"I work in Data Science. What can InTouch do for me?"

InTouch isn't trying to be your notebook or a training cluster — it's the plumbing around the model you already built, so the model stays fed, scored and monitored without you babysitting it.

Your model is already a Python or R script. A runtime environment executes it on a schedule with its dependencies and env vars pinned, writes results to a table, and only pings you if the run fails or a metric drifts. No rewrite, no DSL — your script stays yours.

SQL against any supported database, Snowflake, Databricks, ClickHouse, plus S3, FTP/SFTP, HTTP/REST and Excel/CSV. A dataframe tool joins and aggregates between steps, so the glue code stops rotting inside the notebook.

Extract → transform → load → retrain → score as one workflow, each step passing output to the next. A failure stops the chain instead of silently poisoning the table downstream.

A monitor pairs a check with a condition and an action — accuracy below a floor, a null rate spiking, a source table that didn't land by 6am. You hear about it once, with the actual number, not by noticing three days later.

Every run is logged with inputs, outputs, duration and result code. Credentials come from an encrypted vault at execution time — never in the script, the log, or any AI's context.

Two honest caveats: this isn't a notebook host or a GPU cluster — it runs code you already wrote, on hardware you own. And nothing auto-infers your schema; you point it at the source once, with my help.

Silence means fine. A message means look at this.