COSMOS.
The control layer for data, models, runs, and deployments — with zero undefined states.
COSMOS brings order to the entire machine learning lifecycle. It coordinates datasets, training runs, model versions, deployments, and governance into a single, verifiable system designed for reliability and scale.
Why ML systems drift.
Most ML stacks are a patchwork of notebooks, scripts, dashboards, and undocumented workflows.
Datasets change silently. Models ship without lineage. Promotions happen without verification. Teams inherit systems they cannot trace or trust.
The result is failure modes that appear "mysteriously" in production.
COSMOS eliminates this uncertainty by enforcing structure: every dataset, model, run, and deployment is an explicit, verifiable object.
A unified control plane for the ML lifecycle.
COSMOS provides a single source of truth for:
System overview and health
Synced from Paradigm, fingerprinted
Tracked configurations and metrics
Training and evaluation workflows
Versioned with full lineage
What is serving where and why
Health, metrics, alerts
Policy gates and compliance
Advanced configuration and tools
System configuration
Every stage is deterministic. Every transition is verified.
No undefined states. No silent failures.
Full lifecycle control.
GateService enforcement
- Every mutation funnelled through signature, health, fingerprint, staleness, and contract checks
- BLOCKED (412) or proceed. No bypass.
Hash-chained event log
- SHA-256 append-only. DB-enforced immutability (role + trigger prevent UPDATE/DELETE)
- Daily tamper verification.
Active reconciliation
- 5/15/30 minute drift detection against Paradigm, S3, and K8s
- Mismatch triggers quarantine and lock. Not alerts. Action.
Stored lineage
- Nodes and edges in the database. Recursive CTEs.
- Provenance as queryable data, not reconstructed from JOINs.
Four-state enforcement
- Every object: Verified, Degraded (root cause), Blocked (policy name), or Unverified (required action)
- Bypass is architecturally impossible.
OCI artifact signing
- Build, sign, and attest with SLSA provenance.
Content-addressable evidence store
- Local and S3 backends. Every execution produces one.
Versioned Paradigm contract
- OpenAPI contract with CI-enforced tests.
- Integration is a contract, not vibes.
Designed as Infrastructure.
COSMOS is built as a fault-tolerant distributed system.
Every component is typed, versioned, observable, and testable.
Built for GPU-backed training and evaluation.
COSMOS schedules and executes GPU workloads across cloud providers:
The system expects access to modern GPU accelerators for:
Dataset fingerprints, health checks, and signed execution evidence from Paradigm run automatically before any execution or promotion.
COSMOS is both a controller and a gatekeeper: nothing runs unless the state is correct.
Guaranteed dataset correctness for every run.
COSMOS treats Paradigm as the authoritative source of dataset truth and execution evidence.
- Dataset fingerprint captured
- Health verified
- Drift detected early
- Fingerprint revalidated
- Mismatch blocks deployment
- Policies enforced explicitly
If the data changed, the system refuses to proceed.
If the dataset degrades, training and promotion are blocked.
This eliminates silent drift.
Production-grade stack.
~42,000 lines · 10 routers · 16+ services · 12 DB tables · 15+ schemas
Next: ARCHON integration. Cloud deployment. We ship when it’s real.
COSMOS is used for orchestrating training, evaluation, and cloud GPU–backed experimentation, with integrated dataset validation through Paradigm.
COSMOS is fully operational.
The system is production-ready for real workloads and cloud-backed GPU execution.
The ML control plane for dependable AI.
COSMOS works alongside Paradigm (dataset creation and verification instrument) and ARCHON (execution & evidence engine) to form the foundation of verifiable AI for high-stakes environments.
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