Rig vs. building it yourself
Pick where you're starting from and see how Rig compares.
No warehouse yet? You need a data stack that's AI-native.
The modern data stack you'd build yourselves
Typical early-stage shape: ~10 SaaS sources, ~1 TB of data, one data engineer stitching it together. Your numbers will differ, but the stack's overall shape is similar.
Three comparisons that come up most
vs. building the full stack yourselves
About ten separate tools and contracts. Six to nine months pass before the first useful output, and the maintenance never stops once it is live.
Rig is one product covering ingestion, warehouse, modelling, hosting, AI, governance and audit. The first useful output comes inside a week, and you do not need a data team to start.
vs. a data consultancy build
Six-figure SOW, three to six months of discovery and stand-up. You inherit a stack you didn't choose and still have to run it.
Self-serve on day one, white-glove if you want it. We run the stack, so your team can spend its time on the workflows.
vs. hiring a data team to figure it out
Typically the first data hire spends six months choosing tools, and the second spends six more connecting them.
Your existing operators ship the first apps. Hire a data person when the work calls for one.
Already mid-build? Talk to us about migrating off your DIY stack
Rig's AI agent handles the schema translation, and we can scope the move on a call.