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Documentation Index

Fetch the complete documentation index at: https://docs.praxis-ai.com/llms.txt

Use this file to discover all available pages before exploring further.

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Why Switch to Praxis-AI Middleware?

Praxis-AI middleware transforms how organizations leverage AI by providing a sophisticated orchestration layer that connects your existing systems with multiple AI models while maintaining complete control, security, and flexibility.

LLM-Agnostic Architecture

Seamlessly switch between OpenAI, Anthropic Claude, Google Gemini, Mistral AI, xAI Grok, Stability AI (image/audio/video), AWS Bedrock (Nova, Titan, Llama), and custom models without vendor lock-in

Enterprise Security

Bank-level encryption, SOC 2 compliance, FERPA & COPPA adherence, complete data sovereignty with zero proprietary data exposure

Proven Performance

70% user engagement rates vs 14% for traditional chatbots, with 35% improvement in learning outcomes across 500+ implementations

Cost Optimization

Intelligent token management and model routing reduces AI costs by up to 40% while maintaining quality

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Bring Your Own Token (B.Y.O.T.)

Switching to Praxis-AI middleware is seamless. Use your existing API keys and credit pools across all major AI platforms.

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Supported AI Platforms

Praxis-AI middleware provides native integration with industry-leading AI platforms:
Connect your OpenAI API key to access:
  • GPT-5, GPT-5-mini for generation
  • DALL-E 3 for image generation
  • Whisper for speech-to-text
Configuration: Simply add your API key in Edit → Configuration and Integrations
Leverage your AWS Bedrock access for:
  • Anthropic: Claude Sonnet 4, Claude Sonnet 4.5, Claude Haiku 4.5
  • Amazon Nova: Premier, Pro, Lite, Micro
  • Meta Llama: Llama 4x
  • Mistral AI: Mistral Large
  • Amazon Titan: Text, Embeddings, Multimodal
Configuration: Authenticate via AWS IAM credentials or access keys
Integrate with Google’s AI ecosystem:
  • Gemini 2.5 Pro, Gemini 2.5 Flash
  • Gemini Live (real-time voice)
  • Vertex AI models
Configuration: Add your Google AI API key in Edit → Configuration and Integrations
Access Mistral’s high-performance models:
  • Mistral Large, Mistral Medium
  • Codestral (code-focused)
  • Voxtral (voice TTS/STT)
Configuration: Add your Mistral API key in Edit → Configuration and Integrations
Access xAI’s Grok models:
  • Grok-4.20, Grok-4 Fast for conversation and vision
  • Grok Code Fast for code-focused tasks
  • Grok Imagine for image generation
  • Text-to-Speech (5 voices: Eve, Ara, Rex, Sal, Leo)
  • Embeddings (grok-embedding-small)
  • Real-time voice conversations (Grok-3 Fast)
Configuration: Add your xAI API key in Edit → Configuration and Integrations
Access Stability AI’s generative media models:
  • Image Generation: Stable Image Ultra, Stable Image Core, SD 3.5 Large
  • Audio Generation: Stable Audio 2 (text-to-audio, up to 190 seconds)
  • Video Generation: Stable Video (image-to-video, 4 seconds fixed)
Stability AI is a dedicated media-generation provider — conversation models from other providers invoke the generate_image, generate_audio, and generate_video tools that route to Stability automatically.Configuration: Add your Stability AI API key in Edit → Configuration and Integrations
Connect to any AI model via REST API:
  • Self-hosted models (Ollama, vLLM, TGI)
  • LiteLLM proxy endpoints
  • Azure OpenAI Service
  • Custom fine-tuned models
Configuration: Provide endpoint URL + API key/bearer token

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How It Works

Configure Your Models

Navigate to Configuration → Personalization and AI Models and add your API credentials for each platform you want to use.
You can configure multiple models simultaneously and switch between them based on use case, cost, or performance requirements.

