Building AI-Native Finance Processes for Construction

Contractors are deploying AI while job cost and close still run on manual work arounds. Tetra builds the process and data foundation for AI to provide value on the systems you already own.

Your team isn’t behind but your workflows are.

Every month is a fire drill.

The close runs on late adjustments, rework and overtime.

No one knows where the job really stands.

Costs coded late or to the wrong job so the forecast never moves. Fade shows up at closeout.

Your analysts clean data instead of analyzing it.

Before a forecast goes to leadership, someone repairs what came out of the ERP.

AI has nothing solid to run on.

It needs a process someone owns and data you can trust. Most finance workflows are missing both.

Your finance team needs a foundation to build on.

AI requires a process someone owns and data you can trust. Tetra solves this as the finance engineering firm for contractors, building the process and data foundation your team needs to get value from your AI initiatives. Built on the systems you use today.

Solution: We map your monthly cost-to-complete process from how it’s submitted, approved, and reconciled to every job. Then we work with your team to standardize the process and data inputs, allowing automation to complete the bulk of the workflow. AI reviews the process, flagging exceptions, so your PM’s and Controller spend their time on decisions that need to be made rather than on what already happened.

Your team owns what’s builtWe don’t fix what isn’t brokenJudgement stays with you
David Dors, founder of Tetra

Who you’ll work with

Dave Dors is the founder and managing partner at Tetra. Working with CFOs and Controllers at general contractors, speciality trades, and heavy civil firms. We build AI-native processes for WIP, cost-to-complete, forecasting, and close on the systems you already run: Sage, Procore, Vista, and many more...

Start with the processes that are AI-ready

A 30-minute call with Dave about your close process, WIP or cost-to-complete. You leave knowing whether it’s ready for AI, or what has to be fixed first.