Atlassian Rovo Dev
An AI coding agent built into Jira and Bitbucket that plans, writes, and reviews code using ticket and repository context.
A security tool that inventories every AI model, prompt, and dataset a company uses and flags risky or unapproved ones.
Mend AI is a security tool that finds and governs the AI components inside a company. It builds an AI bill of materials, called an AI-BOM, by scanning for AI models, frameworks, and datasets across an organization, including tools developers adopted without formal approval. It scores system prompts for injection risks, runs adversarial red-team tests against conversational AI to check for data leakage and bias, and applies runtime guardrails that check inputs and outputs against policy. It maps its checks to the OWASP Top 10 for large language model applications, the NIST AI Risk Management Framework, and ISO/IEC 42001. It is made by Mend, also known for open-source dependency scanning. Note that the vendor URL in some catalog records is incorrect; confirm details at Mend's own site.
This fits a company rolling out its own AI features, or one where employees adopt outside AI tools without formal review, that needs a way to find and govern that usage. A practical starting point is the AI-BOM discovery scan to see what AI components already exist before writing new policy. Mend has published a price near $300 per contributing developer per year for its AI product line, separate from its broader application security bundle near $1,000 per developer per year; confirm current packaging directly, since AI security offerings are still evolving quickly. The main risk is treating discovery as a one-time project instead of an ongoing scan, since new AI tools and models get adopted continuously.
How one company factor at a time moves the modeled score. The published score is unchanged.
These estimates cover licensing, setup, integrations, staff time, security, administration, and support.
| Cost measure | Low | Base | High |
|---|---|---|---|
| First-year total | $54.4K | $85.5K | $137.2K |
| Three-year total | $118.1K | $177.9K | $274.3K |
| First-year cost per unit | $54.4K | $85.5K | $137.2K |
| Average annual cost per unit (over three years) | $39.4K | $59.3K | $91.4K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $18K | $24K | $32.4K |
| Implementation | $8.4K | $14K | $23.8K |
| Integration | $9.9K | $18K | $32.4K |
| Staff time and change management | $6K | $8.5K | $11.9K |
| Security | $4.6K | $6.5K | $9.8K |
| Administration | $3.4K | $4.5K | $6.1K |
| Support | $1.7K | $2.2K | $3K |
Estimate assumptions: This scenario uses a category-based allowance, not a verified price for this product. Based on 1 production deployment. Confirm the vendor’s billing unit and current price or quote before budgeting.
Benefits have not been estimated: The current research does not estimate potential savings, return on investment, or how long it would take to recover the cost. Earlier benefit estimates are excluded.
Confirm current product identity, commercial packaging, data processing terms, sign-in and access rules, retention, integrations, support model, implementation effort, and rollback conditions.
Verify identity, package, availability, ownership, pricing, and security evidence before approving a pilot
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Define what success looks like for a test of Mend AI and assign someone to lead it.
Once the requirements above are met, compare a small trial with how your team works today.
Track adoption, output quality, business results, and actual costs against the estimate.
Use the results to decide whether to stop, adjust, or expand the pilot.
Confirm encryption, how the vendor uses your data, customer data separation, how long data stays and how to delete it, activity records, sign-in and user setup, where data is handled, other companies that process data, past incidents, and what your team must manage.
Review before rollout: confirm how to export your data, revoke access, and return to your existing workflow. Assign an owner and test the rollback plan before expanding use.
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
An AI coding agent built into Jira and Bitbucket that plans, writes, and reviews code using ticket and repository context.
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Research observations recorded: 1. Evidence quality: Some support.
Recorded score and category rank across research updates.
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