Private enterprise data for frontier AI
Private Data For Frontier AI
We source and anonymize private enterprise data — codebases, documents, and operational artifacts — that isn't available on the public internet. For AI labs that need real-world training data.
Enterprise Documents
Real Operational Artifacts. Not Templates.
We source and anonymize private enterprise documents — board packages, financial models, compliance reports, internal memos. Created by real teams making real decisions.
Example Dataset
Industries & Domains We Source From
src/ledger/reconciliation.cbl
COBOL IDENTIFICATION DIVISION.
PROGRAM-ID. RECONCILE-LEDGER.
AUTHOR. PAYMENT-SYSTEMS-TEAM.
ENVIRONMENT DIVISION.
INPUT-OUTPUT SECTION.
FILE-CONTROL.
SELECT TRANS-FILE ASSIGN TO 'TRANSIN'
ORGANIZATION IS SEQUENTIAL.
DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-TRANSACTION-RECORD.
05 WS-ACCT-NUM PIC X(12).
05 WS-AMOUNT PIC S9(9)V99.
05 WS-CURRENCY-CODE PIC X(3).
05 WS-SETTLE-DATE PIC 9(8).
05 WS-FX-RATE PIC 9(3)V9(6).
05 WS-STATUS PIC X(2).
88 WS-SETTLED VALUE 'ST'.
88 WS-PENDING VALUE 'PN'.
01 WS-RECONCILE-TOTALS.
05 WS-TOTAL-DEBITS PIC S9(13)V99.
05 WS-TOTAL-CREDITS PIC S9(13)V99.
05 WS-VARIANCE PIC S9(13)V99.
PROCEDURE DIVISION.
MAIN-PROCESS.
PERFORM OPEN-FILES
PERFORM READ-TRANSACTIONS
UNTIL END-OF-FILE
PERFORM VALIDATE-SETTLEMENT
PERFORM APPLY-FX-CONVERSION
PERFORM CALCULATE-VARIANCE
PERFORM UPDATE-GENERAL-LEDGER
PERFORM CLOSE-FILES
STOP RUN.Commit History — 2,847 commits
Private Codebases
Production Code. Decision Context.
Legacy systems, niche domains, infrastructure code — with the full commit history, tickets, and engineering decisions around them. The code AI labs can't get from GitHub.
Languages & Stacks We Acquire
Shutting down?
Your startup shut down but the code still exists. We turn years of engineering into a payout.
Sunsetting a product?
Migrating off a legacy stack? The old system has training value that the new one never will.
Sitting on old code?
Internal tools, proprietary frameworks, domain-specific systems — they're more valuable than you think.
Beyond Data
Training Infrastructure
Private data is just the beginning. We also build verified training environments and full company-level simulations — the infrastructure AI labs need to train agents that can do real work.
Verified Environments — Coding Agents
Simulacra — CloudMetrics Inc. (Synthetic Enterprise)
Finance
Legal
Engineering
Operations
Environments
1,000+
Verified long-horizon tasks
Avg. Horizon
Days → Weeks
Multi-step, multi-tool workflows
Simulacra Verticals
4
Finance, legal, engineering, ops
Docs Per Simulacrum
8,000+
Grounded, realistic artifacts
Why This Matters
Model performance scales predictably with the number of verified training environments. More environments, covering more real workflows, produce agents that generalize better to production work. Your enterprise data doesn't just train a model — it powers verified environments and full company-level simulations that make AI agents production-ready.
Private data. Verified environments.
Production-ready agents.
Tell us what you need — we will scope availability, anonymization, and pricing.