Draftt for AI Governance review
Lifecycle and usage governance for teams managing models, agents, and shadow AI.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Draftt for AI Governance gives engineering teams a central inventory of AI models, agents, and services across cloud providers, SaaS applications, APIs, and custom deployments. It is positioned for mid-market and enterprise organizations that need to understand which systems are in use and govern them while engineering teams handle remediation in their own application contexts. The inventory tracks users, ownership, versions, lifecycle status, activity, usage, and estimated costs, making the product especially relevant where model sprawl or shadow AI is a concern.
Governance is organized around model use and lifecycle. Teams can create custom policies for approved or prohibited models and versions, as well as data-handling rules, and Draftt detects unauthorized or shadow AI usage. It also alerts teams to model deprecations and provides migration paths, while tracking projected extended-support costs for deprecated models. Findings can be routed to responsible teams as tickets and Slack alerts. The product also supports custom agents, agentic workflows, and multi-model pipelines, extending its scope beyond a simple registry. Its listed ecosystem includes AWS Bedrock, Google Cloud Vertex AI, Azure OpenAI, Azure AI Foundry, OpenAI, Anthropic Claude, and Slack.
The fit is strongest for teams that need ongoing visibility into model activity, costs, and lifecycle changes, and that want policy findings routed to the teams responsible for action. According to the vendor's sales approach, prospective customers are directed to book a demo rather than choose from published plans, so buyers should expect to discuss pricing with Draftt. The product is cloud-based and accessed on the web. Its governance emphasis is lifecycle and usage rather than full compliance evidence, so organizations whose primary requirement is compliance-framework evidence should consider whether that focus meets their needs before proceeding.
Draftt for AI Governance pros and cons
- Where it wins
- Continuously inventories models, agents, and services across providers
- Custom policies can govern model versions and data-handling rules
- Routes lifecycle and policy findings through tickets and Slack alerts
- Where it doesn't
- Pricing is contact-sales rather than published by plan
- Deployment is cloud-based and the platform is web-only
- Focuses on lifecycle and usage, not full compliance evidence
Draftt for AI Governance fact sheet, pricing and score →
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