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Accelerate or extend your MVP
Optimize application infrastructure to lower costs
Securely fine-tune on your proprietary data
Deploy hybrid-cloud applications at the edge or on-device

Build Frontier AI Applications and Services

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Peregrine Labs is a hybrid-cloud systems integrator dedicated to advancing America’s general purpose artificial intelligence capabilities. The firm was launched out of MIT by a team of highly specialized engineers with 10+ years of experience building solutions at Google, xAI, Apple, AWS, and Microsoft (among others). We work shoulder-to-shoulder with startups, enterprises, and the United States Government to integrate frontier artificial intelligence into dynamic applications across on-prem, hybrid, and cloud-native ecosystems. We are very comfortable operating on aggressive timelines and work to deliver state-of-the-art results in every engagement. As a firm, our number one priority is integrity - if your needs are outside of our niche, we have a wide industry network and will connect you with the right solution.

Who We Are

AI Application Development

Build custom artificial intelligence into dynamic applications that transform how you operate and serve customers.

Fine-Tuning & Quantization
from transformers import AutoModelForCausalLM, AutoTokenizer from peft import prepare_model_for_kbit_training, LoraConfig from trl import SFTTrainer # Load model with 4-bit quantization model = AutoModelForCausalLM.from_pretrained( "meta-llama/Llama-3-8B", load_in_4bit=True, device_map="auto" ) # Configure QLoRA with rank-8 adapters lora_config = LoraConfig( r=8, lora_alpha=16, target_modules=["q_proj", "v_proj"], lora_dropout=0.05 ) # Fine-tune on custom dataset trainer = SFTTrainer( model=model, train_dataset=dataset, peft_config=lora_config )

Hybrid Systems Integration

Modernize, migrate, or extend AI-enabled products across on-prem, hybrid, or cloud-native computing environments.

Solutions Architecture
Enterprise Data Orchestration: Transform unstructured data scattered across legacy systems into retrieval augmented generation (RAG) pipelines for grounded inference.
Azure Hybrid Cloud Architecture Diagram

Venture-Operating Partner

Invest in technology startups; operate venture capital and private equity portfolios to optimize costs and accelerate growth.

Financial Engineering
Revenue $2.4M
COGS ($360K)
Operating Expenses ($1.2M)
EBITDA $840K
Magic Number 1.2x
LTV/CAC 3.8x
Rule of 40 55%

What We Do