OpenAI
ChatGPT Enterprise
A workplace AI assistant that helps staff write, research, and analyze data, kept private and never used to train the model.
A workplace AI tool that combines company search, chat, and task-running agents, built to run inside a company's own private cloud.
Cohere North is a workplace AI tool. Employees use it to search company documents and get answers with sources, draft and summarize content, and build tables or charts from data. Through its Agent Studio, teams set up AI agents that carry out multi-step tasks, such as contract review or sales research, with an audit trail of what each agent did. It is made by Cohere, which also sells language models through an API. North can run in a company's own private cloud, and a fully isolated option called Model Vault targets regulated industries like banking. Cohere lists RBC, Dell Technologies, Oracle, SAP, Salesforce, and TD Bank among its customers, though North itself is newer and has limited independent public reviews.
This fits a regulated company, such as a bank or insurer, that needs an AI workspace it can run privately in its own cloud rather than a shared public one, and that has an internal team to manage a custom deployment. A sensible starting point is a scoped pilot in one function, such as legal contract review or sales research through Agent Studio, before a broader rollout. Cohere does not publish per-seat pricing, so treat any cost as a case-by-case quote and ask for a fixed pilot price before committing to a full contract. Because North is fairly new and Cohere is better known for models than finished business software, expect fewer independent reviews and a smaller partner network than established competitors. Budget extra time for a hands-on evaluation.
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 | $47.6K | $73.2K | $114.9K |
| Three-year total | $110K | $162.9K | $246.7K |
| First-year cost per unit | $2.4K | $3.7K | $5.7K |
| Average annual cost per unit (over three years) | $1.8K | $2.7K | $4.1K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $18K | $24K | $32.4K |
| Implementation | $6K | $10K | $17K |
| Integration | $6.6K | $12K | $21.6K |
| Staff time and change management | $4.9K | $7K | $9.8K |
| Security | $4.2K | $6K | $9K |
| Administration | $3.8K | $5K | $6.8K |
| Support | $1.9K | $2.5K | $3.4K |
Estimate assumptions: Planning quantity: 20. Unit definition: enabled user plus governed deployment. Pricing model: Enterprise platform subscription; deployment/inference may be separate. 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.
Architecture and deployment decision, data connectors, admin and audit controls, model/inference capacity, implementation partner or Cohere onboarding, and quote validation.
Complete the required permissions, governance, and data-quality review before a narrow pilot
Define the use case, complete the architecture review, obtain a quote and implementation plan, and require independent proof of retrieval quality and operational support.
Define what success looks like for a test of Cohere North 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.
Validate customer data separation, VPC/on-prem/Model Vault responsibilities, key management, retention, auditability, other companies that process data, model-training commitments, and support SLAs.
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.
Define the use case, complete the architecture review, obtain a quote and implementation plan, and require independent proof of retrieval quality and operational support.
OpenAI
A workplace AI assistant that helps staff write, research, and analyze data, kept private and never used to train the model.
Why it’s an alternative—
Compare with ChatGPT EnterpriseAnthropic
A workplace AI assistant that reads very long documents and helps staff write, code, and analyze, run under company controls.
Why it’s an alternative—
Compare with Claude EnterpriseAn AI helper built into Gmail, Docs, Sheets, and Meet, now included in Google Workspace business plans rather than sold separately.
Why it’s an alternative—
Compare with Gemini for Google WorkspaceAn AI helper built into Word, Excel, Outlook, and Teams that drafts, summarizes, and answers questions inside the apps you already use.
Why it’s an alternative—
Compare with Microsoft 365 CopilotWhere to check the product, price, security, and support.
Research observations recorded: 3. Evidence quality: Strong support.
Recorded score and category rank across research updates.
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