AI

Built-in AI for every OKR cycle.

Drafting OKRs, summarizing check-ins, forecasting where you'll land, surfacing the risks that don't show up in dashboards. AI woven into every cycle — not a separate chat tab.

Free for 1–5 users Your data never trains models Turn AI off anytime
In this section

Four AI capabilities, built into the workflow

Why most AI features fall flat

“AI-powered” isn't the same as actually useful.

Most OKR platforms have shipped AI in the last 18 months. Most of it is generic summarization. Three patterns we see:

1

Generic summaries nobody reads

An AI that paraphrases your check-ins into a 200-word paragraph nobody asked for. No recommendations, no risks flagged, no concrete next action. The summary lands in a Slack channel and dies there.

2

AI living in a separate chat tab

Open the OKR tool. Switch to the AI tab. Paste context. Get a response. Copy it back to the OKR view. Five steps to get one suggestion. The AI is technically there — the workflow isn't.

3

Static reports for dynamic problems

The weekly AI digest tells you what happened last week. You needed the warning about what was going to slip, two weeks ago. By the time AI surfaces the issue, you've already missed it.

Feature 1 of 4 · Highest leverage

OKR Analysis

Every objective gets a live AI analysis: where you are, where you'll land, what to do this week, what to do next. Names attached to action items. Concrete next steps, not vague suggestions.

Generated from your real check-in data, your real velocity, and your real KR structure. This is what AI for OKRs should look like — not a 200-word summary, but a specific plan.

  • Projected finish based on actual velocity, not linear extrapolation
  • Action items with owner names — this week and the next two weeks
  • Connected insights across the OKR — spots interactions between KRs
  • Updates as new check-ins land — always reflects the latest data
OKR Analysis: AI-generated objective insight with action items
OKR Analysis: projected finish, action items with owners, connected insights
Feature 2 of 4

AI Coach

Drafts objectives from a one-line brief. Refines vague KRs into measurable targets. Catches the classic mistakes — output KRs disguised as outcomes, KRs with no measurable target, objectives without enough KRs to constrain them.

Works inline in the OKR editor, not in a separate chat. Suggest, accept, edit, ship.

  • Draft an OKR from a one-line description of the goal
  • Refine vague KRs — “improve onboarding” → measurable target
  • Catches structural issues: output KRs, missing targets, unbounded objectives
  • Suggests check-in language when you can't articulate the status
  • Works inline — no separate chat tab
AI Coach: inline OKR drafting and refinement
AI Coach: drafts and refines OKRs inline in the editor
Feature 3 of 4

At-Risk predictions

Every KR gets continuously evaluated for risk. Not at the end of the cycle, not in the weekly digest — live, as new check-ins land. The OKRs that are heading off track get flagged before they miss, with the reason why.

Velocity-based forecast, not linear extrapolation. A KR at 50% with three weeks left isn't the same as a KR at 50% with three weeks left where momentum has stalled — and the forecast knows the difference.

  • Continuous evaluation — not a weekly snapshot
  • Predicted finish based on actual velocity, not linear math
  • At-risk detection before the KR misses
  • Cause hypothesis: stagnant velocity, missed check-ins, blocker patterns
  • Recommended interventions per risk type
At-Risk predictions: KRs flagged before they slip
At-Risk: KRs flagged before they slip, ranked by impact
Feature 4 of 4

AI Insights across the org

Patterns across teams, cycles, and KRs that no single person could spot. Teams that consistently overcommit. Owners who never miss but always finish exactly on target (sandbagging). KRs that look unrelated but always move together.

Updated continuously, surfaced in the Insights view, and delivered as a weekly digest to admins.

  • Cross-team pattern detection — overcommit, sandbag, watermelon
  • KR interaction analysis — spot KRs that move together (or against each other)
  • Cycle-over-cycle health regression detection
  • Weekly digest for admins — the patterns you should know about
AI Insights: patterns across teams and cycles
AI Insights: patterns across teams and cycles, weekly digest
Unique to OKRs Tool

Your OKRs in your inbox, every morning.

A 90-second read that tells you what changed overnight, what's newly at risk, and what to act on today — before you open Slack.

The Daily Briefing

Every weekday morning, leaders get an AI-generated briefing in their inbox. The state of every company OKR. What changed since yesterday. The KRs that crossed into at-risk overnight. The owners who haven't checked in this week. The two or three things to act on today.

No more “I'll catch up on OKRs Friday.” The briefing brings the org status to you — before the day's decisions start landing.

  • Delivered to your inbox every weekday
  • What changed overnight — KR movements, status flips, new check-ins
  • Newly at-risk KRs with cause and owner
  • The 2–3 specific things to act on today
  • Customizable per role — admins, exec team, department leads get different views
Daily Briefing: AI-generated morning email with OKR status and action items
Daily Briefing: AI-generated morning email with what to act on today
Customer story

It's really quick to set up. The interface is clean and easy to use, and the AI suggestions actually helped us write clearer OKRs without overthinking them.

M
Martina
Cloud Phoenix · 4/5 via G2
Frequently asked

AI questions, answered.

Four questions buyers ask before turning on AI features.

Does the AI hallucinate or make up data?
The AI works exclusively from your real OKR data — check-ins, KR values, owners, dates. It doesn't invent numbers. If a KR has no check-in history, the analysis says so explicitly. If velocity is too low to forecast confidently, the forecast says “insufficient data” rather than guessing. The biggest risk — hallucinated numbers in a projected finish — is structurally prevented because the projection is computed from the actual data, not generated by the model.
Can I turn AI features off for compliance reasons?
Yes — at the workspace level, the org level, or per-feature. Disable AI Coach but keep At-Risk. Disable everything for one team while enabling it for another. We log every AI call so admins can audit usage during compliance reviews.
Is my data used to train your AI models?
No. Your OKR data is never used to train any model — ours or our model providers'. We use Anthropic's Claude under their zero-data-retention API tier. No training, no fine-tuning, no sharing with other customers. EU-hosted on AWS Ireland.
Which AI model do you use?
Anthropic's Claude family, accessed via API. We use Claude Sonnet for the main reasoning tasks (OKR Analysis, AI Coach) and Claude Haiku for high-volume real-time tasks (insights, suggestions, risk flagging). We update model versions as new ones ship — AI quality only goes up, never down. Read more about our differentiators.
Related sections

AI is one of five sections.

Each is included on every plan. Click any to see the views inside.