Crucible
the AI ML Engineer

From plain language to a production model.

The Crucible console building a support-ticket classifier — consolidated rules pending review alongside the generated rules.md artifact.

Forge 01

The first model built exclusively for machine learning engineering.

Reviews experiments.
Evaluates outcomes.
Diagnoses issues.
Recommends next steps.
A Forge recommendation artifact — the chosen base model, architecture, and training configuration for a support-ticket classifier, with Forge's advice applied.

Point Crucible at a task. It builds the specialist and keeps it sharp.

A model built for the job, shipped with evals and monitoring, and retrained on your traffic so it sharpens over time.

01

Document classification

  • Built from your labels — no labeling project
  • Low-confidence cases routed for review, not guessed
  • Retrains on live traffic as documents change
82.1%97.8%
02

Customer intent routing

  • Trained on your conversations and routing tree
  • Wrong routes caught in evals, not by customers
  • Relearns as new intents and products appear
74.3%96.2%
03

Contract extraction

  • Built around your schema — MSAs, NDAs, order forms
  • Structured output, not free text to re-parse
  • New clause patterns folded in over time
68.9%94.6%
04

Support resolution

  • Trained on your resolutions and policies
  • Every answer graded before it sends
  • Sharpens on every resolved ticket
71.2%93.1%
05

Compliance screening

  • Built around your policies and thresholds
  • Consistent, auditable decisions at volume
  • Rule changes retrained in as they land
79.5%98.1%
06

And whatever's next

Define what “correct” looks like and Crucible builds the specialist — classification, extraction, routing, scoring, generation.