Generative AI on AWS

From AI Pilot to
Production Scale

MDH builds production-ready Generative AI systems — not demos. We architect, build, and deploy AI agents, RAG pipelines, and intelligent automation on AWS Bedrock that deliver measurable ROI from day one.

85%
Task Automation Rate
10x
Faster Document Processing
$2.4M
Avg. Annual Savings Delivered
12 wks
Avg. Production Deployment
Solutions

Enterprise AI Built on AWS Bedrock

We go beyond chatbots. MDH builds production-grade AI systems with security, reliability, and enterprise governance built in.

AI Agents & Automation

Deploy autonomous AI agents on AWS Bedrock that plan, reason, and execute multi-step workflows — handling complex business processes without human intervention.

Bedrock Agents Tool Use Workflow Automation

RAG & Knowledge Bases

Build retrieval-augmented generation systems that ground LLM responses in your proprietary data — eliminating hallucinations and enabling domain-specific intelligence.

Bedrock KB OpenSearch Vector Databases

Conversational AI for CX

Next-generation virtual agents powered by Bedrock and Amazon Connect — handling complex, multi-turn customer conversations with human-level comprehension.

Amazon Lex Bedrock Claude Contact Center AI

Document Intelligence

Automate document ingestion, extraction, classification, and compliance review using Bedrock, Textract, and Comprehend in intelligent pipelines.

Textract Comprehend Document Automation

AI-Powered Analytics

Surface actionable insights from unstructured data — call transcripts, emails, documents — using Bedrock for summarization, classification, and prediction.

Contact Lens LLM Summarization Predictive Insights

AI Governance & Safety

Responsible AI implementation with prompt guard, output filtering, audit logging, and model evaluation frameworks aligned to enterprise compliance requirements.

Guardrails Model Evaluation Audit Trails
Foundation Models

The Right Model for Every Use Case

MDH has production experience with every major foundation model available on AWS Bedrock.

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Anthropic Claude

Complex reasoning, long-context document analysis, customer-facing agents

Amazon Titan

Embeddings, text generation, image analysis — AWS-native and enterprise-ready

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Meta Llama

Open-source flexibility for fine-tuning, cost-optimized deployments

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Mistral & Cohere

High-performance retrieval, embeddings, and multilingual use cases

Our Methodology

Why Most Enterprise AI Projects Fail — And How We Prevent It

Typical Approach

POC delivered. No plan for production. Data quality ignored. Security as an afterthought. Hallucinations in production.

The MDH Approach

Production-first design. Data strategy defined before code. Security and guardrails built in. Measured against KPIs from day one.

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Measurable Outcomes

Every AI project defines success metrics before kickoff — cost savings, task automation rate, latency, accuracy, and user adoption.

Get Started with AI

From AI Concept to Production in 12 Weeks

Book an AI readiness workshop. We'll assess your data, define high-impact use cases, and build a roadmap to production deployment.