Know what needs your attention
before it becomes a problem.
TeamEye brings together GitLab, Jira, Sentry, HR tools and availability signals into one AI-powered management view, helping engineering leaders spot delivery risks, workload pressure, reliability issues and organizational bottlenecks early.
No code analysis · No employee surveillance · No hidden monitoring.
Every visible teammate can see exactly what their manager sees.
Engineering teams rarely fail
without warning.
Burnout does not happen overnight.
It builds over weeks of sustained pressure, weekend work and invisible overload — none of which shows up in retrospectives.
A delivery bottleneck does not appear overnight.
Review throughput slows, MR queue grows, cycle time lengthens. By the time it surfaces in a retrospective, the sprint has already slipped.
Collaboration breakdowns do not happen overnight.
Silos form gradually. Workload concentrates on a few people. The team starts shipping slower without anyone naming the reason.
The signals appear weeks before the problem becomes obvious. Managers simply do not have enough time to catch them manually — across 10, 20 or 30 engineers.
By the time a problem becomes visible in a meeting, it has usually been building for weeks in the data.
No manager can track operational patterns across an entire engineering team on top of everything else they are responsible for.
That is not a management failure. That is a tooling problem.
From activity to understanding.
GitLab shows what happened. TeamEye explains what it means and whether it needs your attention.
What GitLab gives you
A raw log of what happened. Who pushed, when, how many lines changed. Accurate, but without context or interpretation. You still have to figure out what it means.
What TeamEye gives you
An AI-generated management briefing that explains engineering activity patterns, flags emerging risks and tells you exactly what to do about it — delivered every morning before you open your inbox.
What managers actually receive.
Every morning. Real signals. Plain language. No dashboards to open.
Sara has shown a sustained overload pattern for 5 consecutive days. Recent activity resembles deadline pressure — output is 3.8× her personal baseline with weekend pushes in the last two weeks.
Alex's output dropped 42% vs his personal baseline this week. MR reviews fell from 11 → 3. No leave registered, no public holidays. The drop is sudden and inconsistent with his usual cadence.
The team shows uneven workload distribution. Three contributors carry most of the delivery effort while collaboration metrics continue declining across the rest of the team.
Why disconnected engineering tools are not enough.
GitLab explains engineering activity. Jira explains delivery flow. Sentry explains reliability pressure. Leave systems explain availability. TeamEye connects all of them into one operational picture for engineering leaders.
GitLab
- Shows commits
- Shows merge requests
- Shows reviews
- Shows pipelines
- Shows repositories
TeamEye
- Detects workload pressure
- Detects delivery risk
- Detects collaboration breakdowns
- Detects reliability pressure
- Detects availability conflicts
- Generates management guidance
- Produces actionable recommendations
GitLab explains software delivery. Use it to understand your codebase.
TeamEye explains engineering operations. Use it to understand what is happening across your engineering organization.
The daily AI management briefing.
Every day TeamEye generates a concise management briefing — areas requiring management attention, workload concerns, collaboration issues, engineering activity changes, operational anomalies and recommended manager actions. Instead of reading hundreds of events, you get a 30-second summary.
What needs attention today?
Stop checking dashboards. Know where manager attention is needed.
Sara Jensen carries two critical flags: sustained overload (9 of 14 days, 4.2× median) and weekend push pattern consistent with deadline stress. Immediate 1:1 recommended.
Alex Kim shows a rhythm break — output dropped 42% vs personal baseline. MR reviews fell 11 → 3. Worth a direct conversation. The remaining 5 are steady.
Understand team health without surveillance.
TeamEye is built to help managers support their teams — not to monitor, judge or score engineers. That principle shapes every design decision.
- Record screens
- Track keystrokes
- Monitor webcams
- Measure mouse movement
- Inspect private conversations
- Read or store code
- Read work patterns
- Detect collaboration signals
- Surface operational risk signals
- Generate manager guidance
- Show every engineer their own data
- Enable informed conversations
The goal is not to monitor employees. The goal is to help managers support them.
Why engineering leaders invest in TeamEye.
For teams where losing one engineer costs more than a year of this tool.
Eliminate management blind spots
Understand what is happening between standups, before it surfaces in a resignation or a missed sprint.
