Intro

A few years ago, I had a surprising performance review. It was surprising because all of the signals I was receiving made me feel like I was doing an a great job. After this review, I took it upon myself to conduct an anonymous 360º survey and found that the results didn’t align with my manager’s review. What was clear was my manager’s point of view had been biased by the feedback of one individual from a recent event – he was missing the full context of my work and contributions.

After that experience, I started to run similar surveys on behalf of my employees. The results helped me quickly identify gaps and areas where I should lean in. Overall I felt prepared to have career discussions because I had the full context. I knew how powerful 360º feedback could be but I also knew how manual and time intensive they were – I couldn't help but wonder how powerful this would be if done continuously in the background with no work required from the employee, their manager, or HR leaders.

Problem

Performance reviews SUCK and the more I dug into the data the more grim it got:

58% of companies say their performance management system is "not an effective use of time"

45% of managers see no value in their current review process

Managers spend an average of 210 hours per year on performance reviews

80% of employees prefer ongoing feedback over traditional annual reviews, yet most organizations still rely on infrequent, formal evaluations

The core problems run deep:

Manual 360 feedback is incredibly time-consuming. Even well-intentioned managers who want to gather comprehensive feedback, just like I did, face a ton of work. They must identify relevant colleagues, craft appropriate survey questions, send individual requests, chase down responses, and then spend hours reading through and synthesizing feedback. This process can take weeks for a single employee.

Recency bias undermines fairness. When managers (or anyone) rely on memory to write reviews, they inevitably focus on recent events while forgetting achievements and challenges from earlier in the year. This creates unfair evaluations that don't reflect the full scope of an employee's performance.

Traditional reviews are too infrequent. Annual or even quarterly reviews mean that valuable feedback arrives too late to be actionable. By the time issues are formally documented, patterns have solidified and opportunities for course correction have passed.

The process lacks context. Managers often evaluate employees based on limited visibility into their day-to-day work, especially with distributed or remote teams where cross-functional collaboration is common but less visible to direct supervisors.

Who is it for?

Candor is designed for mid-sized organizations (250-2,500 employees) that have outgrown basic performance management approaches but aren't ready for the complexity and cost of enterprise solutions.

Specifically:

HR Directors and CHROs who spend too much time administering review cycles instead of focusing on strategic initiatives

People Operations teams looking for ways to reduce administrative burden while improving feedback quality

Managers at all levels who want to provide better feedback but lack the time and tools to gather comprehensive insights

Forward-thinking organizations that see AI as an opportunity to enhance rather than replace human judgment in performance management

Why build it?

As mentioned above, the inspiration came from personal experience but the the "aha moment" came when I realized two things:

The feedback collection process could be completely automated: With access to calendar data, communication patterns, and organizational structure, AI could automatically identify who works with whom and generate contextually appropriate survey questions.

The process could be flipped, like a pulse survey: Instead of waiting for a manager or HR to administer a survey, what if the system asked everyone to provide feedback on a regular basis (weekly or bi-weekly). Then the system could continuously collect insights throughout the year, providing managers with rich context whenever they needed it.

The market timing is perfect:

Performance management software is projected to grow from $5.82 billion in 2024 to $12.17 billion by 2032

AI is identified as the #1 disruptor in HR, with 52% of managers already using AI tools

Companies with continuous feedback systems show 39% higher effectiveness in talent attraction and 44% better retention rates

What is it?

Candor is an AI-powered performance management platform that automatically generates and distributes contextual 360-degree feedback based on actual working relationships. Think of it as having a dedicated performance management assistant that never sleeps, never forgets, and always knows exactly who to ask for relevant feedback.

How it works:

🎯 Contextual Survey Generation – AI creates tailored feedback surveys based on:

The specific relationship between feedback provider and recipient

Job roles and responsibilities of both parties

Frequency and type of interactions

Industry-specific performance criteria

Company values and cultural priorities

⚡ Continuous Background Collection – unlike traditional tools that require manual initiation:

Feedback is collected automatically throughout the year

No action required from managers or HR teams

Context accumulates continuously rather than at artificial review periods

Insights are ready whenever managers (or individuals) need them for career conversations

🧠 AI-Powered Insights & Coaching – Candor goes beyond simple feedback collection:

Tone Analyzer helps users rewrite feedback to be more constructive and appropriate

Feedback Coach summarizes insights, identifies patterns, and suggests development areas

Manager Dashboard provides team-wide insights and coaching recommendations

Interested?

Candor is looking for pilot customers: