Google Cloud
Google Vertex AI
Google Cloud's platform for building, training, and running AI models, now being renamed Gemini Enterprise Agent Platform.
A tool for tracking machine learning experiments and for testing, monitoring, and debugging AI apps, with prices published online.
Comet is an AI development platform covering two connected areas. Its MLOps side handles experiment tracking, model versioning, and dataset management for teams building traditional machine learning models. Its Opik product, which has an open-source version, adds tracing, testing, and monitoring for generative AI applications and agents, with more than 60 integrations, over 40 automated evaluation metrics for checking output quality, and a built-in assistant called Ollie that flags recurring errors and suggests fixes. It is made by Comet ML and can run as a fully managed cloud service or be self-hosted. The company states SOC 2, ISO, and HIPAA-related compliance and publishes pricing online: Pro plans start at $19 per user per month, with a free tier for small teams.
This fits a team that wants to see real prices before a sales call, since both its MLOps and Opik products list plan costs on the website. A good starting point is the free tier, which covers a small team and enough usage to test experiment tracking or generative AI monitoring on one real project. Paid Pro plans start at $19 per user per month with defined usage limits, and larger deployments move to custom enterprise pricing with single sign-on and added compliance support; treat these as planning estimates. The main risk is underestimating usage growth once monitoring is added to more applications, since usage-based limits like training hours or trace volume can push a growing team into a higher tier faster than expected.
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 | $81.3K | $128.2K | $206.5K |
| Three-year total | $175.2K | $264.6K | $409.1K |
| First-year cost per unit | $81.3K | $128.2K | $206.5K |
| Average annual cost per unit (over three years) | $58.4K | $88.2K | $136.4K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $27K | $36K | $48.6K |
| Implementation | $13.2K | $22K | $37.4K |
| Integration | $15.4K | $28K | $50.4K |
| Staff time and change management | $8.4K | $12K | $16.8K |
| Security | $6.3K | $9K | $13.5K |
| Administration | $4.9K | $6.5K | $8.8K |
| Support | $2.3K | $3K | $4.1K |
Estimate assumptions: This scenario uses a category-based allowance, not a verified price for this product. Based on 1 production workspace. 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 Comet 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.
Google Cloud
Google Cloud's platform for building, training, and running AI models, now being renamed Gemini Enterprise Agent Platform.
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Why it’s an alternative—
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Research observations recorded: 1. Evidence quality: Some support.
Recorded score and category rank across research updates.
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