Connect everything. Behind one endpoint.
Actualyze is one endpoint between your applications and your AI providers, OpenAI- and Anthropic-compatible. It routes like an AI gateway and keeps team access, budgets, and the record of every call on the same path.
Your tools, already supported
Step-by-step guides for pointing the AI tools your teams use at Actualyze: the base URL, where the API key goes, and how models are picked.
Any LLM, anywhere.
Any model behind an OpenAI- or Anthropic-compatible API works with Actualyze. From the hosted platform, Actualyze reaches public APIs, managed gateways and brokers, neocloud endpoints, and inference servers inside your private network, VPC, or data center. Private servers connect through the Actualyze Inference Relay, which you run and which connects outbound only.
- OpenAI, Anthropic, Google, Azure OpenAI, Bedrock, OpenRouter, and more
- Managed gateways, brokers, and neocloud endpoints connect as direct endpoints
- Your own vLLM or Ollama servers, reached through the relay
- Any model behind an OpenAI- or Anthropic-compatible API
- Governed or Open Access, chosen per endpoint
Even models inside your own network.
Some models can't be exposed to the public internet. The Actualyze Inference Relay is a lightweight component you run inside your network. It connects outbound only, so Actualyze can reach models in your VPC, your data center, or behind your corporate network, and govern them like everything else. Your private endpoints stay private.
- Models in your VPC or private cloud
- Inference servers you already run, behind your firewall
- No inbound firewall ports and no gateway to deploy in each network
- No public exposure of your model endpoints
- Same governance, guardrails, and budgets apply
No rewrites. Point your SDK at one URL.
Point any OpenAI-compatible SDK at one base URL, use an Actualyze API key, and call a Virtual Model by name. Everything you've already built keeps working.
- Use the OpenAI SDK to connect to any OpenAI-compatible LLM
- Python, TypeScript, or your language of choice
- Self-service API keys, each bound to a team and a budget
- Swap models behind a Virtual Model with no redeploy
Wire into the tools you already run.
Plug Actualyze into your identity provider, your security and observability tools, and your finance workflow.
- Identity via Okta, Entra ID, Google, GitHub, or any SAML provider
- Stream audit, inference, and cost metadata to your SIEM or observability stack over OTLP
- Export ledgers to finance as CSV
- Forwarded records carry metadata only, never prompt or response content
Nobody chains a dozen proxies in front of inference
Every capability that wants to see, shape, or meter a model call has to sit in the request path, and every independent proxy you add multiplies latency, failure modes, and security reviews. Actualyze is one layer on that path: one hop, one review, one place where the next capability lands as an integration instead of another hop. If you already run an AI gateway for auth, routing, logging, and spend limits, Actualyze handles those on the same path, or keeps a managed gateway such as OpenRouter or Azure OpenAI as an endpoint behind it.
One endpoint in front of every provider
Explore the rest of the platform.
Connect once. Run everything through it.
Bring your models, your apps, and your stack behind a single endpoint, then govern, secure, operate, and optimize every call from there.