AI Technologies & Platforms

Deep expertise across the modern AI technology stack, from enterprise LLM platforms to workflow automation tools and vector databases.

We're platform-agnostic consultants who recommend the best technology fit for your specific use case, budget, and technical requirements. Our hands-on experience spans the full AI ecosystem, enabling us to design solutions that integrate seamlessly with your existing infrastructure.

Large Language Models (LLMs)

Enterprise-grade AI models for natural language processing, content generation, and intelligent automation.

ChatGPT / OpenAI

GPT-3.5, GPT-4, GPT-4 Turbo API integration, fine-tuning, and custom implementations for enterprise applications.

Claude (Anthropic)

Claude 3.5 Sonnet, Claude 3 Opus for long-context tasks, document analysis, and complex reasoning.

Best for Analysis

Azure OpenAI

Enterprise-ready OpenAI models with Microsoft's security, compliance, and global infrastructure.

Enterprise Choice

AWS Bedrock

Access to Claude, Llama, and other foundation models through AWS infrastructure with enterprise controls.

Google Vertex AI

PaLM, Gemini, and other Google AI models for enterprises using Google Cloud Platform.

Open Source Models

Llama, Mistral, and other open-source LLMs for self-hosted, cost-effective solutions.

Vector Databases & RAG Systems

Build semantic search, recommendation engines, and knowledge retrieval systems with enterprise-grade vector databases.

Pinecone

Fully managed vector database for production-scale semantic search and RAG applications.

Weaviate

Open-source vector database with hybrid search combining keyword and semantic capabilities.

ChromaDB

Open-source embedding database designed for LLM applications and local development.

Qdrant

High-performance vector search engine with advanced filtering and clustering capabilities.

FAISS

Meta's library for efficient similarity search and clustering of dense vectors.

RAG Architecture

Document chunking, embeddings, retrieval strategies, and re-ranking for optimal results.

Workflow Automation Platforms

Connect AI capabilities to your existing tools and automate complex business processes without code.

n8n

Open-source, self-hosted workflow automation with AI integrations and custom logic.

Most Flexible

Make (Integromat)

Visual automation platform with advanced data transformation and AI tool integrations.

Best Visual UI

Zapier

Most extensive app ecosystem for quick integrations and simple automation workflows.

Easiest to Use

AI Development Frameworks

Build sophisticated AI applications faster with proven frameworks and development tools.

LangChain

Most popular framework for building LLM applications with chains, agents, and memory.

LlamaIndex

Data framework for connecting custom data sources to LLMs with RAG capabilities.

Haystack

End-to-end framework for building search systems and question-answering applications.

Semantic Kernel

Microsoft's SDK for integrating LLMs with conventional programming languages.

Claude Code

AI-powered development assistant for code generation and software engineering tasks.

GitHub Copilot

AI pair programmer for code completion and development acceleration.

Cloud AI Platforms

Enterprise cloud platforms providing AI infrastructure, model hosting, and managed services.

AWS AI Services

Bedrock, SageMaker, and comprehensive AI/ML services on Amazon's cloud infrastructure.

Microsoft Azure AI

Azure OpenAI, Cognitive Services, and enterprise AI tools with Microsoft ecosystem integration.

Google Cloud AI

Vertex AI, PaLM API, and Google's AI platform for scalable machine learning solutions.

Additional AI Capabilities

Document Processing

• Intelligent document extraction and analysis
• PDF, Word, Excel processing with LLMs
• OCR and document classification
• Form data extraction and validation

Embedding Models

• OpenAI text-embedding-3-large/small
• Cohere embeddings for semantic search
• Open-source sentence transformers
• Custom embedding fine-tuning

Prompt Engineering

• Chain-of-thought prompting techniques
• Few-shot and zero-shot optimization
• System message engineering
• Prompt templates and versioning

Machine Learning

• TensorFlow and PyTorch implementations
• scikit-learn for classical ML
• Hugging Face model integration
• Custom model training and fine-tuning

How We Help You Choose

With so many AI technologies available, selecting the right stack is critical. We evaluate your specific requirements across multiple dimensions:

Use Case Fit

Match technology capabilities to your specific application requirements, performance needs, and integration constraints.

Security & Compliance

Evaluate data privacy, regulatory compliance, and security features for your industry and geographic requirements.

Cost Optimization

Balance API costs, infrastructure expenses, and development effort to maximize ROI over the project lifecycle.

Scalability & Performance

Ensure the technology stack can scale with your growth and meet performance SLAs for production workloads.

Need Help Choosing the Right AI Stack?

Let's discuss your specific requirements and design a technology solution that delivers results.

Schedule a Consultation