Nimbus vs Tability

Tability is an OKR and strategy platform that has spent 2026 turning a plan hierarchy into a queryable graph. The Strategy Map now organises by people as well as plans, the Dependencies Map traverses up to parent context and down through downstream work from any object, and a workspace-wide filtering layer with saved segments sits over goals and initiatives. Running alongside is an agent track: an AI Importer that reads OKR and KPI spreadsheets into reviewable proposals, and AI managers that can be assigned to a goal and must route decisions back through an approval flow.

The two tracks are converging, and the sequencing tells the story. Delegating goals to AI agents shipped first; the releases since have been building the structure those agents need to reason over — who reports to whom, what depends on what, which slice of a busy workspace a question is actually about. Overflow controls on large maps and a refreshed Initiatives view point at customers with enough plans and people for readability to become the constraint, which is a different buyer than the small-team OKR tool this category started as. Import friction is being attacked from the same direction: an AI-assisted path out of spreadsheets, with review gates before anything is created.

Expect the agent features to start consuming the graph the recent releases exposed — dependency-aware and reporting-line-aware agent actions rather than per-goal delegation — and the scheduled-prompt mechanism behind executive summaries to widen into other recurring outputs.