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
# Production LLM 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=1024) return t.decode(y[0])
Technology Stack:
01
Enterprise AI Services
Custom AI development for production. We ship systems that scale.
Deep Learning & Neural Networks
LLM Fine-Tuning & RAG
AI-Powered Web Apps
MLOps & Model Serving
GDPR-Compliant AI
AI Strategy & Consulting
02
How We Deliver
From first call to production in weeks — not quarters
01
Discovery Call
02
Architecture Design
03
Agile Development
04
Production Launch
03
Trusted Infrastructure
We build on proven, open-source foundations — no vendor lock-in
Hugging Face Ecosystem
Multi-Cloud Deployment
MLOps Toolchain
SMALL // MVP
2–6 weeks · MVP with web interface
- ✓ Web Application MVP
- ✓ React/Vue Frontend + FastAPI
- ✓ Basic AI/ML integration
- ✓ Docker + cloud deployment
- ✓ 2 weeks post-launch support
Popular
MEDIUM // PRODUCTION
6–12 weeks · Full-stack AI platform
- ✓ Microservices architecture
- ✓ LLM fine-tuning or RAG pipeline
- ✓ CI/CD + automated testing
- ✓ Monitoring (Grafana/Prometheus)
- ✓ 4 weeks support & optimization
ENTERPRISE // PLATFORM
12–24 weeks · Distributed AI systems
- ✓ Custom DL + LLM pipelines
- ✓ Kubernetes + hybrid cloud
- ✓ SSO, RBAC & GDPR compliance
- ✓ 24/7 monitoring & SLA
- ✓ 3 months dedicated support
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