Sold by: Praxis AIÂ
AI THAT PUTS HUMANS FIRST. Your Expertise. Your Control. Your Success. Enterprise AI middleware platform transforming human expertise into scalable digital intelligence through authentic digital experts and MCP-powered AI orchestration serving education, enterprise, and workforce development. Unlike generic AI solutions, our digital twins preserve institutional knowledge with human reasoning patterns, delivering 70% engagement rates vs 14% for basic chatbots across 500+ implementations. Built on AWS Bedrock with Model Context Protocol integration for seamless multi-LLM orchestration, our platform creates personalized digital experts providing 24/7 knowledge access while maintaining data sovereignty. Trusted by Notre Dame, DeVry, Clemson, and enterprise clients like Canadian Bar Association processing 1B+ tokens monthly with zero data breaches and complete regulatory compliance.
Overview
Praxis AI is the enterprise middleware platform that revolutionizes knowledge management by transforming human expertise into scalable digital intelligence through authentic digital twins, digital experts, and advanced Model Context Protocol (MCP) integration. Unlike generic AI chatbots that provide basic responses, our platform creates sophisticated digital replicas of subject matter experts that preserve institutional knowledge, maintain human reasoning patterns, and deliver personalized guidance 24/7 with enterprise-grade security. Built on AWS Cloud infrastructure with MCP-enabled LLM-agnostic architecture, Praxis AI seamlessly orchestrates OpenAI, Anthropic, Gemini, AWS Bedrock, and other leading AI models through standardized context protocols while ensuring complete data sovereignty and zero proprietary data exposure. Our digital experts serve any industry because we don't create, we enable, amplifying human expertise without replacing it and providing specialized knowledge access that scales human expertise across global operations.
The platform delivers measurable impact with proven results across 500+ digital expert implementations: 70% user engagement rates versus 14% for traditional chatbots, 35% improvement in learning outcomes, students achieving full letter grade increases, and enterprise clients reporting significant productivity gains and knowledge retention improvements. Healthcare systems deploy digital expert physicians for 24/7 clinical decision support and medical education, financial institutions leverage compliance experts for regulatory adherence across distributed teams, manufacturing organizations preserve decades of operational knowledge from senior engineers through MCP-powered knowledge transfer, professional services firms scale expertise across global consulting practices, and government agencies maintain institutional knowledge through leadership transitions. Trusted by prestigious institutions including Notre Dame, DeVry, Canadian Bar Association, NCAA, Concussion Legacy Foundation, Clemson University, and Alabama State University, and more. Praxis AI processes over 1 billion tokens monthly with zero security breaches.
Enterprise-grade security and compliance capabilities include AWS Cloud infrastructure, Model Context Protocol standardization for secure AI model communication, FERPA and ADA508 compliance, HECVAT documentation, dedicated instances with enterprise encryption, complete data sovereignty, and seamless integration through REST APIs and LMS connectors. Originally proven in higher education's rigorous governance environment, our MCP-powered platform has successfully expanded to enterprise sectors with proven scalability frameworks that ensure regulatory compliance, institutional knowledge preservation, workforce development excellence, and authentic human-AI collaboration that enhances rather than replaces human expertise across all organizational levels.
Highlights
- Enterprise AI middleware platform creating digital twins of experts with 70% engagement rates and 35% learning improvement - proven across education, enterprise, and workforce development sectors.
- LLM-agnostic architecture orchestrating multiple AI models (OpenAI, Anthropic, AWS Bedrock) with enterprise security, FERPA compliance, and zero data leakage to external LLMs.
- Seamless LMS integration and enterprise APIs enabling scalable deployment of personalized AI professors, tutors, mentors, and advisors with institutional knowledge preservation.
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Pricing
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Dimension | Description | Cost/24 months |
|---|---|---|
Tier-1: 9,000 Credits | A bundle of 9,000 credits - 24 month expiration | $1,000.00 |
Tier-2: 25,000 Credits | A bundle of 25,000 credits - 24 month expiration | $2,750.00 |
Tier-3: 50,000 Credits | A bundle of 50,000 credits - 24 month; 10% discount | $5,000.00 |
Tier-4: 100,000 Credits | A bundle of 100,000 credits - 24 month; 15% discount | $9,500.00 |
Tier-5: 500,000 Credits | A bundle of 500,000 credits - 24 month; 25% discount | $41,500.00 |
Vendor refund policy
Any customer may request a refund of unused credits by providing a formal request to support@praxis-ai.com with 30-days notice. There will be a 20% refund fee deducted from any refund.
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Support
Vendor support
Support details: Praxis AI provides comprehensive enterprise support including dedicated technical assistance, implementation guidance, and ongoing platform optimization. Contact support@praxis-ai.com or humans@praxis-ai.com for technical assistance. Enterprise Security & Compliance: AWS Cloud infrastructure with enterprise-grade encryption, FERPA compliance, ADA508 accessibility standards. HECVAT and VPAT available upon request. Security certifications: https://aws.amazon.com/compliance/programs/ Integration Support: Multiple integration options including Canvas LMS Custom Theme (preferred) and LTI 1.3. Comprehensive onboarding with technical documentation and video tutorials. Contact david@praxis-ai.com for implementation assistance. Privacy & Data Protection: Complete data sovereignty with dedicated AWS instances. Privacy policy: https://praxis-ai.com/privacy-policy/ | Terms of Use:
AWS infrastructure support
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AI generated from product descriptions
Multi-Model AI Orchestration
LLM-agnostic architecture capable of seamlessly integrating and orchestrating multiple AI models including OpenAI, Anthropic, Gemini, and AWS Bedrock
Contextual Knowledge Preservation
Advanced Model Context Protocol (MCP) enabling digital replicas that maintain human reasoning patterns and institutional knowledge
Enterprise Security Framework
Comprehensive security infrastructure with dedicated instances, enterprise encryption, complete data sovereignty, and zero proprietary data exposure
Compliance and Governance
Supports FERPA and ADA508 compliance with HECVAT documentation and standardized secure AI model communication protocols
Digital Expert Creation
Automated generation of sophisticated digital twins that provide personalized, context-aware guidance across multiple organizational domains
Local Language Model Execution
Enables direct execution of large language models on local machines without cloud dependencies
Model Customization Framework
Provides capabilities to modify, create, and tailor AI models for specialized applications
API Integration Mechanism
Supports OpenAI-compatible API integration with multiple external language model platforms
Web Search Retrieval Augmentation
Implements web search capabilities for Retrieval Augmented Generation (RAG) using multiple search providers
Multi-Modal Content Generation
Integrates image generation capabilities through local and external APIs to enhance conversational experiences
Recommendation Algorithm
AI-driven content suggestion system using machine learning techniques to analyze user study patterns
Personalization Engine
Dynamic learning pace adjustment based on data-driven user interaction insights
Multi-Language Support
Adaptive recommendation and learning content processing across multiple language frameworks
Content Mapping
Real-time contextual analysis of study materials for relevant additional resource suggestions
Adaptive Learning Technology
Intelligent system that customizes instructional speed and complexity based on individual user performance metrics
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