Foundation Models

Train language models that understand your domain.

From fine-tuning open-source LLMs to building custom pre-trained models — with evaluation pipelines that prove it works in production.

The progression

Start where you are.
Build toward the frontier.

We meet you at your current maturity level and build a clear path forward — from foundational implementation to research-grade capability.

01
Where most teams start

Fine-Tuning

  • PEFT / LoRA instruction tuning
  • Dataset curation & cleaning pipelines
  • Quantization (GGUF, AWQ, GPTQ)
  • Domain-specific prompt engineering
  • Baseline evaluation benchmarks
02
Models shaped by your proprietary data

Custom Pre-Training

  • Continual pre-training on domain corpora
  • Custom tokenizer design & vocabulary
  • Curriculum learning & data mixing
  • Compute-optimal training strategies
  • Rigorous eval framework design
03
Where the AI advantage compounds

Research Frontier

  • RLHF, DPO & Constitutional AI
  • Reward modeling & preference data pipelines
  • Model merging (SLERP, DARE, TIES)
  • Multi-task & cross-lingual training
  • Interpretability & safety evaluation
What you get

Shipped artifacts,
not slide decks.

Every engagement ends with working software, documented systems, and a team that knows how to extend them.

Model weights + inference API

Production-ready fine-tuned or pre-trained weights, packaged with an optimized serving layer.

Custom eval benchmarks

Bespoke evaluation suites built around your domain — not generic leaderboard scores.

Reproducible training pipeline

Versioned, documented training code your team can own, re-run, and extend independently.

Knowledge transfer session

Hands-on handoff so your team understands the architecture, not just the outputs.

Ready to build?

Your Foundation Models stack
starts with one call.

Book a 30-minute strategy session. We'll map your specific opportunity in foundation models, identify the highest-leverage starting point, and tell you exactly what an engagement looks like.

Usually responds within 24 hours