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Orq.ai pricing, features, company info, and alternatives
A factual product page for Orq.ai as a generative AI collaboration platform for building, routing, evaluating, and observing LLM applications.
Last updated April 2026 · Pricing and features verified against official documentation
Pricing
Current public pricing tiers on file for Orq.ai, last verified Apr 25, 2026.
Developer
$0 / month
Includes 1 user, 50k spans per month, 1 GB processed data, 10 MB memory storage, 3 agents, 50 agent runs per month, 3 deployments, 1 webhook, 2 knowledge bases, and 14-day retention.
Growth
EUR 35 / seat/month
Includes unlimited users, 100k spans per month, and metered overages for spans, processed data, memory storage, and agent runs.
KB / Memory Stores Add-on
EUR 500 / month
Optional add-on with unlimited retrievals, ingestion, parsing, chunking, and 2.5 GB document processing.
Teams Add-on
EUR 300 / month
Optional add-on with Enterprise SSO, SAML/OIDC authentication, SSO enforcement, RBAC, and Slack support.
Enterprise
Custom
Includes custom limits, enterprise API, audit logs, HIPAA BAA, custom DPA, and on-prem or private-cloud deployment options.
What You Can Do With It
The main capabilities that shape how people use Orq.ai today.
Builds and deploys agents with memory, tools, and knowledge bases from the studio or API.
Routes requests across 300+ models through one AI Router endpoint with retries, caching, and budget controls.
Versions prompts, runs experiments, and manages online and offline evaluations across deployments.
Traces requests, monitors usage, and supports cloud, hybrid, and on-prem deployments.
Best For
Who Orq.ai is most clearly built for.
Engineering and product teams building production LLM applications with shared routing, prompt, and evaluation workflows.
Organizations that want observability, experimentation, and agent runtime inside one platform.
Teams that need enterprise deployment and security controls around LLM infrastructure.
Company
Leadership and company context for Orq.AI Holding B.V..
Founders
Sohrab Hosseini, Anthony Diaz
Headquarters
Amsterdam, Netherlands
Platforms
Where you can use Orq.ai today.
Web
API
Python SDK
TypeScript SDK
Cloud
Hybrid
On-prem
Integrations
Notable connected tools and ecosystem hooks for Orq.ai.
OpenAI
Anthropic
AWS
Privacy Notes
Publicly stated data-handling notes that matter when evaluating Orq.ai.
The privacy policy says service data is retained for the customer relationship and for up to three years afterward for operational and archival purposes.
The policy says prospect data is retained until it no longer has business value and at most for three years.
The policy says data can be deleted on verified request and that some storage occurs on servers in the United States.
Compliance
Public compliance or enterprise-governance signals we found for Orq.ai.
SOC 2
GDPR
EU AI Act
ISO 27001
Access
How to integrate or build around Orq.ai.
Public API
Yes
Docs
Available
Alternatives
Other tools worth considering alongside Orq.ai.
Open-source LLM engineering platform for tracing, prompt management, evaluations, and analytics.
AI agent testing and LLM evaluation platform for observability, prompt management, simulations, and guardrails.
LLM gateway and observability platform for routing, debugging, and cost tracking across model providers.
Open-source CLI and library for evaluating and red-teaming LLM apps.
Product Snapshot
Orq.ai is a generative AI collaboration platform for software teams building and operating LLM applications. It combines agent runtime, AI routing, prompt management, evaluations, observability, and knowledge-base workflows in one product.
What You Can Do With It
- Build and deploy agents with memory, tools, and knowledge bases from the studio or API.
- Route requests across multiple models through one AI Router endpoint with retries, caching, and budget controls.
- Version prompts, run experiments, and manage online and offline evaluations across deployments.
- Trace requests, monitor usage, and deploy cloud, hybrid, or on-prem setups from the same platform.
Why It Stands Out
It bundles routing, agent runtime, prompt workflows, evaluation, and observability in one platform instead of splitting those jobs across separate tools.
Tradeoffs To Know
- The public Developer tier is tightly limited by spans, agent runs, storage, and retention.
- The Growth plan adds metered overages once included spans, processed data, memory storage, or agent runs are exceeded.
- Enterprise-only controls include SSO, audit logs, and on-prem or private-cloud deployment options.