Claimlane Connector
AI Agents For Warranty Claims — Handle even the most complex warranty claims in just one click. One platform for retailers and manufacturers to manage warranties, returns, and repairs.
ClaimlaneYour warehouseLive
Agent context over MCPSet up in minutes.
No code, no maintenance.
Claimlane
Data source
Claimlane in your warehouse.
Ready for your agents.
AI Agents For Warranty Claims — Handle even the most complex warranty claims in just one click. One platform for retailers and manufacturers to manage warranties, returns, and repairs. Weld's Claimlane connector is fully managed: it extracts data from Claimlane, loads it into your warehouse, and keeps it in sync. The data lands in a clean, documented schema with agent context attached, so analysts can query it with SQL or dbt, and agents can query it over the Weld MCP server without guessing at tables or joins.
Claimlane data schema.
The map your agents read.
Every table, field and relationship Weld syncs from Claimlane is served to agents as context over MCP, so they pick the right tables and join on the right keys.
- tables
- 27
- fields
- 250
Claimlane models.
What the numbers mean.
Open-source SQL that turns the raw Claimlane tables into the reports people ask about. Deploy them in Weld and your agent queries the definitions, not guesses.
- B2b claim linesEvery product line on every retailer-to-supplier claim, with the supplier's decision grouped into a small set of outcomes.grain: claimlane_account x ticket_id x product_index
- B2b claims by monthRetailer claims per brand and claim type per month: volume, the supplier's decisions, and the acceptance rate.grain: month x claimlane_account x brand_name x claim_type
- B2c claim linesEvery product on every consumer ticket, with the ticket's type, outcome and the refunds booked against the line.grain: claimlane_account x ticket_id x product_index (one row per claimed product line)
- B2c claims by monthConsumer claim volume and refunds per month: how many tickets, of which type, how they were settled, and how much money went back.grain: month x claimlane_account x organization_id x ticket_type x currency
- B2c claims by productWhich products come back, why, and what they cost in refunds.grain: claimlane_account x organization_id x currency x product_sku x issue_tag
Ask your agent.
It already knows Claimlane.
Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Claimlane context, finds the tables it needs and queries your warehouse.
- Agent contextClaimlane tables, fields and joins
- QuerySQL against your warehouse
- OperateCheck, rerun and refresh syncs
How many supplier_brand rows do we have per supplier? Use our Claimlane data.
Reading the Claimlane context first, so the query uses the right tables and keys.
Load Claimlane into any warehouse.
Set up in minutes, no code.
Everything you need.
To get started.
Set it up in code.
One REST API.
Use the Weld Connect REST API to create Claimlane connections, configure ELT syncs, and manage pipelines entirely through code. Built for embedding, automation, and CI/CD workflows.
▌Common questions.
About connectors.
Something not covered here? A data engineer can walk through your setup with you.
Talk to usPut your Claimlane data to work.
Connect Claimlane, pick a warehouse, and your agents can query it today. Free for 14 days, no credit card.
Source
