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Performance & OKR SaaS

A performance-management platform

Turning a broad, fast-moving product roadmap into governed, reviewable delivery.

An OKR and performance product — check-ins and confidence tracking, 360° review cycles, a KPI library, continuous feedback — needed to build across a wide feature set quickly while keeping quality and consistency high.

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features inventoried automatically
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improvement ideas mined from docs & code
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governed lifecycle stages, each human-approved
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shared source of truth for the whole backlog

The challenge

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A large, cross-cutting feature surface where a small change in one area can ripple into review cycles, feedback and reporting.

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Multiple contributors and AI assistance, with a real risk of inconsistent patterns creeping in.

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A need to plan and size a big backlog credibly, not by gut feel.

What agI3R did

Mapped the product in minutes

The full feature inventory — review cycles, KPIs, feedback, nominations — was captured automatically as a shared, structured backlog.

Sized and ordered the work

Each item was estimated from its own specification and ordered for delivery, with the reasoning shown — commitment stayed a human decision.

Held the line on quality

Every change carried test evidence and an acceptance-criteria review to the gate, so nothing shipped on hope.

Kept conventions consistent

The platform learned the product’s patterns and applied them to new work, so a wide surface stayed coherent.

The governed workflow

Every piece of work moved through the same human-controlled lifecycle — fast where it could be, gated where it mattered.

Ideate

Requirements are drawn out through a guided interview and captured as a testable specification.

Plan

The backlog is sized from those specs and ordered for delivery; a human commits the plan at a gate.

Implement & Iterate

AI-written changes arrive with test and review evidence; humans decide, always.

Release

Shipping is a governed, recorded step — accountable and reversible.

“A broad roadmap became a single governed pipeline — fast where it could be, controlled where it mattered.”

Illustrative case study based on real onboarding patterns. Anonymized; figures are representative, not customer-specific.