Redbird AI connects your BI semantic layer to your operational document store. Stop manually syncing data between MongoDB collections and Looker explores, exporting reports to update operational databases, or writing custom scripts to keep metrics and application data aligned.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Export aggregated metrics and KPIs from Looker dashboards directly into MongoDB collections. Keep operational systems updated with the latest business intelligence without manual CSV exports or custom ETL jobs.
Stream user behavior, feature usage, and product events from MongoDB into your data warehouse for Looker analysis. Redbird handles schema mapping from nested documents to relational structures your LookML models expect.
Trigger application logic stored in MongoDB when business metrics in Looker dashboards hit critical levels. Automatically update operational flags, user segments, or configuration documents based on analytical insights.
Capture snapshots of key Looker reports and store them as versioned documents in MongoDB. Maintain a queryable archive of business metrics over time without bloating your primary data warehouse.
Write cohort classifications, RFM scores, and customer health metrics from Looker directly back into MongoDB user documents. Keep your application database enriched with the latest analytical insights for personalization and targeting.
Automatically trigger Looker dashboard refreshes and scheduled looks when MongoDB document counts, data volume, or specific field values change. Ensure stakeholders get reports exactly when new operational data becomes available.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Looker and MongoDB with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird understands both LookML semantic models and MongoDB document schemas, intelligently mapping between relational BI concepts and nested JSON structures without custom transformation code.
Redbird's AI automatically navigates MongoDB's flexible document structure and Looker's governed metric definitions. It flattens nested arrays for BI consumption, maps embedded documents to dimension groups, and translates aggregated Looker results back into properly structured MongoDB documents. The platform handles schema evolution on both sides, updating mappings when you modify LookML models or change document structures.
faster than building custom MongoDB-to-warehouse pipelines for Looker
Redbird can pull from Looker and MongoDB simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Looker or MongoDB.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Looker into MongoDB, or from MongoDB back into Looker. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start automations from any Looker dashboard event or MongoDB collection change, then take action across your entire stack.
Trigger when any metric in a Looker dashboard crosses a defined threshold value.
Fire when a scheduled Looker report finishes running on its defined cadence.
Activate when a specific saved Looker explore query produces new or updated results.
Programmatically modify dimension definitions, measures, or model parameters in your LookML repository.
Trigger rebuilds of Looker aggregate tables or persistent derived tables based on external events.
Execute a parameterized Looker query and route the result set to downstream systems.
Fire when new documents are added to specified MongoDB collections or databases.
Trigger when a specific field within MongoDB documents changes to a particular value or range.
Activate when a MongoDB collection grows beyond a defined document count or storage size.
Insert or update MongoDB documents based on key fields, preserving existing nested structures.
Modify specific elements within embedded arrays or nested subdocuments without replacing entire structures.
Run MongoDB aggregation queries to transform, group, or compute values across collections.
Join teams that sync Looker insights with MongoDB operational data in minutes, not weeks. Redbird handles the complexity of connecting your semantic layer to your document store so you can focus on building data-driven products.