Generative AI, in production.
We help teams put generative AI into production on Amazon Bedrock — starting with the use cases that pay for themselves, and running it inside your own AWS account so your data stays yours.
Start a Conversation →60-80%
Efficiency Gains
2-4 wk
To Proof of Concept
5+
Foundation Models
Our GenAI services
End-to-end GenAI solutions.
Four things we get asked for most, whether you're scoping a first pilot or scaling something that already works.
LLM Implementation
Deploy large language models in your enterprise. We handle integration with your existing systems, security, and compliance.
Custom Model Fine-Tuning
Train AI models on your proprietary data. Get industry-specific accuracy that off-the-shelf models can't deliver.
RAG Solutions
Retrieval-Augmented Generation systems that ground AI responses in your company's knowledge base.
AI Strategy Consulting
Not sure where to start? Our fixed-scope AWS AI Assessment pinpoints high-ROI GenAI opportunities and hands you a buildable roadmap.
AWS grants this competency for generative AI consulting specifically — after reviewing the architectures and talking to the customers running them. It is not the same thing as an AI-adjacent partner badge.
Proven in production
Use cases we've delivered.
A few things we've shipped for enterprise clients, with the numbers they moved.
70%
Document Processing Automation
Reduced document processing time by 70% for enterprise clients using GenAI-powered extraction and classification.
60%
Customer Service AI
Deployed conversational AI that handles 60% of support queries automatically while maintaining brand voice.
1000s
Knowledge Base Q&A
Built RAG systems that let employees query thousands of internal documents in natural language.
Keep exploring
Related services.
AI & ML Development
Agentic workflows, RAG, fine-tuning, and production ML on Bedrock & SageMaker.
Intelligent Document Processing
Extract, classify, route, and validate every document type at 95%+ accuracy.
AWS Cloud Consulting
Cloud strategy, architecture review, and cost optimization, led by former AWS engineers.