What is Orq.ai?

Orq.ai is a generative AI collaboration platform for developing, evaluating, and deploying large language model (LLM) applications.It provides an agent runtime for orchestrating multi-agent workflows, an AI gateway for secure model access, and evaluation tools for measuring model performance and behavior.

Integrated knowledge base features support retrieval-augmented generation and enterprise content management.Monitoring and observability capture latency, errors, usage metrics, and model drift for operational visibility.

APIs and SDKs enable SaaS teams, AI startups, consultancies, and enterprise developers to integrate the platform into CI/CD and production pipelines.

Orq.ai on the web:

Orq.ai details

Jurisdiction: Netherlands
Built for: Businesses and teams
Data residency: EEA, United States
Stated compliance: SOC 2, GDPR

Compliance as stated in Orq.ai's own published documentation.

Orq.ai tech specs

Works with: OpenAI / GPT
Cloud: AWS Azure Vercel

Orq.ai pricing

Developer $0

Growth €35 per seat/mo

Custom custom seatscustom spanscustom processed datacustom memory storage

$35/mo is pricier than most for LLM median $19.50/mo

Most LLM tools start between $9.50 and $56.50 a month.

Verify on the official pricing page.

View plans

Orq.ai's key features

Agent Runtime
Evaluation
AI Gateway
Knowledge Base
Monitoring & Observability

Orq.ai use cases

Build a production-grade multi-agent customer support assistant using Orq.ai to orchestrate specialized agents, leverage a RAG-enabled knowledge base for accurate, context-aware answers, route requests through the secure model gateway for compliance, and monitor agent performance with built-in observability
Implement an LLM CI/CD pipeline with Orq.ai to automate model evaluation, A/B testing and safe deployments via the secure model gateway, integrate retrieval-augmented generation for staged rollouts, and use evaluation and monitoring tools to detect regressions and enforce governance
Create an internal knowledge and developer productivity assistant using Orq.ai to ingest documentation into a RAG knowledge base, run multi-agent workflows for code generation, review and troubleshooting, collaborate on model improvements via evaluation tools, and expose governed APIs for enterprise-safe consumption