Bring data and an objective. Future Model Systems ingests, trains, evaluates and ships your model — and every step streams to your console while it happens. No black box. No status meetings.
Every run moves along the same instrumented rail — the one you see across this site. Each stage emits artifacts you can open, download and audit.
Upload CSV, JSONL or image archives. Checksums, schema sniffing and PII flags run automatically.
Splits, dedup, tokenization and class-balance analysis — recorded, repeatable, inspectable.
Your run executes on managed workers. Loss, LR and throughput stream to your console per step.
Held-out suites, per-class breakdowns and regression checks against your baseline.
Versioned export to ONNX or safetensors with a signed model card.
One-click hosted endpoint, or take the artifact and run it anywhere.
Start from a hardened template — sensible defaults, guardrails and the right eval suite built in. Custom specs available on ML Partner.
Fraud, churn, scoring. Gradient-boosted trees and calibrated ensembles on your structured data.
Routing, moderation, intent. Fine-tuned transformer encoders sized to your latency budget.
Your tone, your format, your domain — adapters trained on open-weight checkpoints.
Defect detection, tagging, triage. Transfer-learned CNN/ViT backbones on your images.
Every engagement ends with an eval report. These are excerpts from real report cards, shared with permission.
| baseline AUC | 0.71 |
| FMS run fms-2311 | 0.89▲ |
| training cost | $610 |
| manual routing acc. | 74% |
| FMS run fms-2287 | 93.2%▲ |
| p95 latency | 31 ms |
| vendor model top-1 | 81.5% |
| FMS run fms-2216 | 94.7%▲ |
| re-train cadence | weekly |
You buy a defined outcome — our engineers execute it on the pipeline while you watch. Fixed scope, compute included, quoted before we start. No meters, no surprises.