Introducing Kiboh

Performance management tools were built for compliance departments, not people. They reduce trust to a score, compress a year of work into a single awkward conversation, and treat every employee like a compliance ticket waiting to be closed. I've sat through enough of these to know: the problem isn't that managers don't care. It's that the tools they're given don't let them.

Performance reviews shouldn't feel like a checkbox exercise. Maister and Green's Trust Equation gets it right: trust is a function of credibility, reliability, and intimacy — divided by self-orientation. The best managers already know this intuitively. They build trust by showing up consistently, by knowing their people, and by putting the team's interests ahead of their own. But the tools they're handed optimise for the opposite: infrequent, transactional, and centred on the organisation's need to document rather than the person's need to grow. That gap is why I started building Kiboh.

Three beliefs that shaped the product

Relationships over transactions. Every variable in the Trust Equation grows through repeated, genuine interaction. They shrink when the only touchpoint is a form due every six months. Kiboh is designed around ongoing conversations, not periodic events, because that's how trust actually compounds.

Signals, not scores. A single number can't capture someone's contribution. What matters is the pattern of evidence: feedback, goals, commitments, reflections. Kiboh surfaces those signals so managers can make grounded judgments instead of guessing.

AI as copilot, never autopilot. AI is powerful enough to draft a review, flag potential bias, and suggest what to discuss in a 1:1. It is not wise enough to replace human judgment. Every AI feature in Kiboh is designed to augment the person using it, not to make decisions for them.

What you can do in Kiboh today

Kiboh isn't a roadmap slide. The features below are live and working in our beta.

Conversational 1:1s are the backbone of the product. Each 1:1 is a long-lived conversation with persistent topics — career growth, wellbeing, performance, projects — and tracked commitments that carry forward across meetings. Before each session, an AI-generated agenda surfaces what matters most with clear rationale. During the meeting, a live conversation mode keeps both parties focused with a shared real-time highlights feed. Afterward, post-session reflections capture tone, takeaways, and follow-ups. These aren't meeting notes. They're the connective tissue between a manager and their team.

AI-Enhanced Reviews ground evaluations in evidence, not recency bias. When a review cycle opens, Kiboh's AI drafts narratives drawn from the full body of evidence accumulated during the cycle — feedback, goal progress, 1:1 notes, achievements. A built-in bias detection layer flags language patterns that could undermine fairness. Managers review, refine, and make it theirs. The AI assists; the human decides.

Goals and OKRs support OKR, KPI, and simple goal types at every level — company, team, and individual. Goals cascade visually so alignment is obvious, not assumed. Each goal carries a confidence score from 0 to 100, giving leaders an honest read on progress instead of green-yellow-red theatre.

Performance Signal Index (PSI) is a composite score built from evidence density, review quality, peer feedback, and rubric coverage. It replaces gut-feel assessments with a transparent, auditable signal that HR and managers can use during calibration.

Continuous Feedback makes it easy to give appreciation, constructive, and general feedback at any time. It supports anonymous options, feedback requests to peers or cross-functional partners, and AI-powered summarization that turns scattered signals into clear patterns. Feedback flows directly into reviews as supporting evidence — nothing gets lost.

Analytics give leaders department-level dashboards, trend tracking, and performance distributions without spreadsheet gymnastics. You see the full picture because the data was captured continuously, not reconstructed from memory at year-end.

The AI layer

Every AI feature in Kiboh follows the same principle: augment judgment, never replace it.

The review drafter synthesizes evidence into a starting narrative so managers spend their time refining, not staring at a blank page. The fairness auditor scans review text for bias patterns — gendered language, halo effects, recency bias — and flags them before submission. The calibration copilot surfaces outliers, PSI distributions, and narrative readiness across teams so HR can facilitate fair, data-informed calibration sessions. The agenda assistant analyzes open topics, overdue commitments, and recent feedback to suggest a prioritized 1:1 agenda before each meeting.

These tools exist because managers are busy, not because they're incapable. The goal is to free up cognitive space for the conversations that actually matter.

Who this is for

Kiboh is for managers and teams who believe performance management should be fair, transparent, and actually useful. If you've ever spent hours writing reviews that felt disconnected from the work that happened, or sat through 1:1s that were just document dumps instead of real conversations, you'll understand the frustration that led to this product.

We built Kiboh with international teams in mind from day one. The platform ships with full English and Japanese support — not as an afterthought, but as a core part of the product. If your team spans borders, Kiboh speaks your language.

Try Kiboh

Kiboh is now in beta and we're onboarding pilot customers. If this resonates with how you think about managing people, I'd genuinely like to hear from you.

Tell us about your team — we'll take it from there.