Contextual AI
on Orq.ai
Access Contextual AI models through Orq.ai for grounded generation, retrieval, reranking, evaluation, and retrieval-augmented workloads through one API.
Capabilities:
Chat
Reasoning
Models Supported:
...
No models available
Provider HQ:
Mountain View, California
Access Contextual AI through Orq.ai’s AI Router
Contextual AI develops models and tools for grounded enterprise AI, with capabilities spanning generation, retrieval, reranking, and evaluation. Its approach is particularly suited to RAG and other applications where outputs need to stay closely tied to retrieved information.
Contextual AI models available on Orq.ai
Compare the Contextual AI models currently available through Orq.ai, including their supported capabilities, context limits, pricing, and regional availability.
Model
Type
Context
Input / 1M
Output / 1M
No provider models available
Why use Contextual AI through Orq.ai?
Using Contextual AI through Orq.ai lets teams combine grounded generation, retrieval, and evaluation capabilities with a wider model stack without maintaining separate observability, evaluation, governance, and cost-control systems for each provider.
Capability | Provider | Direct | Through Orq.ai |
|---|---|---|---|
Chat / RAG | Contextual AI generation models | Use supported Contextual AI models directly for grounded generation and retrieval-augmented applications. | Route grounded generation through Orq.ai while applying tracing, evals, budgets, and governance controls around each workflow. |
Retrieval | Contextual AI retrieval and reranking models | Use specialized models to improve the ordering and relevance of retrieved content. | Manage retrieval and reranking alongside other model providers while keeping logs, evaluations, and experiments in a shared platform. |
Evaluation | Contextual AI evaluation models | Use supported evaluation models for scoring, preference testing, and assessing model outputs. | Incorporate evaluation workloads into Orq.ai alongside centralized evaluations across models, providers, and workflows. |
Pricing
Contextual AI model pricing varies by model, provider configuration, region, and billing setup.
You can connect supported Contextual AI credentials to Orq.ai or use other available access options depending on your workspace configuration. Check Orq.ai and your Contextual AI setup for current per-model rates, quotas, and billing details.
Compatible frameworks and tools
Orq.ai works with OpenAI-compatible clients and common AI development frameworks where supported. Retrieval and evaluation workflows can also integrate through available Orq.ai interfaces and tooling.
Check the Orq.ai integration documentation for the latest setup options and compatibility information for Contextual AI.
FAQs
Do I need a separate Contextual AI account to use Contextual AI through Orq.ai?
You can connect supported Contextual AI credentials to Orq.ai or use other available access options depending on your workspace, plan, and region.
Can I route only some workflows to Contextual AI and others to different providers?
Yes. Orq.ai lets you route different workloads to different providers, so you can use Contextual AI where grounded generation, retrieval, reranking, or evaluation capabilities fit the workflow while routing other requests elsewhere.
Does using Contextual AI through Orq.ai add latency?
Orq.ai adds a routing layer between your application and the model provider. Teams can monitor end-to-end latency and use routing, caching, and provider controls where appropriate to manage performance.
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