Scalable, Secure, and Built on AWS.
Simplify the complexity of large language models (LLMs) with our full-stack AI platform. Streamline fine-tuning, deployment, and monitoring to build enterprise-grade AI applications faster and more efficiently.
A robust set of tools designed to take models from experiment to production.
Swap between models like Claude 3.5, Llama 3, and Titan with a single API call. No migration overhead.
Integrated safety layers using AWS Guardrails to filter toxicity and ensure compliance in real-time.
Serverless deployment on AWS Lambda and Fargate for cost-efficient inference at any scale. Utilize AWS Inferentia and Trainium chips to reduce model running costs by up to 50%.
Enterprise-grade model management for the full AI lifecycle
Track model versions, compare performance, and roll back to previous iterations with ease.
Run parallel model deployments to test performance and select the optimal configuration.
Enterprise-grade security with VPC isolation, data encryption, and AWS IAM integration.
ModelStack is architected to utilize the full depth of AWS AI services, ensuring that your model stack is secure, scalable, and globally available.
Deploy and orchestrate models with just a few lines of code
from modelstack import Stack
# Initialize the stack with AWS Bedrock
ms = Stack(region="us-east-1", provider="bedrock")
# Route queries dynamically based on cost/performance
response = ms.route(
prompt="Analyze this financial report",
strategy="best_value",
max_tokens=2048
)
print(response.model_used) # 'anthropic.claude-3-sonnet'
print(response.cost) # '$0.0023'
# Deploy custom model to SageMaker
endpoint = ms.deploy(
model_id="my-finetuned-llama",
instance_type="ml.g5.xlarge",
auto_scaling=True
)
Enterprise-grade reliability and security
Native support for Pinecone and AWS OpenSearch
Private cloud and edge deployment options
Curated collection of pre-trained models
VPC Isolation
End-to-End Encryption
AWS IAM Integration
SOC 2 Compliance
Audit Logging
Built on the full power of AWS AI services. Our platform leverages Amazon Bedrock & SageMaker to deliver enterprise-grade AI capabilities. Using AWS Inferentia and Trainium chips, we reduce model running costs by up to 50% for our customers.
We are currently expanding our AWS infrastructure and seeking AWS Activate support to accelerate our growth and further enhance our AWS-native capabilities.