Mend AI
A security tool that inventories every AI model, prompt, and dataset a company uses and flags risky or unapproved ones.
An engineering catalog that automatically finds every software service a company runs and uses AI to fill in owners and descriptions.
OpsLevel is an engineering platform, sometimes called an internal developer portal, that tracks every software service a company runs, along with its owner and dependencies. Its Catalog Engine scans source repositories, Kubernetes clusters, CI/CD systems, and cloud accounts to find services automatically, then AI writes plain-language descriptions, flags likely duplicates, and reviews commit history to find a likely owner for each service, notifying that person by email. It includes an MCP (Model Context Protocol) server so AI coding assistants can query the catalog about ownership and architecture. Admins set up integrations once, and the catalog keeps itself current without manual entry.
This fits a larger engineering organization with enough services, usually dozens or more across several teams, that manually tracking ownership and documentation has become unreliable. A practical starting point is running the automated discovery scan against existing repositories and cloud accounts to see how much of the catalog it builds without manual entry. OpsLevel prices per developer and does not publish list pricing, so treat any quote as a starting point for negotiation; its Standard plan caps at 50 users, so a growing organization should ask about Enterprise pricing early. The main limitation is that AI-generated descriptions and ownership suggestions still need a human check, since commit history does not always show who currently owns a service.
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: Based on 1 production deployment. This is a planning allowance, not verified product pricing. 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 OpsLevel 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.
A security tool that inventories every AI model, prompt, and dataset a company uses and flags risky or unapproved ones.
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