Aggregate signals from project management, communication tools, peer feedback, and manager input into continuous performance insights. Surface patterns human reviewers miss. Make every review cycle faster, fairer, and more actionable—on your infrastructure.
"I have seven direct reports. Review season takes three weeks of my life. And I still feel like I'm making half of it up from memory."
— Engineering Manager, Enterprise Software
Deploy an AI analyst that continuously aggregates performance signals from your existing systems and synthesizes them into comprehensive, explainable review inputs.
Pulls data from project management, code repositories, communication tools, and peer feedback throughout the year. No more "what did they do in Q1?" Memory becomes comprehensive.
Combines quantitative metrics (tickets closed, PRs merged, deals won) with qualitative signals (peer sentiment, collaboration patterns). Surfaces what matters, not just what's easy to count.
Every rating comes with evidence. "Exceeds on delivery" links to specific projects. "Needs development on collaboration" points to concrete patterns. No black boxes.
Jira, Asana, Linear, Monday. Tickets completed, story points, sprint velocity, on-time delivery.
GitHub, GitLab, Bitbucket. PRs merged, code review participation, build quality, documentation.
Slack, Teams. Collaboration patterns, responsiveness, cross-team engagement, knowledge sharing.
360° reviews, project retrospectives, kudos and recognition. Qualitative sentiment aggregated.
Salesforce, HubSpot. Quota attainment, pipeline generation, deal velocity, customer retention.
Lattice, 15Five, Culture Amp. Goal completion, key result progress, alignment scores.
Support tickets, NPS mentions, customer success notes. Direct customer impact signals.
LMS completion, certifications earned, skills development, mentorship activity.
Your engineering managers each have 6-8 direct reports. Review season means three weeks of nights and weekends gathering data.
"Here's the review draft for Sarah Chen: 47 PRs merged (team avg: 32), 4.7 peer rating with themes of 'technical mentorship' and 'reliable delivery.' Collaboration score flagged—cross-team PRs down 40% vs prior quarter. Three specific project highlights attached with links."
Your calibration meetings devolve into debates about perception. Louder managers win ratings for their teams.
"Calibration view for L5 Engineers: Objective metrics normalized across teams. Three employees rated 'Exceeds' have lower delivery scores than two rated 'Meets.' Suggesting recalibration review for consistency. Evidence attached for each."
Employees want feedback more than twice a year. Managers don't have time to provide it continuously.
"Monthly performance pulse for your team: Marcus trending up on delivery velocity (+15%). Jennifer's peer feedback scores declining—two 'communication' flags this month. Suggesting 1:1 focus areas attached for each direct report."
Promotion decisions feel political. High performers don't know what they need to demonstrate. Managers can't articulate gaps.
"Staff Engineer readiness assessment for Sarah Chen: Technical depth—meets bar (evidence: system design docs, architecture reviews). Scope of impact—meets bar. Cross-team influence—gap identified (limited work outside Platform team). Recommended: Lead Q1 infrastructure project with Data team."
Aggregates performance signals throughout the year, not just at review time. Nothing forgotten.
Combines quantitative metrics with qualitative feedback into unified performance view.
Generates review drafts with evidence links. Managers edit and personalize, not write from scratch.
Provides objective baselines for calibration discussions. Flags rating inconsistencies across managers.
Tracks performance trends over time. Early warning on declining signals before they become problems.
Monitors OKR and goal progress. Links objectives to evidence of completion or gap.
Automates peer feedback requests, reminders, and aggregation. No more chasing responses.
Loom Sentinel integration ensures sensitive data is handled appropriately. Configurable privacy controls.
Assesses employees against level requirements. Identifies specific gaps with development recommendations.
A clear charter, defined triggers, and agreed levels of human oversight—structured for enterprise deployment.
Inputs – Project outcomes, peer feedback, manager notes, OKR progress, 1:1 summaries, system metrics, recognition data
Outputs – Review drafts with evidence, calibration reports, promotion readiness assessments, development recommendations
Escalate to HR when: insufficient data for review, potential bias detected, employee disputes evidence, PIP considerations arise
Pay once. Own the asset. Full source code on Google ADK. Deploy, modify, extend.
Reviews, ratings, and feedback are deeply sensitive. Everything stays on your infrastructure.
Security updates, model compatibility, and integration maintenance. You own agents; you subscribe to safety.
Add custom metrics, adjust signal weights, and define your competency model.
Deploy the Performance Review Analyst on your infrastructure. Give managers data. Give employees clarity. Make every review cycle better.
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