Build from intent. Turn requests into sources, code blocks, transformations, checks, and schedules.
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.
customer_idstringinvoice_totaldecimalupdated_attimestampConnect what tools miss. Create workflows for unsupported APIs, files, vendor feeds, SaaS tools, and internal systems.
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.
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.
Modernize the tools your team relies on
Choose your current tool. See how we can move one workflow, check its results, and keep it running.
Ab Initio Move a reporting workflow so specialists can focus on other priorities.
AWS Data Pipeline Move scheduled jobs and keep delivery checked.
AWS Glue Build the next incremental feed with safe replay and checked writes.
AWS Step Functions Move data workflows with checked publishing.
Azure Data Factory Deliver the feed your system rollout needs, with ongoing operation.
Azure Logic Apps Deliver an app-data handoff that respects destination API limits.
Azure Synapse Analytics Move one feed. Keep your analytics platform.
BizTalk Move one data or file handoff, check delivery, and keep it running.
Google Cloud Composer Move one DAG feed and keep its data current.
Google Cloud Data Fusion Rebuild a batch feed and check its output.
Google Cloud Dataflow Assess and rebuild a suitable batch feed.
IBM DataStage Move data jobs while engineering focuses elsewhere.
Informatica PowerCenter Preserve agreed data rules and compare the new results.
Oracle Data Integrator Move warehouse loads without adding another internal build.
Oracle Data Integrator Enterprise Edition Move selected data loads.
Oracle SOA Rebuild one business handoff, verify delivery, and keep it running.
Pentaho Keep supplier-file jobs running without taking on another rebuild.
SAP Data Services Modernize data loads with business systems in place.
SAP Process Integration Keep message fields intact and data flowing.
SAP Process Orchestration Modernize a handoff while preserving approval steps.
SAS Enterprise Guide Automate data prep and recurring report refreshes.
SSIS Move data loads off the backlog and keep reports current.
Talend Data Integration Hand off selected jobs and their ongoing operation.
Talend Open Studio Give your existing data jobs a supported path forward.
TIBCO BusinessWorks Move an integration and free up your specialists.
webMethods Rebuild a customer-data handoff without another internal project.






