INITIALIZING
Enterprise AI

Architecting
Intelligence

Production-grade AI systems for enterprise. From computer vision to LLMs, we build the infrastructure that powers the future.

model.py
# AI pipeline
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

def run_ai(prompt, m="gpt2"):
    d="cuda" if torch.cuda.is_available() else "cpu"
    t=AutoTokenizer.from_pretrained(m)
    a=AutoModelForCausalLM.from_pretrained(m).to(d)
    x=t(prompt,return_tensors="pt").to(d)
    y=a.generate(**x,max_new_tokens=32)
    return t.decode(y[0])

Software Stack:

Python PyTorch PyTorch Lightning NumPy Pandas TensorFlow JAX Flax Hugging Face Transformers Diffusers OpenAI API OpenRouter vLLM Triton ONNX CUDA LangChain LlamaIndex FAISS Pinecone Weaviate ChromaDB DeepSpeed FSDP Accelerate Horovod Ray Train MLflow Weights & Biases DVC ClearML Jupyter VS Code Linux Docker GitHub
01

Core Capabilities

End-to-end AI development and deployment

🧠

Deep Learning

Custom neural architectures for computer vision, NLP, and predictive analytics. Production-grade PyTorch and TensorFlow implementations with MLOps integration.

PyTorchTensorFlowCUDAONNX

MLOps

Automated training pipelines and scalable Kubernetes deployment.

🔒

Secure AI

GDPR-compliant systems with federated learning capabilities.

☁️

Cloud Architecture

Multi-cloud and hybrid deployments with infrastructure as code.

KubernetesDockerFastAPIRedis
📊

Data Engineering

Real-time pipelines and warehouse optimization.

🎯

AI Strategy

Roadmapping and technical due diligence.

02

How We Work

From concept to production in weeks, not years

01

Discovery

Deep dive into your business logic, data landscape, and success metrics.

02

Architecture

Design scalable systems with the right mix of cloud, edge, and on-premise.

03

Development

Agile sprints with continuous integration and model versioning.

04

Deployment

Production release with monitoring, A/B testing, and auto-scaling.

03

Flagship Product

Automated web deployment powered by AI

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