Custom LLM Development & Fine-Tuning
Fine-Tuned Open-Source & Private Foundation Models Tailored for Your Vertical
Harness the power of domain-specific Large Language Models (LLMs). We fine-tune models like Llama 3, Mistral, and DeepSeek using LoRA, QLoRA, and full-parameter tuning to deliver supercharged accuracy for industry-specific terminology.
Delivery Benchmarks
Engineered SLA Standard
4x
Inference Speedup
vLLM & Quantization
65%
Token Cost Savings
vs Proprietary API calls
99.4%
Domain Accuracy
Benchmark Evaluated
100%
On-Premises / VPC
Air-Gapped Privacy
Private VPC / Air-Gapped Ready
100% Zero-Data-Retention & IP Protection.
Enterprise-Grade AI Tailored to Your Specific Workflows
Generic public models fail when confronted with complex domain vocabularies, proprietary codebases, or sensitive internal data. We engineer tailored LLM solutions optimized for your exact niche—drastically reducing API token costs, latency, and reliance on closed-source providers.
What We Build & Deliver
Domain-Specific Fine-Tuning
PEFT, LoRA, and QLoRA fine-tuning on custom curated datasets for medical, legal, financial, and technical domains.
Dataset Preparation & Synthetic Data
Automated data cleaning, tokenization, instruction-pair formatting, and synthetic data generation with RLHF/DPO alignment.
Model Quantization & vLLM Serving
FP8, INT4 quantization and high-throughput TensorRT-LLM / vLLM serving engines for sub-50ms token generation.
Private Self-Hosted Infrastructure
Deploy on AWS SageMaker, GCP Vertex AI, RunPod, or bare-metal GPU clusters with automated auto-scaling.
Continuous Evaluation Harness
Automated benchmarking against BLEU, ROUGE, MMLU, and proprietary golden test sets before each release.
Hybrid Model Routing
Intelligent query classification routing small prompts to fast 8B models and complex tasks to 70B+ architectures.
Specialized Tooling & AI Stack
We leverage leading state-of-the-art frameworks, foundation models, and vector stores to ensure ultra-low latency, strict reproducibility, and infinite cloud scalability.
Llama 3.3 (8B/70B)
Base Foundation
Mistral / Mixtral
MoE Architectures
DeepSeek R1 / V3
Reasoning Models
Hugging Face TRL
Fine-Tuning Stack
vLLM / TensorRT
Inference Engines
Ray Train & PyTorch
Distributed Training
Triton Server
Model Serving
Weights & Biases
Experiment Tracking
Real-World Industry Applications
Embedded in-product AI assistants that understand proprietary database schemas and internal documentation.
Biomedical NER, clinical summary parsing, and chemistry molecular property query models.
Policy underwriting risk analyzers, claims processing LLMs, and regulatory auditor bots.
Private code completion and automated PR review LLMs fine-tuned on internal company repositories.
Prove ROI & Feasibility in 14 Days
Validate your AI hypothesis on private benchmark datasets before committing significant capital to full-scale infrastructure.
Frequently Asked Questions
Everything you need to know regarding implementation, timeline, and privacy.
Fine-tuned models offer 100% data sovereignty, lower latency, up to 70% cheaper operational costs at scale, and higher precision on specialized domain terminology.
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