Retrieval
Hybrid BM25 + dense, rerankers, query rewriting.
Generative AI & LLM
LLM Fine-tuning & RAG
Make general models specialists — without overfitting your roadmap.
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RAG, SFT, DPO, LoRA — applied when the eval delta justifies it, not because it's trending.
Capabilities
What we build
Fine-tuning
LoRA / QLoRA / DPO on open and frontier models.
Evaluation
Pairwise, rubric, and task-grounded benchmarks.
Serving
vLLM, TGI, TensorRT-LLM, managed and self-hosted.
Outcomes
Measured results
+40%
Task accuracy
50%
Token cost saved
Reproducible
Eval reports
Why nexgts
Why teams pick us
- Honest about when RAG > fine-tune
- Open-source first, frontier where it pays
- Cost & latency budgeted
Use cases
Where it fits
Domain Q&ADocument draftingCode generationStructured extraction
Ready to put LLM Fine-tuning & RAG into production?
We scope, build, and operate — usually in weeks, not quarters.
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