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.
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.
Fine-Tuning
- PEFT / LoRA instruction tuning
- Dataset curation & cleaning pipelines
- Quantization (GGUF, AWQ, GPTQ)
- Domain-specific prompt engineering
- Baseline evaluation benchmarks
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
Research Frontier
- RLHF, DPO & Constitutional AI
- Reward modeling & preference data pipelines
- Model merging (SLERP, DARE, TIES)
- Multi-task & cross-lingual training
- Interpretability & safety evaluation
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.
Your FinTech & Accounting
AI stack
starts with one call.
Book a 30-minute strategy session. We'll map your specific opportunity in fintech & accounting ai, identify the highest-leverage starting point, and tell you exactly what an engagement looks like.