ModelStack simplifies the complexity of the AI lifecycle. Standardize your model evaluation, deployment, and optimization on a single, unified stack built on AWS Bedrock.
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.
ModelStack is architected to utilize the full depth of AWS AI services, ensuring that your model stack is secure, scalable, and globally available.
Our Python SDK and CLI make model orchestration a breeze.
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'
We are currently expanding our AWS SageMaker training cluster and seeking AWS Activate support to subsidize Inference/Fine-tuning on H100 (p5) and L40S (g6) instances.