AI Performance Review Software
AI performance reviews grounded in real work
Windmill turns scattered work context, Slack conversations, peer feedback, and manager notes into review drafts your team can trust.
Manager review draft
Avery Chen - Q2 performance review
Built from GitHub activity, Linear projects, Slack feedback, 1:1 notes, and peer review responses.
- Shipped the billing migration two weeks early.
- Unblocked onboarding with clearer API examples.
- Mentored two engineers through their first production launches.
- Delegate operational follow-up sooner.
- Document architectural decisions before implementation starts.
Peer feedback is unusually consistent on cross-functional communication. Rating gap flagged for manager review.
Reviews drafted from real work
Windmill pulls context from Slack, GitHub, Linear, Jira, Salesforce, and past check-ins so managers are not starting from a blank page.
Managers stay in control
AI prepares the first draft. Managers verify facts, add judgment, and publish feedback in their own voice.
Cycles close faster
Self-reviews, peer feedback, manager drafts, and calibration pre-reads are prepared before review week becomes a scramble.
Why it matters
Performance reviews fail when managers have to reconstruct the past
Review prep is manual
Managers dig through old docs, tickets, Slack threads, and memory to reconstruct months of work.
Feedback arrives too late
Traditional review cycles capture stale examples and miss the small moments that explain how work actually happened.
Peer selection is noisy
People nominate whoever they remember, not always the people who collaborated most closely during the cycle.
Calibration lacks context
Leaders spend calibration meetings trying to read thin writeups instead of discussing the real tradeoffs.
A review cycle that is already prepared
AI review drafts
Generate self, peer, upward, and manager review drafts from work evidence, feedback, and role context.
Continuous evidence
Capture accomplishments and collaboration signals throughout the cycle instead of relying on end-of-cycle memory.
Smarter calibration
Surface rating gaps, thin reviews, missing evidence, and manager notes before the calibration meeting starts.
Workflow
From work signals to finished reviews
- 1
Connect the work systems your team already uses
Windmill syncs work context from communication, project, code, and CRM tools so review evidence builds in the background.
- 2
Collect employee and peer input conversationally
Windy asks targeted follow-up questions in Slack, turning lightweight conversations into structured review inputs.
- 3
Generate drafts managers can edit
Managers receive specific, evidence-backed drafts with wins, development areas, and examples they can verify and personalize.
- 4
Calibrate with the right context
Leaders get pre-reads and exception flags so calibration focuses on fairness, not gathering missing data.
AI assistance where review work actually happens
| Capability | Windmill | Manual or form-based tools |
|---|---|---|
| Evidence collection | Continuous context from work tools, Slack conversations, check-ins, and peer feedback. | Manual notes, self-reported accomplishments, and manager memory. |
| Review drafting | AI-generated first drafts that managers verify and edit. | Managers start from a blank form or copy old review language. |
| Peer feedback | Reviewer suggestions based on real collaboration patterns. | Manual nominations based on who people remember. |
| Calibration | Pre-reads, rating gaps, and thin-review flags prepared before the meeting. | Leaders discover missing context during calibration. |
FAQ
Questions teams ask
What is AI performance review software?
AI performance review software helps teams collect review context, request feedback, draft review language, and prepare calibration materials. Windmill focuses on using AI to assist managers while keeping humans responsible for final judgment.
Does Windmill replace managers in performance reviews?
No. Windmill drafts and organizes review context so managers can move faster. Managers still verify facts, add coaching judgment, and own the final review.
Where does Windmill get review context from?
Windmill connects to tools like Slack, GitHub, Linear, Jira, Salesforce, Google Workspace, and other systems where work happens, then combines those signals with self-review and peer feedback conversations.
Can small teams use AI performance review software?
Yes. Windmill is designed for teams that want a lightweight review process without building a heavy HR operating machine. The first 10 users are free.
Run the review cycle without the scramble
See how Windmill prepares self-reviews, peer feedback, manager drafts, and calibration context from the work your team is already doing.