Multi-Model AI Configuration — Choose Your AI Models in WalnutAI.
Run WalnutAI on OpenAI, Azure OpenAI, AWS Bedrock, Google Gemini, Anthropic Claude, or local Ollama. Per-project model configuration with spending limits and AES-256 key encryption.
Trusted by enterprises that can't afford AI vendor lock-in
AI providers supported — OpenAI, Azure, AWS Bedrock, Gemini, Anthropic, and local Ollama
Model configuration means different teams can use different models based on cost, compliance, or capability needs
Data residency control — on-premise inference via Ollama means data never leaves your infrastructure
The best AI model for your team today might not be the best one tomorrow
The AI model landscape changes faster than any enterprise can standardize on. A model that leads on code generation today may be surpassed next quarter. Organizations with strict data residency requirements need local inference options that cloud-only platforms can't offer. WalnutAI is model-agnostic by design — configure any supported model per project, switch without rebuilding workflows, and retain full control over cost, compliance, and performance.
Choose any model per project — not one model for everything
Different projects have different needs. A cost-sensitive internal tooling project might run on a fast, efficient model. A high-stakes customer-facing feature might warrant the most capable available. WalnutAI’s per-project model configuration lets each team optimize independently without affecting others.
Bring your own keys — WalnutAI never holds your API credentials insecurely
API keys for every configured model are encrypted with AES-256 at rest. WalnutAI calls the model on your behalf using your credentials — the model provider sees your account, your usage, and your billing. No intermediary markup, no shared model pool that leaks usage across customers.
Run fully on-premise with Ollama for complete data sovereignty
For air-gapped environments, regulated industries, or organizations with strict data sovereignty requirements, WalnutAI’s Ollama integration enables fully local AI inference. Every story generation, gap analysis, and test generation call stays within your infrastructure — nothing reaches an external API.
Set spending limits per project before costs surprise you
Each project can be configured with a spending cap on AI model usage. When usage approaches the limit, WalnutAI alerts the project owner — no runaway token costs from a batch job that processed more than expected.
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