In Depth: Speakeasy vs Databricks Unity AI Gateway
Blog post from Speakeasy
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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