Model Management

Your Central Hub for AI Models

Manage every AI model from one place. Cloud APIs, local models, and custom deployments, unified with versioning, monitoring, and seamless switching.

Model Management Features

Everything you need to manage AI models at scale, from development to production.

Unified Model Hub

Access all your models, cloud APIs, local, and custom, from a single interface. Switch providers without changing code.

Model Versioning

Track model versions, configurations, and parameters. Roll back to a previous version instantly when you need to.

One-Click Deployment

Deploy models to production with a single click. Automatic scaling and load balancing are included.

Usage Analytics

Monitor token usage, latency, cost, and performance metrics across every model in real time.

API Key Management

Securely store and rotate API keys. Share model access with your team without exposing credentials.

Model Routing

Intelligently route requests to different models based on cost, latency, or capability requirements.

Connect Any Provider

Connect to any AI provider or run models locally. One API, unlimited possibilities. Avyndo speaks to OpenAI, Anthropic, Google, Mistral, local runtimes, and any OpenAI-compatible endpoint.

  • OpenAI: GPT-4o, GPT-4 Turbo, GPT-3.5, Whisper, DALL-E
  • Anthropic: Claude 3.5 Sonnet, Claude 3 Opus, Claude 3 Haiku
  • Google: Gemini Pro, Gemini Ultra, PaLM 2
  • Mistral: Mixtral 8x7B, Mistral Large, Mistral Small
  • Local models: Ollama, LM Studio, llama.cpp
  • Custom: any OpenAI-compatible API, ONNX, PyTorch

Hundreds of Models Across Every Category

Access hundreds of pre-configured models spanning every AI category, or upload your own. Language, vision, audio, embeddings, and image generation are all available behind the same gateway.

  • 50+ language models: GPT, Claude, Gemini, Llama, Mistral
  • 20+ vision models: YOLO, CLIP, SAM, InsightFace
  • 10+ audio models: Whisper, ElevenLabs, PlayHT
  • 15+ embedding models: text-embedding-3, Cohere, BGE
  • 8+ image generation models: DALL-E, Stable Diffusion, Midjourney
  • Unlimited custom models: upload your own ONNX or PyTorch models

From Evaluation to Production

Manage the entire AI lifecycle, from model evaluation to production deployment. Build multi-model applications, compare models before you ship, keep spend under control, and stay audit-ready.

  • Multi-model applications with routing, fallback chains, A/B testing, and cost optimization
  • Model evaluation with side-by-side comparison, custom benchmarks, quality metrics, and latency testing
  • Cost management with usage tracking, budget alerts, cost allocation, and team quotas
  • Compliance and audit with access logs, data retention, GDPR compliance, and export reports

Simple, Unified API

Switch between models with one line of code. No provider-specific SDKs needed. Call any model through the same interface, and add an automatic fallback chain so a single failure never takes you down.

Point the same request at gpt-4o, claude-3.5-sonnet, or llama-3.1-70b, then list several models with a sequential fallback so traffic shifts to the next one on failure.

One Gateway, Every Model

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Pre-Configured Models
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Supported Providers
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Unified API
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Frequently Asked Questions

Which model providers does Avyndo support?

Avyndo connects to OpenAI, Anthropic, Google, and Mistral, runs local models through Ollama, LM Studio, and llama.cpp, and works with any OpenAI-compatible API as well as ONNX and PyTorch models you upload yourself.

Can I switch models without changing my code?

Yes. Every model is called through one unified API, so switching from gpt-4o to claude-3.5-sonnet or a local llama-3.1-70b is a one-line change. You do not need provider-specific SDKs.

How do fallback chains work?

You list several models in priority order with a sequential fallback strategy. If the first model fails, the request automatically moves to the next one, so a single provider outage never takes down your application.

How do I keep AI spend under control?

Usage analytics track token usage, latency, and cost across every model in real time. You can set budgets and alerts, allocate cost per team, and enforce quotas to prevent overruns.

Can I run my own custom models?

Yes. Alongside the 100+ pre-configured models, you can upload your own ONNX or PyTorch models and serve them behind the same gateway with versioning, monitoring, and one-click deployment.

Ready to Unify Your AI Models?

Stop juggling multiple AI providers. Manage everything from one platform with built-in monitoring, versioning, and cost control.

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