Catch overload before it becomes burnout
Identify sustained pressure patterns early, when a conversation still works — not after someone has already decided to leave.
Have better conversations with your team
Go into every 1:1 informed, not guessing. Focus your time where it has the most impact — not spread thin across everyone equally.
Scale your leadership capacity
Maintain full visibility across growing teams without spending hours inside GitLab or waiting for problems to surface in retrospectives.
Organizational intelligence, flat pricing.
Simple pricing based on engineering team size. Every plan includes GitLab, Jira, Sentry and leave-system integrations, daily AI briefings, operational risk detection and management intelligence dashboards.
- Daily AI management briefing
- GitLab integration
- Jira integration
- Sentry integration
- Leave-awareness engine
- Operational risk detection
- Everything in Starter
- Historical trend analysis
- Team intelligence reports
- Delivery risk monitoring
- Reliability pressure insights
- AI management advisor
- Everything in Professional
- Multi-team visibility
- Executive dashboards
- Organization-wide reporting
- Cross-team risk detection
- Priority onboarding
- Everything in Organization plan
- SSO
- Custom data retention
- Dedicated success manager
- Enterprise onboarding
- Custom integrations
Card details later · cancel anytime
Questions engineering leaders ask.
TeamEye helps engineering leaders understand operational health, delivery risk and team dynamics using the systems their organization already uses.
What will I actually learn about my engineering organization?
You'll learn where management attention is needed.
TeamEye combines GitLab activity, Jira delivery flow, Sentry reliability signals and leave context into one operational picture. Instead of manually checking multiple tools, leaders get a daily briefing that highlights delivery risk, review bottlenecks, workload imbalance, reliability pressure and unusual changes in team operating patterns.
How is this different from just looking at GitLab reports?
GitLab shows you what happened. TeamEye explains what it might mean.
A commit count tells you nothing on its own. TeamEye combines historical engineering patterns, review flow, delivery activity and organizational context to explain what changed and whether it deserves attention.
What kinds of situations can TeamEye help me detect?
The operational risks leaders tell us they missed before using TeamEye:
Delivery bottlenecks. Review flow breakdowns. Sustained workload imbalance. Rising production pressure. Sprint execution issues. Missing engineering capacity caused by leave. Cross-team dependency risks.
None of these are visible until they've already compounded. TeamEye flags them early.
Why do engineering leaders actually use this?
Because engineering information is fragmented.
GitLab explains activity.
Jira explains delivery.
Sentry explains reliability.
Leave systems explain availability.
Most leaders spend time stitching those signals together manually.
TeamEye does that work automatically and delivers a concise daily briefing.
Does TeamEye tell me what action to take?
Yes. Every risk signal includes a suggested intervention — not a vague "pay attention to this person", but something concrete: schedule a 1:1, ask if they're blocked, check whether the workload is distributed fairly, or simply validate your assumptions before the next sprint.
You always decide what to do. TeamEye makes sure you have the context to decide well.
Does TeamEye invent anything, or does it work from real data?
Everything you see is grounded in your team's actual activity. TeamEye never generates signals, invents patterns, or fills gaps with assumptions. If a person has no activity in a window, we say so — we don't guess.
What we do is interpret what's already there. Your systems produce operational data every day just by being used — commits, reviews, merge requests, tickets, error rates, leave. That data already contains signals about delivery risk, workload pressure, and collaboration health. TeamEye reads those signals and translates them into plain language an engineering leader can act on.
The AI writes the narrative, but the evidence behind every sentence is your own data. You can always drill down and see exactly what triggered a detection.
What data does TeamEye actually access?
Only read-only operational metadata required to build management insights.
No screen recording.
No laptop agents.
No IDE monitoring.
No private messages.
No source code analysis.
TeamEye reads operational signals from connected systems and never modifies data.
Can TeamEye replace my 1:1s and team conversations?
No — and it's not designed to. TeamEye is designed to make your conversations better, not to eliminate them. It tells you who might need a check-in and why, so that when you do sit down with someone, you're not going in blind. You're going in informed.
The goal is fewer surprises, not fewer conversations.
Operational visibility for engineering organizations.
TeamEye connects engineering activity, delivery flow, reliability signals and availability context into one management view, helping leaders notice risks before they become costly problems.