Use Orq.ai as the model control layer for Anthropic. Route Claude calls through one OpenAI‑compatible endpoint, capture traces, monitor cost, and manage fallback behavior without rebuilding your Claude‑based agent logic or application code.
What is Anthropic?
Anthropic provides the Claude family of models (for example Claude 3.x and 4.x) with strong reasoning, safety tooling, and a JSON‑friendly API that many teams already use for agents, tools, and workflows. Orq.ai helps those teams focus on agent behavior while centralizing model routing, observability, and cost controls.
How the integration works
Step 1
Point Claude traffic at Orq.ai’s router
Configure your applications or agent framework to send Claude requests to Orq.ai’s base URL (using Orq’s Anthropic provider or OpenAI‑compatible interface) instead of calling the Claude API directly. This gives Orq the context it needs to apply routing rules, capture usage, and enforce fallback behavior.
Step 2
Enable tracing from Anthropic workloads to Orq
Keep your existing logging and monitoring in place while routing LLM calls through Orq’s AI Gateway / Router. Your app continues to emit logs for agent execution, and Orq records LLM interactions, latency, and cost metrics for those requests, so you can see both agent‑level and model‑level traces.
Step 3
Define routes, fallbacks, and policies in Orq
Create routes for key Claude‑based workflows and assign them model tiers, fallback chains, and region/data policies. Your agent sends the request to the configured Orq route, and Orq applies the routing rules you define before invoking Claude or alternative models.
Step 4
Monitor, evaluate, and tune
Once connected, use Orq’s dashboards to watch latency, errors, and cost for Claude agents, and run evals or experiments on their traces. You can then adjust routes, models, or prompt configurations centrally where supported, without changing your Anthropic integration or agent wiring.
Use Cases
Multi‑agent products with real observability
Trace which agent, tool call, and model contributed to a failed workflow or unexpected outcome, combining your own logs with Orq’s router‑level traces.
Cost‑aware internal tools
Route routine steps to lower‑cost models while keeping complex reasoning or high‑stakes flows on your strongest Claude routes configured in Orq.
Eval‑driven agent improvements
Reuse failed conversations and agent traces as eval inputs before shipping prompt, tool, or model changes, turning production telemetry into a continuous improvement loop.
Safer experimentation across providers
Test a new provider or model on a small share of Claude‑based traffic, then promote or roll back based on traces and evals, instead of editing each agent definition or Anthropic integration by hand.
FAQ
Do I have to change my Anthropic code to use Orq.ai?
In many cases, you can repoint the LLM calls your agents make (for example by updating the base URL and API key configuration to Orq’s router) and keep your existing agent logic as‑is, adding only minimal configuration instead of rewriting your agents. The agent definitions, tools, and orchestration stay in your framework.
Does Orq.ai replace Anthropic’s own runtime or framework?
No. Claude remains your underlying model and you keep using Anthropic’s capabilities. Orq.ai sits alongside it as the control plane for models, multi‑provider routing, cost tracking, and evaluation. You still design and run agents with Claude at the core, but you use Orq to see what they cost, which models they should call, and how LLM behavior compares across providers under the same agent workflow.
Can I keep using my existing LLM providers with Anthropic if I move to Orq.ai?
Yes. You can bring your existing Anthropic API key into Orq.ai and route traffic through Claude, alongside any new models you add later. That way you centralize access, routing, and tracking without losing the Anthropic setup you already rely on. Bring production controls to Claude agents
