AI Development

LangChain is a framework for building applications powered by large language models (LLMs) like GPT-4/5, Claude 4.5, Gemini 2.5, and Llama 4. It provides memory management, tool integration, and AI agent orchestration. We use LangChain with LangGraph, CrewAI, AutoGen, and Microsoft Semantic Kernel for production AI systems.

LangChain accelerates development by handling conversation memory automatically, enabling LLM switching (GPT-4/5, Claude 4.5, Gemini 2.5) without code changes, and connecting LLMs to external tools. Best for chatbots with memory, AI agents, RAG systems, and multi-step workflows. Includes production-ready error handling and LangSmith monitoring.

RAG (Retrieval-Augmented Generation) combines LLMs with your own documents and data. RAG retrieves relevant information from your knowledge base before generating responses. This eliminates hallucinations and ensures answers come from your actual content, not the model's general knowledge.

Use RAG for large knowledge bases (documentation, policies), frequently updated content LLMs don't know, proprietary data that can't be in training data, or when you need source citations. Common use cases: enterprise knowledge bases, customer support chatbots, legal document search, medical literature review, compliance Q&A.

GPT-4 excels at complex reasoning, coding assistance, math, and creative writing. GPT-4 Turbo has 128K token context. We also work with GPT-5 series (gpt-5, gpt-5-mini, gpt-5-nano, gpt-5-chat) for enhanced capabilities. For HIPAA/GDPR compliance, use Azure OpenAI Service.

Claude 4.5 Sonnet and Claude 4.1 Opus excel at processing long documents (200K+ token context), detailed analysis, and safe responses. Claude 4.5 Haiku offers fast, cost-effective processing. Use Claude for long-context understanding, document analysis, technical writing, and applications requiring high accuracy and reliability.

Meta Llama (Llama 4, Llama 3.3, Llama 3.2 Vision) is best for cost optimization and on-premise deployment. It's open-source and runs on your infrastructure (RunPod, Lambda Labs, Vast.ai). Use Llama for budget constraints, highly sensitive data, or when you need full control without vendor lock-in.

An AI agent is an autonomous system that reasons, makes decisions, uses tools, and takes actions to achieve goals. Unlike chatbots, agents break down complex tasks, use multiple tools (search, APIs, databases), and execute workflows autonomously. We build agents using LangChain, CrewAI, AutoGen, OpenAI Swarm. Example: Recruitment agent reduced HR from 3 to 1 person.

Chatbots respond with predefined answers and can't take actions. AI agents autonomously decide steps, use external tools (search, databases, APIs), break complex tasks into sub-tasks, and execute workflows. Real example: Voice sales agent eliminated 3 full-time sales staff with 24/7 availability.

Timelines vary: MVP/proof-of-concept 4-6 weeks, simple AI integrations 6-8 weeks, RAG systems 8-12 weeks, custom AI agents 12-16 weeks, enterprise platforms 24-40 weeks. You'll see working prototypes within 2-3 weeks with weekly demos.

Yes, we integrate AI into existing Laravel, MERN, MEVN, and Python applications without rebuilds. Examples: The AsBuilt (Laravel + AI chat), KnoCommerce (Vue.js + AI analytics). We add AI as modular features with zero downtime. Cost: $15,000-$80,000, Timeline: 6-12 weeks.

Yes, we build HIPAA-compliant AI using Azure OpenAI Service (BAA-covered) or on-premise Llama 4. We implement AES-256 encryption, role-based access control, audit logging, and PHI data isolation. All projects include Business Associate Agreement (BAA) execution. HIPAA compliance adds 15-20% to project cost.

Yes, we build GDPR-compliant AI with EU-only data centers (AWS eu-central-1, Azure Europe), right to deletion, data minimization, and privacy by design. We serve Germany (Grundsteuer Digital - 7-partner SaaS), UK, and other EU countries. All projects include Data Protection Impact Assessments (DPIAs).

AI automation delivers 30% operational cost reduction, 50% efficiency improvements, and 40% enhanced customer satisfaction. Real examples: Recruitment automation (3 FTE→1, 8hr→2hr processing, savings = 2 annual salaries), Voice sales agent (eliminated 3 FTE, 24/7 availability). ROI timelines average 6-12 months.