LinearB helps teams automate the pull request workflow. Axify shows whether your AI coding tools are paying off, by connecting AI usage and cost to delivery metrics. Here is how they compare, and where each one fits best.
Last updated: · Based on public information from both vendors
The short answer
Choose Axify if…
your main question is “Is AI making us faster, and what does it cost?” Axify brings usage, adoption and cost from tools such as GitHub Copilot, Cursor and Claude Code into one view, and ties them to cycle time and DORA metrics. You also get every major Git provider at the entry price, billing on active contributors only, and hands-on rollout support on Enterprise.
Choose LinearB if…
you want to act inside the pull request workflow: AI code review, policy-as-code automation and developer surveys, with ISO 27001 and R&D cost capitalization already in place.
What they share: DORA metrics, cycle time, Git and Jira integrations, and an MCP server so you can ask questions about your data from Claude, ChatGPT or Cursor.
Feature by feature, as each vendor describes it publicly.
| Capability | Axify | LinearB |
|---|---|---|
| Focus | ||
| Core focus |
AI usage, cost and impact on delivery |
Workflow automation and AI code review on top of engineering metrics |
| AI | ||
| AI spend by tool, model, team and developer |
Such as GitHub Copilot, Cursor, Claude Code, LiteLLM |
Not listed |
| AI spend forecast |
Up to 12 months ahead |
Not listed |
| AI adoption insights |
Adoption score built on reflexive use, reliance and trust |
AI impact dashboard (AI vs human code delivery) |
| Delivery | ||
| DORA metrics |
Included |
Yes |
| Value stream mapping (end-to-end) |
Included |
Not listed |
| Workflow and finance automation |
Not offered (read-only by design) |
AI code review, gitStream PR automation, R&D cost capitalization (Enterprise) |
| Developer surveys |
Not offered (system data only) |
Yes, including Slack |
| Reporting and alerts | ||
| Alerts |
Email and Slack, custom alert preferences |
Slack and Teams notifications, custom alert preferences |
| Scheduled email reports |
Custom reports by email, with an AI-written executive summary |
Scheduled reports, monthly to yearly |
| Platform | ||
| MCP server |
Yes |
Yes |
| Git providers |
GitHub, GitLab (cloud and self-managed), Bitbucket (cloud and Data Center), Azure DevOps |
GitHub and GitLab (cloud and on-prem), Bitbucket Cloud, Azure DevOps |
| Issue trackers |
Jira Cloud, Azure DevOps, GitLab |
Jira (cloud and on-prem), Azure Boards |
| Security and compliance |
SOC 2 Type II, hosted in Canada (AWS), encryption in transit and at rest, privacy officer for Law 25 and GDPR |
SOC 2 Type II, SOC 1 Type II, ISO 27001, GDPR |
| Access to your code and prompts |
None. Read-only, metadata only |
Reads pull request content for AI code review and automation |
| Enterprise | ||
| SSO and audit log |
Yes (Enterprise) |
Yes |
| Connector for self-hosted tools |
Proxy Agent (Enterprise) |
On-prem agent (Enterprise) |
| Single-tenant data encryption |
Yes (Enterprise) |
Not listed |
| Custom integration development |
Yes (Enterprise) |
Not listed |
| Implementation services |
Included in Enterprise, with a dedicated CSM and 24/7 support |
Premium onboarding on Enterprise, services sold ad hoc |
“Not listed” means the feature does not appear on the vendor’s public pricing or product pages as of the update date. It may exist or be on its way.
Feature lists look alike. These are the places where the two tools make different bets.
Axify starts from AI: who uses which assistant, what it costs, and whether delivery actually got faster. LinearB starts from the workflow: its message is that visibility is not enough, so it automates reviews and enforces pull request policies.
Bottom line: pick the tool whose starting question matches the one your leadership is asking.
Axify shows gross cost and token use by tool, model, team, project and developer, with a spend forecast up to a year ahead. LinearB measures AI impact on code delivery; per-tool AI spend tracking is not listed on its public pages.
Bottom line: if finance is asking about the AI bill, Axify answers that directly.
Axify relies only on system data from the tools your teams already use: no surveys, no manual entry. LinearB combines system metrics with developer surveys, now sent through Slack, which helps if you want to track sentiment alongside delivery.
Bottom line: want zero survey fatigue? Axify. Want developer sentiment in the same tool? LinearB.
Axify is read-only and never reads your code, prompts or conversations. LinearB writes into the workflow: AI code review, auto-approval of safe changes and reviewer routing through gitStream. That is a real strength if review is your bottleneck.
Bottom line: measurement with minimal access, or automation with deeper access.
Axify Enterprise includes implementation services, white-glove onboarding and a dedicated customer success manager with 24/7 support. If a tool you rely on is not supported, Axify builds the integration for you. Data is encrypted per customer with single-tenant encryption. LinearB offers premium onboarding to Enterprise customers and sells implementation services on an ad hoc basis; custom integration development is not listed.
Bottom line: rolling out across many teams, or running internal tools? Axify brings the people and the integrations with the platform.
List prices in USD, per developer per month, billed annually: the model both vendors use.
| Same baseline | Axify Pro | LinearB Essentials | LinearB Enterprise |
|---|---|---|---|
| Terms | |||
| Price per developer / month | $29 | $29 | $59 |
| Who is billed | Active contributors only (commit, PR or ticket moved in the last 30 days) | Every user assigned to a team | Every user assigned to a team |
| Minimum seats | None | 50 | 100 |
| Git providers covered | GitHub, GitLab, Bitbucket, Azure DevOps | GitHub Cloud only | All supported providers |
| Usage-based extras | None. MCP access includes a token quota | AI credits beyond 1,000 per user per month | AI credits beyond 1,500 per user per month |
| Free trial | 14 days, no card | 45 days, no card | 45 days, no card |
| Annual cost at LinearB's seat minimums | |||
| 50 developersLinearB Essentials minimum | $17,400 | $17,400 (GitHub Cloud only) | $70,800 (100-seat minimum) |
| 100 developersLinearB Enterprise minimum | $34,800 | $34,800 (GitHub Cloud only) | $70,800 |
How to read this
Not on GitHub Cloud? Then LinearB Essentials is not an option, and LinearB Enterprise starts at $70,800 a year. For the same team on GitLab, Bitbucket or Azure DevOps, Axify Pro costs $17,400 at 50 developers (about 4x less) and $34,800 at 100 developers (about half). Axify also bills only people active in the last 30 days, so occasional contributors cost nothing, and it has no seat minimum. Prices exclude taxes, volume discounts and extra AI credits.
Axify Enterprise and large LinearB deployments are both priced on request, with volume discounts.
Axify is a better fit if you…
LinearB is a better fit if you…
From DORA metrics and value stream work with Axify.
Axify connects read-only to the Git, issue tracking and AI tools you already use, so you can run it next to LinearB during your evaluation without changing any workflow.
Everything you need to know about how Axify and LinearB compare.
Sources: LinearB information comes from linearb.io (pricing, product pages and blog), reviewed October 30, 2026. Axify information comes from axify.io (pricing, security and product pages). LinearB is a trademark of its owner. Spotted something out of date? Tell us and we will fix it.