A sealed archive passing through a dark scrim and emerging as precise orange trajectories

scrim /skrɪm/ — a practice match against real opponents

RL environments builtfrom real company data

Scrimdata licenses the real company data, fully anonymizes it, and turns it into RL environments where frontier models train.

The transfer gap

Sandboxes don’t transfer.

Today’s agents train in synthetic sandboxes: replica apps with invented contents, imagined tasks, and benchmarks the whole industry has already memorized.

Then they meet the ambiguous email thread, the stale ticket, and the spreadsheet with three conflicting versions.

The training gap is a data gap: agents have never seen real work, because real work was never for sale.

Until now.

Synthetic environment

Invented tasks, plausible on paper
Clean data, empty history
Published benchmarks, memorized by every model

Scrimdata environment

Tasks mined from work that actually happened
Years of decisions, mistakes, and context
Private environments no model has ever seen

From real work to RL environments.

Real company data → anonymized Stand-In → RL environments

01

We license the data.

Real companies license their operational history to us: inboxes, Slack workspaces, ticket queues, document trees, CRMs, and calendars. Operating, winding down, or exited.

02

We erase the identity.

Curtain swaps every name, date, dollar figure, and proprietary detail for a consistent substitute. Relationships, timelines, and dependencies stay coherent.

03

We build the environments.

Each Stand-In becomes multi-step, multi-tool tasks with expert rubrics, programmatic verifiers, and reference trajectories grounded in what actually happened.

The digital twin

A structurally faithful workspace history.

The tasks

Work mined from what the real team did.

The rubrics

Expert grading anchored to real outcomes.

The verifiers

Checks that score trajectories at RL scale.

For AI labs

Practice like it’s production.

Private, uncontaminated environments with multi-step, multi-tool tasks, programmatic verifiers, and reference trajectories.

A private concrete training chamber with a warm scrim-lit threshold

Why private matters

Uncontaminated by construction.

Every public benchmark eventually leaks into training runs. Ours can't: Scrimdata environments come from operational histories that were never on the open internet and never will be.

When an agent passes, you're measuring capability, not memory. Rewards are anchored to the ground truth of what the company actually did.

Identity hidden.
Structure lit.

Curtain takes its name from the theater scrim: a solid wall from the audience side, the full shape of the work when the light changes. Every name, person, client, dollar figure, product detail, and date is transformed consistently.

The raw archive stays sealed. Structure survives. Identity doesn’t.

How anonymization works