What is Layr?

Layr turns everything your product team knows into a clear answer on what to build next — backed by the evidence behind it.

It connects the tools you already use, builds a continuously updated picture of your product reality, and helps you decide what to build and why.

The problem

Most product teams don't fail for lack of data. They fail because their data is everywhere and means nothing in isolation.

• Customer pain lives in support threads and Intercom conversations.
• Feature requests are buried in Slack channels.
• Engineering context is scattered across Jira or Linear tickets.
• Product specs and research notes sit in Notion — disconnected from live signal.
• Last quarter's decisions live only in someone's memory.

One or two people are expected to hold all of that together, synthesize it continuously, and walk into every planning meeting with a confident, defensible answer on what to build next. The tools they use were never designed for that question.

What Layr is

Layr is a product decision engine. It sits between the raw signals your team generates every day and the decisions you need to make about what to build.

The mental model is simple:

signals → understanding → decision → spec → execution

Layr closes the loop — from a customer complaint in a Slack thread, to a curated opportunity with evidence, to an Ask Layr answer you can cite in a meeting, to an execution-ready spec, to an optional ticket or doc in Jira, Linear, or Notion — using context that is actually yours.

How it works

For a surface-by-surface tour of the app, see How teams use Layr.

Why evidence matters

Layr's defining feature is that recommendations are traceable. It doesn't just surface a plausible-sounding answer — it shows the sources behind it, and it remembers context across time.

• It knows a problem has been around for months, not days.
• It remembers a decision you made and why, and can flag when the world has changed since. "You deprioritized export in March; export signals have tripled since then."
• Every piece of memory carries where it came from, how many sources corroborate it, and whether a human has confirmed it.

Auditable evidence is what makes recommendations trustworthy — and what makes specs credible enough for engineering to execute.

Who it's for

Layr is built for product teams of roughly two to twenty people — small enough that the PM is still the glue between tools, large enough that context is already fragmenting.

What Layr is not

• Not a feedback repository. Passive storage without synthesis is a solved problem — and not the bottleneck.
• Not a dashboard. More charts of the same disconnected data don't help you decide what to build.
• Not a blank-page spec generator. The value is the connected evidence that makes a spec credible.
• Not a replacement for Slack, Jira, Notion, or Linear. It's a thin, powerful layer on top that makes the context those tools hold actually useful for product decisions.
• Not an autonomous agent writing tickets while you sleep. Reads are continuous; writes require explicit human intent.

Trust and control

Layr is designed for teams that cannot paste customer conversations into random AI chat windows.

• Workspace isolation — customer data does not cross tenant boundaries in normal product use.
• Least-privilege OAuth — Layr requests only what each workflow needs.
• Opt-in sources — connecting a tool does not ingest everything inside it.
• Human gates — review promotion, spec approval, and write-back are intentional actions.

Security reviewers should start with Data and privacy and Permissions and access.

Next steps