Our public roadmap. Updated every sprint. No vaporware — only things that are actually on the board.
Define which rows an AI model can access per data source. Filter by org, user, or custom expression.
Stream audit events to your SIEM, Datadog, or custom endpoint in real time.
Per-agent uptime graphs, query throughput, latency percentiles, and error rates in the dashboard.
Native MongoDB support with collection schema discovery and aggregation pipeline tools.
Auto-discover GraphQL schemas and expose queries as typed MCP tools.
Formal audit completion for enterprise and regulated-industry customers.
Override auto-generated tool names, descriptions, and parameter types from the dashboard.
Data warehouse support for analytics-scale queries from AI models.
Optional TTL-based caching layer to reduce database load for repeated AI queries.
Control plane available in EU and APAC regions for data residency compliance.
Dedicated infrastructure with BAA support for healthcare customers.
Manage plugins, connections, and MCP servers as infrastructure-as-code.
Our roadmap is shaped by real customer requests. Tell us what's blocking you.
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