AI & Machine Learning Engineering
We build autonomous AI agents, enterprise RAG knowledge search engines, LLM fine-tuning pipelines, and computer vision models engineered for security and speed.
Our AI Capabilities
Four specialized delivery tracks covering autonomous AI agents, enterprise RAG vector search, LLM fine-tuning, and computer vision.
Industry Domain Focus
We translate domain privacy constraints and workflows into custom AI models.
HIPAA-compliant clinical RAG search, medical report summarization, and diagnostic image assistance.
Fraud detection ML algorithms, automated document OCR parsing, and algorithmic risk models.
Predictive fleet maintenance models, route optimization algorithms, and automated package sorting.
AI visual search, personalized product recommendations, and automated customer support chat agents.
Contract analysis RAG search, automated clause comparison, and legal brief summarization.
YOLOv8 visual quality control on assembly lines and predictive machine failure sensors.
Case Studies
See how our RAG search engines and AI agents drove immediate operational efficiency.
A national law firm indexed 500,000+ legal briefs into a private vector search engine, allowing attorneys to search precedent rulings in sub-200ms.
500,000+
Legal documents indexed
< 200ms
Semantic query response time
An electronics factory deployed custom YOLOv8 computer vision models on edge gateways to inspect circuit boards for micro-defects at 60 FPS.
60 FPS
Real-time video inspection speed
99.6%
Micro-defect detection accuracy
A SaaS company deployed autonomous LangChain AI agents that resolve 80% of customer technical support tickets without human intervention.
80%
Automated ticket resolution rate
-65%
Customer support operation cost
Consult with our senior AI architects and receive a custom vector search blueprint, model selection recommendation, and launch estimate.
Working semantic search prototype running on your private documents within two weeks.
Senior Machine Learning architects and PyTorch engineers assigned to your build full time.
Complete ownership of fine-tuned weights, training pipelines, and vector database schemas.
Technology Stack & Ecosystem
We build AI systems with strict vector precision, low inference latency, and data isolation.
AI agent & tool orchestration
Data framework for LLM applications
Deep learning model training
Production machine learning core
Multi-agent conversation networks
High-throughput LLM inference
Development Process
Evaluate training data quality, privacy constraints, latency goals, and model selection before coding.
Build vector search pipelines, fine-tune open-source LLMs, and draft prompt safety guardrails.
Develop autonomous agent workflows, FastAPI backends, and connect internal CRM/ERP tools.
Test model accuracy against golden datasets, evaluate hallucination rates, and optimize inference cost.
Deploy models to GPU clusters with autoscaling, vLLM acceleration, and monitoring walls.
Continuous dataset retraining, prompt engineering refinements, and model SLA maintenance.
Engagement Models
$15k - $32k
4 to 6 weeks
$32k - $75k
6 to 12 weeks
$75k - $160k+
12 to 22 weeks
Security & Quality
Your private company documents and data are never used to train public LLM models.
Deploy fully open-source Llama 3 or Mistral models inside your private AWS/Azure VPC with zero external API calls.
Strict RAG context groundings preventing AI from inventing inaccurate facts.
Encrypted vector storage, audit logging, and role-based access for healthcare and finance.
Sensitive AI actions (like financial transfers or medical records) require human sign-off.
vLLM and TensorRT acceleration for ultra-fast real-time model responses.
FAQ
Everything you need to know about LLM fine-tuning, RAG accuracy, and data security.