Story

Hey HN!

My co-founder and I have been building Logical, a proactive desktop AI copilot that watches what you're doing (locally), understands the context of your workflow, and surfaces helpful actions before you prompt it.

- Quick demo: https://www.loom.com/share/090a065315934aa7b36a7676f9394d1f

- Try Logical: https://trylogical.ai/signup

Logical lives on your desktop, infers what you're trying to do across apps – email, meetings, documents, PDFs, terminals – and:

- Gives you a reply suggestion when you hit "Reply" on an email thread

- Offers to "Check schedule" when you open a message asking for a quick chat

- Automatically extracts to-dos during calls and from pretty much anywhere on your screen (and reminds you to follow-up)

- Suggests a formula in Excel as you work that you can apply with one click

- Explains terms of research papers as you highlight them

No prompting. No switching context. No copying text around.

* Why we built this *

Despite big progress in LLMs, the dominant UX is still: User does work –> realizes AI could help –> stops –> writes a prompt.

But your computer already has the context of what you're doing. It knows what window you're in, what text you're reading, which script just errored, and what meeting you're sitting in. We wanted an AI that uses this ambient context to proactively assist – more like a real teammate than a chatbot.

* Privacy and data handling (something we deeply care about) *

Right now:

- We offer a technical guarantee that no user data ever touches Logical servers.

- Context is sanitized locally (our local pipeline strips PII / sensitive text before anything is sent off).

Long-term, we aim to move everything on-device as small language models and consumer AI chips mature.

We've seen interest from founders, researchers, engineers, and privacy-sensitive users who want AI benefits without cloud exposure.

* What's under the hood *

- A context engine that digests signals and user data from apps (both local, and if you choose, cloud-based services).

- A sanitization pipeline that removes identifiable or sensitive details before model usage.

- A local vector store + lightweight knowledge graph for immediate retrieval.

- An intent engine that infers "what you're trying to do" in real time and surfaces actions at the right moment.

* What's next *

- Windows support. Logical is currently Mac only.

- Letting developers plug into the context engine and intent engine to offer richer experiences on their apps. At least until desktop MCP is good enough.

- Fine-tuned integrations with more apps and workflows.

Would love your feedback:

If you're interested in: proactive AI; OS-level context awareness; on-device AI; privacy-preserving AI; building AI that actually reduces friction instead of adding more prompts

Happy to chat in the comments! hello@trylogical.ai is always open for feedback.