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Laya
AI command centre - Turn tool overload into one calm feed
Laya intercepts events from your dev tools, researches context with AI agents, and surfaces ready-to-approve Action Cards. By the time you open a notification, the answer is already staged. Local-first, open source, and it learns from your corrections.
I built Laya because I was drowning. Not in work -- in notifications about work.
Every morning I'd open Slack to find a wall of unread messages. Then Jira with a stack of ticket updates. Gmail with threads about the same issues. Bitbucket with PRs related to those tickets. The worst part wasn't the volume -- it was the fragmentation. The same bug existed as a Jira ticket, a Slack thread (called something completely different), a PR on Bitbucket (named after the technical fix), and an email thread asking about the timeline.
I'd spent my morning just building context before I could make a single decision.
So I built Laya. The core idea is simple: by the time you look at a notification, the research should already be done. Laya intercepts events from your tools, links related items across platforms using semantic matching, routes them through specialized AI personas, and presents you with Action Cards -- approve or dismiss, one decision, back to work.
A few things I'm particularly proud of:
- It's truly local-first. Your data stays on your machine. SQLite for structured data, ChromaDB for vector search, OS keychain for API keys. The only external calls are to your chosen LLM provider. - It learns from you. When you correct a classification (wrong priority, wrong persona), Laya extracts generalizable rules and applies them to future events automatically. - Context Association actually works. "BUG-1234" in Jira gets automatically linked to the Slack thread where your teammate called it "the payment thing" and the PR titled "fix: null check in payment handler." Three layers: explicit cross-references, semantic similarity, and LLM verification.
It's open source and free. I'd love your feedback -- especially on what integrations and features would make this useful for your workflow.
“AI command centre - Turn tool overload into one calm feed”
Laya was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #151 on the daily leaderboard. Laya intercepts events from your dev tools, researches context with AI agents, and surfaces ready-to-approve Action Cards. By the time you open a notification, the answer is already staged. Local-first, open source, and it learns from your corrections.
On the analytics side, Laya competes within Task Management, Open Source, GitHub and Side Project — topics that collectively have 199.2k followers on Product Hunt. The dashboard above tracks how Laya performed against the three products that launched closest to it on the same day.
Who hunted Laya?
Laya was hunted by Aayush Chawla. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Laya including community comment highlights and product details, visit the product overview.
Aayush Chawla
Hey Product Hunt! I'm Aayush, the maker of Laya.
I built Laya because I was drowning. Not in work -- in notifications about work.
Every morning I'd open Slack to find a wall of unread messages. Then Jira with a stack of ticket updates. Gmail with threads about the same issues. Bitbucket with PRs related to those tickets. The worst part wasn't the volume -- it was the fragmentation. The same bug existed as a Jira ticket, a Slack thread (called something completely different), a PR on Bitbucket (named after the technical fix), and an email thread asking about the timeline.
I'd spent my morning just building context before I could make a single decision.
So I built Laya. The core idea is simple: by the time you look at a notification, the research should already be done. Laya intercepts events from your tools, links related items across platforms using semantic matching, routes them through specialized AI personas, and presents you with Action Cards -- approve or dismiss, one decision, back to work.
A few things I'm particularly proud of:
- It's truly local-first. Your data stays on your machine. SQLite for structured data, ChromaDB for vector search, OS keychain for API keys. The only external calls are to your chosen LLM provider.
- It learns from you. When you correct a classification (wrong priority, wrong persona), Laya extracts generalizable rules and applies them to future events automatically.
- Context Association actually works. "BUG-1234" in Jira gets automatically linked to the Slack thread where your teammate called it "the payment thing" and the PR titled "fix: null check in payment handler." Three layers: explicit cross-references, semantic similarity, and LLM verification.
It's open source and free. I'd love your feedback -- especially on what integrations and features would make this useful for your workflow.
GitHub: https://github.com/aayushch/laya