Automate your data engineering

Keep Stripe, Salesforce, and BigQuery aligned so customer revenue is current in our warehouse.

Mage

I've created a connected workflow.

  • pull new and updated customers from Stripe
  • match them to Salesforce accounts
  • write revenue and account records to BigQuery
  • check for duplicates, missing IDs, and failed writes
  • alert the team when records cannot be matched

I’ll also show the source map so you can review which systems are used and where the data goes.

Describe the workflow. Mage builds it, runs it on autopilot, and turns every trusted output into reusable context.

Ship more work with the team you already have

Mage removes the repetitive work between a request and a production-ready workflow.

Sync Stripe customers to BigQuery every weekday before 8am.
Weekdays · 8:00am
Stripe
Transform
Validate

Build from intent. Turn requests into sources, code blocks, transformations, checks, and schedules.

Internal billing API
customer_idstring
invoice_totaldecimal
updated_attimestamp
Billing feedConnected

Connect what tools miss. Create workflows for unsupported APIs, files, vendor feeds, SaaS tools, and internal systems.

Customer sync
Running normally
Replayed from transform

Keep production moving. Monitor, debug, retry, replay, backfill, recover, and optimize workflows after they ship.

Trust before it moves. Validate data quality, business rules, and workflow intent before outputs go downstream.

One request becomes a self-operating workflow

Mage turns a request into sources, code, checks, schedules, recovery, and reusable outputs.

Build a daily customer health workflow. Pull account data from Salesforce, product usage from Snowflake, and open tickets from Zendesk. Score each account before 8am, notify the owner when risk increases, and save the result for dashboards and agents.

Customer health workflow is ready to review. I connected the 3 sources, created the scoring logic, scheduled it for 7am, added freshness and failure checks, and prepared alerts for account owners.

Customer health workflow
3 sourcesDaily at 7amChecks enabled

Ask. Describe the sync, model, report, or workflow you need.

Build. AI Sidekick creates the sources, code blocks, transformations, checks, and schedule.

Run. Mage executes the workflow across apps, APIs, warehouses, files, streams, and dbt.

Validate. Autopilot checks data quality, business rules, and whether the workflow still matches intent.

Recover. Autopilot explains failures, retries safely, replays history, and repairs broken steps.

Reuse. The output becomes context for dashboards, automations, products, APIs, and agents.

The systems behind every automated workflow

Prompt-built workflows Describe the workflow. Mage turns it into sources, code blocks, dependencies, checks, and schedules.

Talk to your data Ask questions across schemas, outputs, run history, errors, and upstream data while you build.

Workspace actions Ask Mage to inspect runs, review failures, create resources, or manage workflow changes.

Self-healing operations Detect failures, repair what broke, retry safely, replay history, and recover production runs.

Quality and intent checks Describe what should be true. Mage checks data quality, business rules, and workflow intent automatically.

Resource optimization Tune runtime, memory, concurrency, and infrastructure usage as workloads change.

Reusable workflow context Turn reliable outputs, logic, lineage, checks, and run history into context teams can reuse.

Intent-aware context Give agents the right data, permissions, freshness, and scope for the task.

Context activation Use trusted outputs across dashboards, APIs, automations, RAG pipelines, products, and agents.

Start with the work your team already does manually

Bring Mage the recurring work that is slow, brittle, repetitive, or stuck between tools.

Integration syncs. Keep Salesforce, Stripe, HubSpot, BigQuery, Snowflake, and internal systems aligned.

Data quality routines. Check freshness, schema drift, duplicates, missing IDs, failed writes, and business rules.

Backfills and recovery. Replay missing time windows, repair incomplete runs, and recover without duplicate writes.

Start with a missing connector, fragile script, dbt workflow, medallion model, manual report, or recurring sync between business systems.