Stop wasting hours fixing marketing data by hand. Lunde automatically combines separate platform metrics and messy invoices, removing errors through our human-in-the-loop QA process so you get verified, clean datasets ready for your next AI or Data Science project.
Raw on the left. Model-ready on the right. Nothing in between you have to babysit.
Daily API streams arriving at minute-by-minute volatility vs. quarterly accounting cycles arriving as static PDFs.
Net-to-advertiser, ledger-aligned, column-per-field arrays your pipeline can consume on the first try.
input_harmonization
Supply your marketing mix models with precise paid media signals. Lunde resolves daily ad-network volatility against monthly billing timelines, delivering net-to-advertiser values that survive retraining cycles without data degradation.
managed_pipelines
Eliminate the data engineering chore. Your operations team never has to build or maintain complex marketing data connectors. Lunde fully manages the underlying pipeline infrastructure—ingesting raw formats, normalizing currency, and programmatically scanning for discrepancies. When a variance occurs, our integrated human-in-the-loop data QA flags the issue and pushes a deep-linked anomaly alert straight to your Slack or Teams channel. Your team never touches code; they simply verify the highlighted cell, ensuring your corporate dashboards stay accurate and completely audit-ready with minimal effort.
mcp_infrastructure
Connect your pipelines directly to autonomous workflows. Lunde is Model Context Protocol (MCP) ready, delivering structured aggregate metrics with full row-level provenance and zero hallucinated context parameters.
version_control
Eliminate historical data drift. Compile immutable, version-controlled marketing data arrays that allow your data teams to re-run prior predictive models against exact, historical context blocks with absolute structural confidence.
What ships in the pilot. What's already on the bench.