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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.

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

Seamlessly switch between AI models such as OpenAI, Anthropic Claude, and Google Gemini without vendor lock-in. Use your existing API keys and credit pools across all major AI platforms.

Enterprise Security

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

One Knowledge Base, Every Model

Your IP Vault documents, assistants, tools, and conversation history work the same no matter which AI model answers — switch providers without rebuilding anything

Cost Optimization

Prompt caching discounts (cached input tokens are billed at a reduced rate), per-task model choices, and transparent credit accounting help you control AI costs

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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 3.1 Pro and the Gemini Flash family
  • 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)
Stability AI is a dedicated media-generation provider — conversation models from other providers invoke the generate_image and generate_audio tools that route to Stability automatically. (Video generation routes to Amazon Nova Reel or OpenAI Sora.)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 4.6, GPT-5.2, Gemini 3.1 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

Assign Models per Task

Each Digital Twin can use a different model for each kind of work — conversation, summaries, image generation, image analysis, audio transcription, embeddings, and real-time voice. Assistants can also pin their own conversation model, overriding the Twin’s default.

Monitor & Optimize

Track usage, token consumption, and credit spend across all models through the admin Analytics and Histories dashboards, then adjust your model assignments to optimize for your specific needs.

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Key Advantages Over Direct API Integration

Unified Interface

A single API and a single admin console for all AI models — no per-provider integration work

Easy Model Switching

If a model is deprecated, unavailable, or too expensive, switch to an alternative in the admin console — no code changes

Context Management

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

Token Optimization

Prompt caching discounts on supported models and per-task model choices reduce the cost of repeated context

Compliance Built-In

Content moderation, conversation audit history, and granular access controls support your regulatory obligations

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 both ways: expose your Digital Twin as an MCP server to Claude Desktop, Cursor, or any MCP-compatible client, and connect your Twin to remote MCP servers to extend its tool set. See MCP Server.
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 admin dashboards tracking:
  • Token usage and credit spend, broken down per model
  • Conversation activity, sessions, and engagement over time
  • Per-user usage statistics with CSV export
  • User feedback with admin responses

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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, or buy bundles and save
  • AI Model Costs: Customers who bring their own API keys (BYOK) receive a 40% discount on standard pricing
  • No Hidden Fees: Transparent pricing with volume discounts available

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Where the Savings Come From

  • Bring Your Own Keys — a 40% discount on standard pricing when you supply your own provider credentials (see Plans and Credits)
  • Prompt caching — cached input tokens are billed at a reduced rate on models that support caching, with the realized discount shown on each conversation’s report card
  • Right-sized models — assign inexpensive models to high-volume background work (summaries, embeddings) and reserve premium models for conversation
  • No failed-call charges — AI calls that fail are not billed

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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

Configure 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