026-06-17
MIT-licensed Maple client (Tauri/Rust/TS), active; multi-platform
https://github.com/OpenSecretCloud/opensecret recorded 2026-06-17
AGPL-3.0 OpenSecret platform; AWS Nitro enclave / TEE confidential-computing architecture

Adoption

3 low confidence

3.0

Launched Jan 2025; vendor reports "5x user growth in the last six months", >90% month-over-month paid retention, and "billions of tokens" in year one, but no absolute user count is published. Self-reported figures only, hence low confidence.

https://blog.trymaple.ai/one-year-of-private-ai-how-maple-ai-made-encryption-easy/ recorded 2026-06-17
launch date (Jan 2025); 5x growth, >90% retention, billions of tokens processed

Capability

4 medium confidence

4.0

Broad multi-model, multi-platform private chat with vision, API, and teams. Short of top because it is a focused private-chat product without a confirmed agentic tool-use/web-browsing ecosystem.

https://blog.trymaple.ai/maple-ai-model-guide-with-example-prompts/ recorded 2026-06-17
model lineup (open-weight) and tier/feature structure

Unchanged since 2026-06-17 (last edited, not re-checked)