Jellyfish connects engineering work to business outcomes: resource allocation, software capitalization and AI impact for R&D and finance leaders. 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: · Jellyfish details from its public website
The short answer
Choose Axify if…
your main question is “Is AI making us faster, and what does it cost?” Axify tracks usage, adoption and cost from tools such as GitHub Copilot, Cursor and Claude Code, down to the model and the developer, forecasts your AI spend, and ties it all to cycle time and DORA metrics. Pricing is public, you can start a free trial on your own, only active contributors are billed, and Enterprise includes hands-on rollout support.
Choose Jellyfish if…
finance and leadership need investment reporting: effort by initiative, capacity planning and audit-ready software capitalization, with developer experience surveys in the same platform.
What they share: AI adoption, impact and cost tracking with a spend forecast, DORA metrics, GitHub, GitLab, Bitbucket, Azure DevOps and Jira integrations, no access to source code, and an MCP server so you can ask questions about your data from Claude.
Feature by feature, based on Jellyfish’s public pages and our own product.
| Capability | Axify | Jellyfish |
|---|---|---|
| Focus | ||
| Core focus |
AI usage, cost and impact on delivery |
Engineering investment and business alignment, with AI impact and DevFinOps |
| AI | ||
| AI spend by tool, model, team and developer |
Gross cost and tokens, such as GitHub Copilot, Cursor, Claude Code, LiteLLM |
By tool and team, with model named in its messaging; per-developer view not listed |
| AI spend forecast |
Up to 12 months ahead |
Projected spend and run rate |
| AI adoption insights |
Adoption score built on reflexive use, reliance and trust |
Adoption across tools such as Copilot, Cursor, Claude Code, Windsurf and review agents |
| AI impact on delivery |
AI usage tied to cycle time and DORA metrics |
Usage and spend tied to throughput, quality and delivery speed |
| Delivery | ||
| DORA metrics |
Included |
Yes |
| Value stream mapping (end-to-end) |
Included |
Life cycle and workflow analysis; value stream mapping not listed by name |
| Resource allocation and capitalization |
Not offered |
Effort by initiative and product line, audit-ready software capitalization (DevFinOps) |
| Developer surveys |
Not offered (system data only) |
Yes, validated DevEx surveys and a DevEx Index |
| Reporting and alerts | ||
| Alerts |
Email and Slack, custom alert preferences |
Slack and email alerts on team goals |
| Scheduled email reports |
Custom reports by email, with an AI-written executive summary |
Not listed |
| Platform | ||
| MCP server |
Yes |
Yes (open source) |
| Git providers |
GitHub, GitLab (cloud and self-managed), Bitbucket (cloud and Data Center), Azure DevOps |
GitHub, GitLab (SaaS and self-managed), Bitbucket, Azure DevOps |
| Issue trackers |
Jira Cloud, Azure DevOps, GitLab; Jira Data Center through custom integration (Enterprise) |
Jira (Cloud and Data Center), Linear, 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 1 Type 2, SOC 2 Type 2, CSA STAR Level 1, GDPR, CCPA; hosted on AWS |
| Access to your code and prompts |
None. Read-only, metadata only |
No source code access required |
| Enterprise | ||
| SSO and audit log |
Yes (Enterprise) |
SSO and SCIM; audit logging mentioned on its trust portal |
| Connector for self-hosted tools |
Proxy Agent (Enterprise) |
Jellyfish Agent, runs on-premises |
| 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 |
Embedded services |
“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. Jellyfish starts from the business: where engineering effort goes, how it maps to initiatives and budgets, and how R&D costs are capitalized, with AI impact as one of its modules.
Bottom line: pick the tool whose starting question matches the one your leadership is asking.
Both tools now track AI token spend and forecast it. Axify shows gross cost and token use by tool, model, team, project and developer. Jellyfish describes spend by tool and team, with run rate and projected spend; a per-developer view is not described on its public pages.
Bottom line: if you need to see which developers and models drive the AI bill, Axify shows it directly.
Axify relies only on system data from the tools your teams already use: no surveys, no manual entry. Jellyfish combines system data with validated developer experience surveys and a DevEx Index.
Bottom line: want zero survey fatigue? Axify. Want developer sentiment in the same tool? Jellyfish.
Jellyfish is built for finance as much as engineering: resource allocation by initiative, capacity planning and audit-ready software capitalization backed by a SOC 1 Type 2 report. Axify does not do capitalization; it focuses on delivery flow, DORA, value stream mapping and the effect of AI on them.
Bottom line: need R&D capitalization for your auditors? Jellyfish. Need to know if AI speeds up delivery? Axify.
Axify publishes its price, $29 per active contributor per month on Pro, and you can start a 14-day trial on your own. Axify Enterprise adds implementation services, a dedicated customer success manager with 24/7 support, custom integration development and single-tenant encryption. Jellyfish prices by seats and modules on quote only, and lists embedded services; custom integration development and single-tenant encryption are not listed.
Bottom line: want to know the cost before talking to sales, or need an integration with an internal tool? Axify.
Axify publishes its prices. Jellyfish prices by number of seats and modules, on quote.
| Terms | Axify Pro | Jellyfish |
|---|---|---|
| Terms | ||
| Price per developer / month | $29, billed annually | Not published (quote) |
| What is included | Full platform: AI adoption and cost, delivery and DORA metrics, value stream mapping, Axify Intelligence | Modules sold separately: AI Impact, Developer Productivity, DevFinOps |
| Who is billed | Active contributors only (commit, PR or ticket moved in the last 30 days) | Seats, as defined in your quote |
| Minimum seats | None | Not listed |
| How to start | 14-day free trial, no card | Talk to sales or request a quote |
How to read this
Axify Pro is $29 per active contributor per month, billed annually. Jellyfish does not publish prices, so ask for a quote with the same team size and modules to compare like for like.
Axify Enterprise and Jellyfish are both priced on request for large deployments, with volume discounts.
Axify is a better fit if you…
Jellyfish 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 Jellyfish during your evaluation without changing any workflow.
Everything you need to know about how Axify and Jellyfish compare.
Sources: Jellyfish information comes from jellyfish.co (pricing, platform, integrations, trust center and blog), reviewed November 2, 2026. Axify information reflects our product as of the same date. Jellyfish is a trademark of its owner. Spotted something out of date? Tell us and we will fix it.