Orq.ai

Orq.ai is a generative AI collaboration platform for building, shipping, and monitoring AI applications and agents. Developer and enterprise deployment options available.

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Orq.ai at a glance

Orq.ai is a generative AI collaboration platform for building, shipping, and scaling AI applications and agents in one place. The product combines model routing, observability, evaluation, governance, and shared asset management so teams can develop and operate GenAI systems from a single platform.

The home and pricing pages position Orq.ai around the AI application lifecycle: configure agents, trace their behavior, measure quality, and improve with production feedback. The platform supports deployment across cloud, hybrid, VPC, and on-premise environments for enterprise customers, while also offering a self-serve Developer plan for individual builders and smaller teams.

Core capabilities

AI Gateway

Route requests across many models and providers through a single API, with fallbacks, retries, routing rules, and cost visibility built in.

Observability and tracing

Capture prompts, tool calls, retrieval steps, latency, token spend, failure modes, and other trace data in real time for debugging and monitoring.

Evaluation workflows

Run offline and online evaluations, compare versions side by side, and use LLM-as-judge, code, and human review to measure output quality.

Agent runtime and orchestration

Build and orchestrate agents with memory, tools, multi-step reasoning, and runtime execution, including support for multi-agent systems and remote MCP servers.

Shared library for assets

Organize prompts, tools, skills, MCPs, and knowledge in reusable repositories with versioning and deployment support.

Governance and security controls

Apply governance controls such as role-based access control, SSO/SCIM, audit logs, PII filtering, and deployment options for enterprise environments.

Common ways teams use Orq.ai

Build and deploy AI applications
Teams building AI features can route requests through the AI Gateway, organize prompts and tools, and launch agents with memory and execution support.
Monitor live AI systems
Product and engineering teams can trace prompts, tool calls, retrieval steps, latency, and token spend to understand how production behavior changes over time.
Evaluate changes before release
Builders can run offline and online evaluations, compare versions, and use human or automated review to decide whether a change is ready to ship.
Operate under enterprise governance
Organizations with stronger control requirements can apply RBAC, SSO/SCIM, audit logs, data masking, retention rules, and enterprise deployment options.
Support retrieval-augmented workflows
Teams using RAG workflows can manage knowledge bases and memory stores, inspect document processing, and expose controlled context to deployments and agents.

Pros and Cons

Pros

Covers the full AI application lifecycle from routing and tracing to evaluation and improvement.
Offers real-time observability with traces, metrics, dashboards, feedback loops, and logging controls.
Supports both offline and online evaluation workflows, including human review and evaluator libraries.
Provides enterprise security and governance features such as RBAC, SSO/SCIM, audit logs, and PII filtering.
Includes a free Developer plan for trying the platform without a credit card.

Cons

Some capabilities, such as enterprise deployment and advanced administration, are tied to the Enterprise plan.
The source material does not provide complete detail for every integration or workflow, so some product areas remain partially documented here.

FAQ

Is there a free way to try Orq.ai?

You can start with the free Developer plan, which is self-serve and does not require a credit card. The pricing page says it includes access to core platform features with some restrictions.

What is the difference between a trace and a span?

On the pricing page, a trace is described as a complete end-to-end interaction, while a span is a single step within that trace. Billing is based on spans.

Does Orq.ai support enterprise deployment options?

Yes. The pricing and home pages both describe enterprise deployment options such as VPC, private cloud, cloud, hybrid, and on-premise setups, along with enterprise security and compliance support.

What does document processing priority mean?

The pricing page says Enterprise customers get priority document processing, which means files are parsed and indexed faster when uploaded to a knowledge base.

Can subscriptions be managed or cancelled?

The pricing page says paid Developer subscriptions can be managed or cancelled at any time, with changes taking effect at the end of the billing cycle. Enterprise plans use a contact-sales flow.

Quick Facts

Category: Generative AI collaboration platform
Primary use: Build, ship, monitor, and improve GenAI applications and agents
Plans: Free Developer plan, paid Developer plan, and Enterprise plan
Deployment: Cloud, hybrid, VPC, and on-premise options
Domain: orq.ai
Notable workflows: AI Gateway, observability, evaluation, governance, and shared libraries