In Depth: Speakeasy vs Databricks Unity AI Gateway

Speakeasy’s comparison of its AI Control Plane with Databricks Unity AI Gateway argues that the products address enterprise AI governance from different starting points: Databricks focuses on routing and governing model traffic and registered MCP services within the Unity Catalog and lakehouse ecosystem, while Speakeasy focuses on identity-based control of tool use, agent behavior, and AI clients across an organization. Unity AI Gateway, generally available in August 2026, provides centralized model access, token-level cost attribution, budgets, rate limits, traffic routing, catalog-based permissions, and audit logging, though several features including Smart Routing, service policies, and agent services remain in beta. Speakeasy uses MCP gateways, endpoint-deployed agent hooks, and directory identity integrations to inspect prompts, tool calls, shell commands, retrievals, and unregistered MCP servers, emphasizing company-wide discovery, policy enforcement, and visibility into personal or off-platform AI usage. The comparison concludes that Unity AI Gateway is better suited to organizations with Databricks-centered AI estates and lakehouse workloads, whereas Speakeasy is positioned for security and IT teams seeking governance across SaaS tools, internal APIs, developer clients, and other systems outside a single data platform; the products can also be used together because they govern different traffic paths.

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