Sync SEO data into your lakehouse and push ML-powered insights back to marketing teams. Stop exporting keyword rankings to CSV, manually enriching competitor data, or rebuilding the same performance dashboards every week.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically pull daily ranking data, backlink metrics, and SERP features from Semrush into Databricks. Build longitudinal datasets tracking keyword performance, competitor movements, and search visibility over time without manual exports.
Score website opportunities using machine learning models trained on historical SEO and conversion data. Push predicted traffic potential, content gap scores, and ranking probability back to Semrush projects for prioritization.
Join keyword ranking changes, organic traffic from Semrush with conversion and revenue tables in Databricks. Build unified dashboards showing true SEO ROI and automatically alert teams when rankings correlate with revenue shifts.
Monitor site health audits and crawl errors in Semrush, then trigger Databricks jobs to analyze log files, identify affected pages, and correlate technical issues with traffic drops across your data warehouse.
Use clustering and NLP models to segment high-performing content themes, then automatically update Semrush tracking campaigns with optimized keyword groups and content recommendations based on what actually drives conversions.
Continuously capture competitor analysis data from Semrush—backlink growth, ad spend estimates, top pages—into versioned Delta tables. Build time-series models identifying competitive pattern shifts and market share movements.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Databricks and Semrush 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 Databricks table schemas and Semrush API structures—from Delta table partitions and feature stores to keyword databases and domain analytics hierarchies.
Redbird maps Semrush position tracking reports, backlink indexes, and traffic analytics to your Databricks catalog structure automatically. It knows how to handle keyword ranking arrays, competitor domain lists, and SERP feature data as structured tables. When you push ML predictions back, Redbird formats scoring outputs to match Semrush project schemas—no custom transformations or API wrangling required.
faster than building custom Semrush API connectors and Spark jobs
Redbird can pull from Databricks and Semrush 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 Databricks or Semrush.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Databricks into Semrush, or from Semrush back into Databricks. 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 ranking changes in Semrush or model training completion in Databricks—connect every event across your data and marketing stack.
Trigger when ETL pipeline, ML training run, or SQL query finishes—successful or failed.
Detect inserts or updates to specific Delta tables, databases, or catalog schemas.
Fire when new model versions are logged, staged for production, or promoted.
Run Databricks notebooks, SQL queries, or orchestrate multi-step workflows programmatically.
Insert, upsert, or append records to Delta tables with schema evolution and merge logic.
Score new data using registered models and write predictions back to feature store or tables.
Fire when tracked keywords move up or down in position beyond defined thresholds.
Trigger when Semrush identifies new referring domains, lost links, or authority changes.
Alert when crawl errors, broken links, or SEO health scores cross warning levels.
Add or remove keywords from position tracking projects based on performance data.
Set up new competitor tracking, backlink monitoring, or traffic analysis automatically.
Generate and retrieve keyword, traffic, or competitor reports with specific date ranges and filters.
Stop building custom pipelines between your data lakehouse and marketing analytics. Connect Databricks and Semrush in minutes and let AI handle the sync, enrichment, and orchestration.