Wooly · research agent

Ask questions. Get answers. No dashboards required.

Wooly is Weave’s research agent. Ask any question about your engineering org and get grounded, source-cited answers in seconds.

How does AI-assisted output compare across teams?

Ask

Auto

Last 13 weeks

All repos

Or start from one of these

“Why did cycle time spike last sprint?”

“Which teams have the highest revert rates?”

“What did we spend per shipped feature?”

What the answer is built from

4

48 pull requests

github

112 reviews

github

9,204 agent runs

cursor

$12,480 of spend

billing api

AI-assisted output by team
Normalized units of work per engineer, last 13 weeks, split by authorship.
+38% vs Q3
answered in 4.2s
raw output
AI vs human
by type
by component
by team
by AI tool
by people
backend
frontend
infrastructure
Median
Top 10 %
Top 1 %

Any question about your engineering org, asked in your own words.

Any question about your engineering org, asked in your own words.

Natural language across your entire engineering dataset. No query builder, no dashboard request, no waiting on a data team.

Natural language across your entire engineering dataset. No query builder, no dashboard request, no waiting on a data team.

Median answer

4.2 seconds

Claims with a source link

100%

Dashboards to configure

None

What do you want to know?

Auto

Last 3 months

Normal

Ask your question…

Which engineers are using AI most effectively?

Analyze the strengths and weaknesses of our teams

Where are our deployment cycles getting stuck?

Every answer is grounded in your own records, and cites them.

What do you want to know?

Auto

Last 3 months

Normal

Ask your question…

Which engineers are using AI most effectively?

Analyze the strengths and weaknesses of our teams

Where are our deployment cycles getting stuck?

Q1

“Why did cycle time spike last sprint?”

4.2s

Q2

“Which teams have the highest revert rates?”

2.8s

Q3

“How does AI-assisted output compare across teams?”

6.1s

Q4

“Which AI tool has the best cost-per-merged-PR?”

3.4s

Q5

“What did we spend per shipped feature last quarter?”

5.7s

Four steps between your question and a cited answer.

Four steps between your question and a cited answer.

Wooly does not guess. It resolves the question, pulls the records, separates human from AI work, and keeps a link to every source it used.

Wooly does not guess. It resolves the question, pulls the records, separates human from AI work, and keeps a link to every source it used.

Thinking · 4 sources · verifying data points

4.2s

Comparing AI-assisted output per engineer across four teams over the last thirteen weeks. Normalising by codebase component so a platform change and a mobile change count the same, then checking the result against peer organisations of the same size.

AI-attributed share of shipped output · by week

Step 1 of 4

Parse

Wooly reads the question, resolves the teams and repos it mentions, and picks the time window.

Step 2 of 4

Retrieve

It pulls the underlying records: pull requests, reviews, deploys, agent runs and spend.

Step 3 of 4

Attribute

Human and AI contributions are separated on every record it touches, not estimated after.

Step 4 of 4

Cite

Every number in the answer keeps a link back to the exact record it came from.

Answers grounded in your records, not in general knowledge.

Answers grounded in your records, not in general knowledge.

Context-aware answers

Every answer is grounded in your organization’s own PRs, reviews, deployments, and costs. Not general knowledge — your data.

Source-cited answers

Every claim links back to the underlying records. Click through from any number to the PRs behind it.

Uncover what dashboards miss

Ask cross-cutting questions no fixed dashboard was built to answer, and get an answer in seconds instead of a data request.

One answer · every claim traced

5 of 5

642.12 units shipped

48 pull requests

51% AI-attributed

cursor · agent runs

99th percentile output

peer benchmark

3 reverts on mobile

deploy log

$12,480 of AI spend

billing api

No figure appears in an answer without the record behind it.

The questions a fixed dashboard was never built to answer.

The questions a fixed dashboard was never built to answer.

What a fixed dashboard gives you

Panels chosen months ago

Someone decided which cuts mattered before you had the question.

One metric at a time

No way to join spend against output against review load.

A request queue

A new cut is a ticket, and the ticket takes days.

Numbers without provenance

Trust the tile, or go and rebuild the query yourself.

What Wooly gives you

Any question

Asked in plain words, the moment it occurs to you.

Cross-cutting by default

Spend, output, review depth and revert rate in one answer.

Seconds, not days

Fast enough to ask the follow-up while you are still thinking.

A citation per claim

Click any figure and land on the record it came from.

4.2s

Median time from question to cited answer

100%

of figures carry a link to their record

0

Dashboards to build, request or maintain

Ask from wherever the question came up.

Ask from wherever the question came up.

Wooly answers in the place you were already working, and keeps the answer shareable afterwards.

Wooly answers in the place you were already working, and keeps the answer shareable afterwards.

Slack

Mention Wooly in any channel and the answer lands in thread, cited, for everyone reading.

Your Editor

Ask from inside the repo the question is about, without breaking flow to open a tool.

The CLI

Pipe a question into a script, a scheduled job, or your own internal reporting.

The Workspace

The full Wooly surface, with history, saved answers and shared threads.

Give your teams the data they need to build the products you want.

Trusted by engineering teams from startups to Fortune 500