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  7. Unlock:OKR

Unlock:OKR logo

Unlock:OKR

Not Agent-Ready Yet
Agent-Ready SaaS Index · unlockokr.com · scored 2026-05-10 · rubric v2.0
Score 15 / 100
Objectives And Key Results
Self-serve checkout

Unlock:OKR scores 15/100 on xpay's Agent-Ready Index v2: partial pricing visibility.

See Unlock:OKR pricing summaryLive pricing page
Pricing
Unlock:OKR pricing
As of 2026-05-10 · unlockokr.com/
Billed annually only — no monthly option
Software
Sales
$6/user/mo
billed annually
Individual and Team Performance Dashboards
Automated Product Onboarding
Sustainable User Engagement Drivers
Personalized Implementation Plan
Score breakdown · rubric v2.0
How Unlock:OKR scores on the agent-ready dimensions

Public pricing visibility

13 / 15

Self-serve checkout

0 / 15

Public API + docs

0 / 20

Usage-based / metered pricing

0 / 20

Free entry path

0 / 7

No sales call required

0 / 7

Card / wallet / x402 payment

2 / 6

Machine-readable bonus (MCP / OpenAPI)

0 / 10


Total
15 / 100
Effective pricing
What it actually costs at typical scale
10 employees
$60/mo
· Each employee costs $6 per month (billed annually).· Implementation fee is one‑time and not included in monthly cost.
Confidence: high
100 employees
$600/mo
· Each employee costs $6 per month (billed annually).· Implementation fee is one‑time and not included in monthly cost.
Confidence: high
Agent purchase verdict
Can an autonomous agent transact here?
Sales-gated
LLM score: 20/100

Can create account

No

Can enter payment method

No

Can upgrade plan

No

Can buy more usage

No

Can cancel online

No


Payment methods

invoice

Human approval recommended

Yes

Pricing transparency

full

Purchase motion

sales_led

Demo required

Yes

Quote required

Yes


Annual commit required

Yes

Auto-renewal mentioned

No

Cancellation policy visible

No

Refund policy visible

No

Minimum term

12 months


Invoice payment available

Unknown

Purchase orders supported

Unknown

MSA required

Unknown

DPA available

Unknown

Security review required

Unknown


Competitive intel
Positioning & ecosystem
Headline

“Premium Platform, Not Pricing”

Buyer persona

mid market
enterprise

Integrations mentioned
HubSpot
Slack
Jira
BambooHR
Zenefits
Microsoft Teams
Salesforce
Agent purchase simulation
Six-step check: can an agent actually buy from Unlock:OKR?
✓

Discover price

◐

Select a plan

✗

Pay per task

✓

Avoid a sales call

✗

API docs without auth

✗

Estimate cost upfront

Analysis
Pros and cons for AI agents
Observational summary written by xpay from the signals captured on 2026-05-06. Not a review of the product — only of its current pricing posture for agent buyers.
✓ For an AI agent
  • Pricing is publicly visible on an indexable page — agents can read tiers without scraping past auth.
  • Every advertised tier is self-serve; no tier requires scheduling a call.
◐ Opportunities for the provider
  • No per-unit price was advertised, so an agent has no way to estimate the cost of a single task.
  • API documentation is gated or absent; an agent cannot inspect the integration surface without authentication.
  • PPU requires account creation and an issued API key; a fully unauthenticated agent purchase is not yet supported.
  • No /.well-known/ai-pricing.json or equivalent machine-readable pricing manifest is published — agents must rely on HTML scraping.
One-line fix
How Unlock:OKR could lift its score

Add a per-unit price (e.g. $X / 1K calls) to the pricing page so an agent can compute its own cost before committing.

pricing_visible

true

headline_phrasing

at $6.00.

tier_count

1

lowest_paid_entry_usd

6

free_tier

false

free_tier_terms

null

per_unit_price

null

annual_required

false

self_serve_paid_tiers

1

sales_only_tiers

0

public_api_docs_url

null

api_docs_auth_walled

null

ai_pricing_json_present

false

agents_txt_present

false

anonymous_purchase_path

false

agent_friendly

{"ai_pricing_json":false,"agents_txt":false,"llms_txt":false,"sitemap_xml":true,"mcp_server_card":false,"agent_skills_index":false,"x402_supported":false}

You work at Unlock:OKR?
Claim this scorecard & lift your score.

Get the breakdown of every signal we measured, the one-line fix, and how your peers in Objectives And Key Results stack up.

Evaluating Unlock:OKR?
Compare the agent-ready picks in Objectives And Key Results.

If you're building or running an AI agent that needs to buy from this category, see who's scoring highest right now.

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Are you Unlock:OKR? Something off in this listing?
Agent-Ready Spec
Unlock:OKR
Not Agent-Ready Yet

15

/ 100 (rubric v2.0)

Category

Objectives And Key Results

Pricing model

at $6.00.

Tier count

1

Free tier

No

Lowest paid entry

$6/mo

Self-serve / sales-only tiers

1 / 0


Public API docs

Auth-walled

Anonymous purchase path

No

Machine-readable pricing

Not published


Last refreshed

2026-05-10

Pricing intelligenceInsights extracted from unlockokr.com/
Pricing model

Annual-only tier subscription

Agent-purchase verdict
Sales-gated
20/100 · v2.1
Canonical answer

Unlock:OKR pricing starts at $6/mo per employee, billed annually, with a $1,000 implementation fee; no free plan is listed.

Cheapest entry

Software plan ($6) · sales-led

Actions
Open live pricing page
Verdict reflects Not Agent-Ready Yet status under rubric v2.0. Source observed at https://unlockokr.com/.
Agent-friendly features1 of 7 present
Discovery files and protocols
Side-channel signals — informational, not part of the score. Each protocol is independent; adoption signals the publisher is thinking about agent buyers.

ai-pricing.json

agents.txt

llms.txt

sitemap.xml

MCP Server Card

Agent Skills

x402 / MPP

More in Objectives And Key Results
Compare Unlock:OKR with peers
Highest-scoring companies in the same category that an AI agent might evaluate as an alternative.
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75
gtmhub.com
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Koan
68
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Approaching Agent-Ready
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66
jell.com
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Perdoo
64
perdoo.com
Approaching Agent-Ready
Commonality
63
commonality.co
Approaching Agent-Ready
Talbit
62
talbit.io
Approaching Agent-Ready
Normalyz
62
normalyz.com
Approaching Agent-Ready
GroSum
60
grosum.com
Approaching Agent-Ready
Browse all Objectives And Key Results →

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