AI & ML that ships.
Custom AI and ML built on Amazon Bedrock and SageMaker. We take on agentic workflows, RAG systems, fine-tuning, and the production pipelines that keep them running after launch.
Start a Conversation →2–4 wk
To First Prototype
5+
Foundation Models
100%
AWS-Native
Core capabilities
What we build.
Four things we build most often, from autonomous agents to the ML pipelines that keep them running in production.
Agentic AI Workflows
Build autonomous AI agents that reason, plan, and execute multi-step tasks. Bedrock Agents with tool use, memory, and guardrails for enterprise-safe automation.
RAG Systems
Retrieval-Augmented Generation pipelines using Bedrock Knowledge Bases, OpenSearch vector stores, and custom embedding strategies for grounded AI responses.
Model Fine-Tuning
Custom model training on your proprietary data using Bedrock fine-tuning or SageMaker. Industry-specific accuracy improvements that off-the-shelf models can't match.
MLOps & Production Pipelines
End-to-end ML lifecycle management with SageMaker Pipelines, model monitoring, A/B testing, and automated retraining for production-grade deployments.
The stack
AWS AI/ML technology stack.
We work across the full AWS AI/ML stack, from choosing the right foundation model to keeping it monitored once it's live.
Amazon Bedrock
Foundation Models
Claude, Titan, Llama, Mistral, Cohere
Knowledge Bases
Vector search, document ingestion, RAG pipelines
Agents
Tool use, action groups, guardrails
Fine-Tuning
Custom model training on proprietary data
Prompt Flows
Visual prompt chaining and orchestration
Amazon SageMaker
Training & Tuning
Distributed training, hyperparameter optimization
Model Deployment
Real-time endpoints, batch transform, serverless inference
Pipelines
ML CI/CD, model registry, automated retraining
Model Monitor
Data drift detection, model quality monitoring
Feature Store
Centralized feature management and sharing
Textract
Document AI
Comprehend
NLP
Translate
Multi-language
OpenSearch
Vector Search
Proven in production
Use cases we've delivered.
Real-world AI/ML implementations for enterprise clients across regulated industries.
Document Intelligence
AI-powered extraction, classification, and processing of complex documents — loans, invoices, medical records, contracts.
Conversational AI
Enterprise chatbots and virtual assistants grounded in your knowledge base with RAG, guardrails, and human escalation.
Predictive Analytics
ML models for demand forecasting, churn prediction, anomaly detection, and recommendation engines on SageMaker.
How we engage
Three ways to start.
Flexible engagement models to fit where you are — from first assessment to full production deployment.
01
AI Discovery & Strategy
Assessment of your operations to identify high-ROI AI opportunities with a clear implementation roadmap.
2-3 weeks
02
Proof of Concept
Build a working prototype to validate the approach, demonstrate value, and de-risk your investment.
3-4 weeks
03
Production Implementation
Full production deployment with CI/CD, monitoring, security, compliance, and ongoing optimization support.
8-16 weeks
Keep exploring
Related services.
Generative AI Consulting
GenAI use cases on Amazon Bedrock — compliance-first, from evaluation to production.
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.