The Platform

The complete fine-tuning compliance stack

Dataset versioning → training run tracking → eval benchmarking → audit package generation. Cognify handles the entire documentation chain from first training step to compliance sign-off.

Abstract platform architecture diagram showing ML pipeline stages connected with amber data flow paths on dark background
Dataset Versioning

Dataset versioning that compliance teams trust

Every dataset used in training — base model fine-tuning corpora, instruction datasets, eval benchmarks, safety test sets — is snapshotted and cryptographically hashed at the moment of use. No retroactive edits. Full diff between versions.

dataset_versions.diff
VersionTimestampRecordsSHA-256Status
v1.0.02026-03-14 09:12847,293a3f2...8e19base
v1.1.02026-03-21 14:05851,1047d8c...4a01+3,811 rows
v1.1.12026-03-29 11:33851,104c12e...9f77schema change
v1.2.02026-04-08 16:44902,5185b39...2d64+51,414 rows
v2.0.02026-04-17 09:001,203,741e87a...0c45major revision
v2.0.12026-04-24 13:201,203,741f99d...7b12cleanup only
Run Lineage

Training run lineage — immutable and complete

Every hyperparameter, every checkpoint, every hardware configuration linked to the dataset version that produced it. The lineage graph is write-once — not even admins can edit a completed run record.

lineage_graph
dataset:v2.0.1
↓ hash-linked
config:lr=2e-5,bs=16
↓ training run #447
checkpoint:step_8000 step_16000 final
↓ eval pipeline
eval:safety=0.94 & domain=0.87
↓ immutable lock
audit_record:sealed
Eval Benchmarking

Eval benchmarks compliance teams can reference

Track model performance on domain-specific safety benchmarks across every training iteration. Compliance teams can see exactly which eval results correspond to which training run — not just the final model.

eval_summary.json (run #447)
{
  "run_id": "cgnf-run-447",
  "benchmarks": {
    "safety_classification": 0.942,
    "domain_accuracy": 0.871,
    "bias_detection_f1": 0.889,
    "hallucination_rate": 0.023
  },
  "policy_thresholds_met": true,
  "compliance_status": "READY_FOR_REVIEW",
  "signed_by": null,
  "locked": false
}
Audit Packages

Audit packages in formats regulators recognize

One-click export of structured model documentation: model card (AI Act template), data provenance report, training configuration attestation, eval benchmark summary. PDF for legal, JSON for your internal systems, XLSX for governance committees.

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Abstract visualization of compliance audit document export — stylized document cards with amber accent highlights on dark background