Set Model Preferences

Define which models to use for different Digital Twins or conversation types:
  • High-reasoning tasks: Claude Sonnet 4, GPT-5.2, Gemini 2.5 Pro
  • Fast responses: Claude Haiku 4.5, Gemini Flash, Amazon Nova Lite
  • Cost-sensitive operations: Amazon Nova Micro, GPT-5-mini
  • Specialized domains: Custom fine-tuned models

Enable Intelligent Routing

Praxis-AI’s Neural Engine automatically routes requests to the optimal model based on:
  • Query complexity and context
  • Token budget and cost constraints
  • Model availability and latency
  • User preferences and history

Monitor & Optimize

Track usage, performance, and costs across all models through the Analytics dashboard. Adjust routing rules to optimize for your specific needs.

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Key Advantages Over Direct API Integration

Unified Interface

Single API for all AI models eliminates integration complexity and reduces development time by 80%

Automatic Failover

If one model is unavailable or rate-limited, route requests to alternative models

Context Management

Persistent conversation memory and RAG vector search across all models with institutional knowledge prioritization

Token Optimization

Intelligent prompt compression and caching reduces token consumption by up to 60%

Compliance Built-In

Automatic PII detection, content filtering, and audit logging for regulatory compliance

No Vendor Lock-In

Switch models instantly without code changes or data migration

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Migration Path

Switching from direct API integration to Praxis-AI middleware requires minimal changes to your existing infrastructure.

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Three-Step Migration

  1. Add Praxis-AI SDK: Install the middleware SDK alongside your existing AI integrations
  2. Configure Models: Import your existing API keys into Praxis-AI’s model configuration
  3. Update Endpoints: Point your application to Praxis-AI’s unified API endpoint

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Zero Downtime Migration

Run Praxis-AI middleware in parallel with your existing integration during the transition period. Gradually shift traffic to validate performance before full cutover.

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Enterprise Features

Praxis-AI implements the Model Context Protocol standard for seamless multi-LLM orchestration, enabling standardized context sharing across different AI models and providers.
Secure storage for institutional knowledge with hierarchical access:
  1. LMS Content such as Canvas
  2. IP Vault proprietary content
  3. Trusted external sources
All content is encrypted and access-controlled with role-based permissions.
Create sophisticated AI experts that preserve human reasoning patterns and institutional knowledge. Each Digital Twin can use different models optimized for their specific domain.
Comprehensive dashboards tracking:
  • Token usage and costs per model
  • Response quality and user satisfaction
  • Model performance comparisons
  • ROI and efficiency metrics

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Pricing & Cost Optimization

Praxis-AI middleware adds minimal overhead while providing significant cost savings through intelligent routing and token optimization.

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Cost Structure

  • Middleware Fee: Credit-based system pay as you go ir in bundles and save
  • AI Model Costs: Large discounts when using your own API keys
  • No Hidden Fees: Transparent pricing with volume discounts available

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Typical Savings

Organizations using Praxis-AI middleware report:
  • 40% reduction in AI costs through model routing
  • 60% fewer tokens consumed via prompt optimization
  • 80% less development time compared to managing multiple direct integrations

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Getting Started

Sign Up

Create your Praxis-AI account at https://pria.praxislxp.com or through AWS Marketplace

Create Digital Twin

Set up your first Digital Twin and run the personalization assistant in Configuration → Personalization and AI Models

Configure First Model

Configure your Digital Twin to use your API Token

Test & Deploy

Test conversations and deploy to your organization via LMS integration, Web SDK, or REST Apis

Need Help?

Contact our team for personalized onboarding assistance and technical support

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Additional Resources

Choose a model

Personalize your Digital Twin models

Configurare your API Keys

API Keys Configuration for your Digital Twin

Integrate your Digital Twin

Integrate your Digital Twin

Connect via our APIs

Complete API reference and integration guides

Adding Credits

Adding credits in 3 steps