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AI & Machine
Learning
Development

We build intelligent AI solutions that transform operations and create competitive advantage. From GPT-powered chatbots to custom ML models, we deliver AI that solves real business problems, not just demos.

OpenAI LangChain Python TensorFlow
AI Solutions

Intelligence that delivers ROI

We focus on AI that creates measurable business value. No black boxes, no hype—just practical solutions that automate workflows, enhance decision-making, and improve customer experiences.

AI Chatbots & Assistants

GPT-powered conversational AI that actually understands context. Customer support, internal helpdesks, and domain-specific assistants trained on your data.

  • RAG (Retrieval-Augmented Generation)
  • Multi-channel deployment
  • Human handoff workflows

Predictive Analytics

Machine learning models that forecast trends, identify risks, and optimize operations. Churn prediction, demand forecasting, anomaly detection.

  • Customer churn prediction
  • Sales & demand forecasting
  • Fraud & anomaly detection

Recommendation Engines

Personalization that increases engagement and revenue. Product recommendations, content curation, next-best-action suggestions.

  • Collaborative filtering
  • Content-based filtering
  • Real-time personalization

Document Intelligence

Automated document processing, data extraction, and intelligent search across your knowledge base.

  • Invoice & contract processing
  • Semantic search
  • Knowledge base Q&A

Computer Vision

Image and video analysis for quality control, object detection, and visual inspection systems.

  • Defect detection
  • Object recognition
  • Visual search

AI Workflow Automation

Intelligent process automation that goes beyond simple rules. AI agents that handle complex, multi-step workflows.

  • AI agent orchestration
  • Tool use & function calling
  • Human-in-the-loop systems
Technology Stack

Built on proven foundations

We leverage cutting-edge AI platforms while maintaining practical engineering principles. Our solutions are production-ready, scalable, and maintainable.

GPT

OpenAI / Azure OpenAI

GPT-4, embeddings, function calling

LC

LangChain

Chains, agents, RAG pipelines

TF

TensorFlow / PyTorch

Custom model training

HF

Hugging Face

Open-source models, fine-tuning

What We Deliver

AI solutions that work in production

We don't just build demos—we deliver production-ready AI systems with proper error handling, monitoring, and maintainability.

01

Custom AI assistants and chatbots

02

Natural language processing

03

Predictive analytics

04

Recommendation engines

05

Computer vision solutions

06

AI integration and automation

Transparent Pricing

AI Development Investment Guide

Starter
$30K - $100K

Chatbots, basic ML models, single-use-case solutions

  • GPT-powered chatbots
  • RAG implementations
  • Basic classification models
Most Popular
Growth
$100K - $300K

Custom ML models, multi-model systems, integrations

  • Custom ML model training
  • Recommendation engines
  • Predictive analytics
Enterprise
$300K - $1M+

Multi-model platforms, complex pipelines, enterprise scale

  • Enterprise AI platforms
  • Model fine-tuning
  • MLOps infrastructure
Our Process

From concept to production

AI projects require a different approach. We start with proof of concepts and iterate based on real-world performance.

01

Discovery & Data

Assess feasibility, identify data sources, define success metrics

02

Proof of Concept

Rapid prototype to validate approach and demonstrate value

03

Development

Build production system, train/tune models, integrate

04

Deploy & Monitor

Launch, monitor performance, continuous improvement

Common Questions

AI Development FAQ

Do I need a lot of data to use AI?

Not always. It depends on the type of AI solution:

  • LLM-based solutions (chatbots, document processing) can work with minimal data using prompt engineering and RAG
  • Traditional ML models typically need 1,000-10,000+ labeled examples
  • Deep learning requires larger datasets, but transfer learning can help

We help identify, clean, and augment data sources.

How do you handle AI hallucinations and accuracy?

We implement multiple safeguards:

  • RAG: Ground responses in your actual data
  • Output validation: Structured outputs, fact-checking
  • Confidence scoring: Flag uncertain responses
  • Human-in-the-loop: Critical decisions route to humans

Should I use OpenAI or open-source models?

Both have their place:

  • OpenAI/Azure OpenAI: Best-in-class capabilities, faster to deploy, ongoing API costs
  • Open-source (Llama, Mistral): Lower running costs, full control, requires more infrastructure

We often start with OpenAI for rapid prototyping, then evaluate alternatives based on cost, performance, and data sensitivity.

Related Services

Complete your AI solution

Web Development

Build the applications that deliver your AI to users

Cloud & DevOps

Scalable infrastructure for AI model deployment

Strategy & Consulting

AI roadmap and use case prioritization

Ready to
transform?

Whether you're launching a new product, modernizing legacy systems, or scaling your digital capabilities—let's build something remarkable together.

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