4 min read
safeAI
Deploy enterprise AI capabilities in weeks, not months. Hybrid MCP architecture with ECS Fargate client and Lambda servers for optimal cost and performance.
Security
Scalability
Cost Savings
What is safeAI?
safeAI is a unified solution that addresses the technical challenges of AI integration while maximizing AWS investments. It features a hybrid architecture with MCP Client on ECS Fargate and MCP Servers on Lambda, functioning as a landing zone for AI implementation that can be extended to support any use case.
Your Engineers Should Be Building AI Solutions, Not Integration Points
Stop letting integration complexity delay your AI adoption. safeAI delivers the enterprise-grade security, knowledge management, and model access your team needs to build business value, not infrastructure.
Eliminate Security and Compliance Barriers
Security concerns, data sovereignty requirements, and compliance obligations often stall AI initiatives. safeAI provides a secure foundation with enterprise-grade controls that protects your sensitive data while enabling powerful AI capabilities.
Accelerate AI Time-to-Value
Imagine deploying secure, enterprise-grade AI integrations in two weeks instead of six months. With safeAI, you transform the economics of AI implementation through pre-built components, standardized protocols, and AWS-native services.
Our Solution
A complete landing zone for integrating AWS Bedrock AI capabilities into your enterprise applications securely and efficiently.
Hybrid MCP Architecture
MCP Client runs on ECS Fargate for reliable, always-on connectivity while MCP Servers execute on Lambda for cost-effective, event-driven processing. This hybrid approach optimizes both performance and costs while connecting your applications to AWS Bedrock models.
Enterprise-Grade Security
Your data remains protected and under your control with AWS IAM, KMS, and Secrets Manager. All communications are encrypted with granular access controls that meet stringent regulatory requirements.
Intelligent Knowledge Management
Documents uploaded to S3 trigger Lambda-based MCP servers for automatic processing. Vector embeddings are generated via AWS Bedrock and stored in Aurora PostgreSQL Serverless v2, enabling semantic search across your organization's knowledge with event-driven efficiency.
Your AI Transformation
How your organization's experience changes with safeAI
From Stalled Projects to Rapid Deployment
Stop watching your AI initiatives get stuck in lengthy proof-of-concept phases. With safeAI, you can move from concept to production in just 2 weeks, allowing your team to demonstrate tangible AI value to stakeholders and gain competitive advantage.
From Data Silos to Intelligent Knowledge
End the frustration of disconnected information sources. safeAI's knowledge base integration converts your documents and data into intelligent vector embeddings that your AI models can securely access, creating a single source of truth for your organization.
From Security Concerns to Confidence
Transform security from a blocker to an enabler. safeAI's enterprise-grade security architecture lets you implement AI capabilities with the confidence that your sensitive data remains protected at all times, meeting the most stringent regulatory requirements.
From Model Lock-in to Flexibility
Avoid being tied to yesterday's AI technology. safeAI's Model Context Protocol implementation creates a standardized interface that allows you to easily switch between AWS Bedrock models as they evolve, future-proofing your AI investments.
From Custom Development to Proven Patterns
Stop reinventing the integration wheel for each AI project. safeAI provides a tested hybrid framework with MCP Client on ECS Fargate for reliability and MCP Servers on Lambda for cost efficiency, reducing integration costs by 40-50% compared to custom development approaches.
Answering Your Questions
Common questions about AI integration with safeAI
"How does safeAI ensure the security of our sensitive data?"
safeAI implements a comprehensive security architecture with AWS IAM, KMS, and Secrets Manager to protect your data. All communications are encrypted, access is granularly controlled, and your data remains within your AWS account, giving you complete data sovereignty.
"What AI models does safeAI support?"
safeAI is built to work with AWS Bedrock models, including Claude 3. The architecture allows for easy switching between models as your needs evolve, without having to rebuild your integrations.
"How does the knowledge base integration work?"
Documents uploaded to your S3 bucket are automatically processed by AWS Bedrock, with vector embeddings stored in Aurora PostgreSQL Serverless v2 or OpenSearch. This enables semantic search across your organization's knowledge, ensuring AI responses are accurate and aligned with your company data.
"What is Model Context Protocol (MCP) and why is it important?"
MCP is a standardized protocol for connecting AI models to various data sources and tools. It's important because it creates a consistent interface between your applications and AI models, allowing for flexibility and scalability as your AI needs evolve.
"How long does implementation typically take?"
While traditional AI integrations can take 6+ months, our implementation is typically completed in 2 weeks. This rapid timeline is possible because of our pre-built components, standardized framework, and AWS-native approach.
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