Milestone raises $10M to maximize the ROI of generative AI coding for enterprises šŸŽ‰
Introducing Milestone Insights

Your engineering
data finally tells you
what to do next

Milestone Insights turns AI spend, adoption, quality, flow, and agent activity into prioritized findings with evidence and recommended action.

Book a demo See sample Insights
Built for CTOs VPs of Engineering Engineering Ops AI Transformation
Milestone Insights overview
Live
AI adoption
0%
Spend mapped
0%
Active
13
Active insights
Agent code merging without human review milestone/agent_runtime
High adoption with high review rework Team Atlas
Adoption ready to scale on Team Nova Team Nova
Critical GenAI ROI
Premium model spend rising faster than output
9 evidence Suggested action
Warning Flow
AI pull requests waiting longer for review
6 evidence Suggested action
Opportunity
Unused model budget ready to reallocate on Team Nova
One intelligence layer across AI ROI Spend Adoption Quality Flow Agent governance
The problem

AI changed the work. Now
leaders need a new signal layer.

Dashboards show activity. Milestone Insights shows meaning. See where AI creates value, where it creates risk, and what action should happen next.

Raw signals the noise

Everything happening across engineering and AI.

AI usage session 4821
Pull request #2207 merged
Code review 3 comments
Spend premium model
Model reasoning tier
Repo milestone/payments_core
Team Atlas
Agent Runtime task
MCP tool call
Session 38 min
Story CHK-204
Ticket OPS-91
Epic Checkout AI
Board sprint 24
Communication channel update
AI usage session 4821
Pull request #2207 merged
Code review 3 comments
Spend premium model
Model reasoning tier
Repo milestone/payments_core
Team Atlas
Agent Runtime task
MCP tool call
Session 38 min
Story CHK-204
Ticket OPS-91
Epic Checkout AI
Board sprint 24
Communication channel update
Milestone core
Milestone
AI Insights Engine
Connects signals. Scores change. Surfaces the next action.
Answers for leadership resolved

Every question answered with evidence.

What changed? trend
Why does it matter? impact
Who is affected? 3 teams
What evidence proves it? 8 sources
What should we do next? action
The Insight pipeline

From signal to outcome

Signal
Evidence
Milestone
Insight
Action
Outcome
Anatomy of an Insight

Every Insight turns data into action

1
Severity
Know what needs attention first.
2
Plain language finding
No analyst required to read it.
3
Observed versus baseline
See the size of the change.
4
Suggested action
Move from diagnosis to response.
5
Evidence
Grounded in real data.
6
Share
Send it to the right owner.
Warning GenAI ROI Team Atlas

Premium model spend increased without output gain

What is happening

Premium model usage rose 38 percent while merged pull requests stayed flat.

Observed
0%
premium share
Baseline
0%
org median
Effect size
0x
above median
Suggested action

Shift routine tasks to standard models. Reserve premium models for complex work.

Evidence Atlas API Atlas Web Atlas Automation
Critical Insight in action

Catch the risk before
it reaches production

The moment agent activity drifts outside your controls, Insights flags it, proves it with
evidence, and tells you how to close the gap.

Critical Agent Governance milestone/agent_runtime
first seen 75d

Agentic code is merging without human review

Observed
0%
unreviewed
Baseline
0%
org median
Effect size
0x
above median
Suggested action

Require at least one human review before merge with a branch protection rule on milestone/agent_runtime.

Metric UNREVIEWED_MERGED_PR_PCT
Unreviewed merges Last 90 days
0% of merges shipped with no human review
Evidence by repositorymerged PRs
milestone/agent_runtime96 of 102
milestone/workflow_cache104 of 108
milestone/gtm_context97 of 100
Org median7%
Detected automatically by Milestone Insights
Insight categories

Insights across the full AI engineering system

Opportunity

AI ROI

See where AI spend converts into output, and where it does not.

spendworkvalue
Spend mapped to teams
Warning

AI Spend

Catch premium model drift and tool portfolio waste.

modelstoolsdrift
Cost per merged pull request
Adoption

Adoption

Spot teams with low, unhealthy, or plateaued usage.

3 teams1 under target
AI assisted pull request rate
Warning

Quality

Detect AI rework, review churn, and fragile output.

reviewrework
Post review rework
Critical

Flow

Surface stalled pull requests and review bottlenecks.

openstalledmerged
AI pull request cycle time
Critical

Agent Governance

Find agent code paths missing human review.

agentreview gatehuman
Unreviewed agentic merges
Opportunity

Proficiency

Tell effective AI use from rework creation.

effectiverework
Review depth on AI code
Opportunity

Readiness

See where the org is ready to scale AI.

pilotscaleorg
Premium model share
Before and after

Less reporting. More operating.

Before Insights
MilestoneWith Insights
Metrics everywhere Prioritized findings
Manual interpretation Plain language explanation
Late detection Early detection
No clear owner Owner ready sharing
Hard to prove impact Evidence attached
Spend based on estimates Spend and impact connected
Proven ROI, delivered across your workflow
Slack Email Your tools

See your first Insights in a live walkthrough

Bring your stack. We will surface real findings on your teams, spend, and agents.

Use cases

The decisions Insights makes visible

Control AI spend before it becomes budget noise

Catch cost per merged pull request rising above baseline early.

Cost per merged pull request+41%
baseline

Scale AI adoption where it actually improves output

Compare high adoption with low rework against high adoption with high rework.

Team Novalow rework
Team Atlashigh rework

Govern agentic development without slowing innovation

Surface agent generated code that needs human review.

Criticalmilestone/agent_runtime
0unreviewed agentic merges this week

Improve quality as AI contribution grows

Track AI pull request rework against human pull requests.

AI pull requestsHuman pull requests

Clear the review bottleneck slowing AI delivery

See where AI pull requests wait far longer to merge than human pull requests.

AI pull requests92 hrs avg
Human pull requests16 hrs avg
0xlonger to merge on milestone/payments_core

Tell effective AI use from expensive AI use

Find groups at full AI adoption whose code still reworks heavily after review.

Developer Group Platform AI
AI adoption100%
Post review rework58%
Adoption is not effectiveness.
Executive workflow

Built for weekly leadership reviews and daily engineering action

Step 01

Review the active Insight queue

Spend rising faster than output
Review queue aging
Adoption ready to scale
Step 02

Open the evidence behind the finding

Atlas APIAtlas WebAutomation
Step 03

Share with the right owner

Sent to Platform AI
channel update and review note
Owner assigned
Step 04

Track whether the action improved the metric

Premium model shareresolved
See it on your data

Ready to see what your AI engineering data is trying to tell you?

Milestone Insights helps engineering leaders act faster, spend smarter, govern agents, and scale AI with confidence.

Book a demo See sample Insights
Live in days, not quarters Connects to your existing stack No dashboards to build
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