Description
Orq.ai offers a comprehensive platform for managing the entire lifecycle of AI agents, addressing the challenges of AI drift, hallucinations, and regression. The platform empowers teams to build with robust quality gates, observe production performance, evaluate against real metrics, and implement continuous improvement workflows. This includes configuring intelligent agents with memory and tools, tracing every prompt and tool call in real-time, and scoring outputs using various evaluators.
The platform facilitates building, shipping, and governing AI agents on a single stack. Key components include the AI Gateway, which provides a unified API to route requests across over 400 models from 28 providers, with built-in fallbacks, retries, and cost visibility. AI Observability offers detailed traces across multi-step agents, tracking latency, token spend, and failure modes. Evals enable confident shipping through offline and online evaluations, allowing side-by-side comparison of versions on critical metrics. Control Tower provides AI Governance, offering a centralized view of all agents, tools, and models, with monitoring for cost, compliance, and risk.
Orq.ai promotes collaboration and efficiency with a Shared Library for organizing prompts, skills, MCPs, tools, and knowledge, making them reusable and versioned across teams. The platform is framework-agnostic, supporting popular tools like LangGraph, OpenAI Agents, CrewAI, and Vercel AI, as well as any OpenTelemetry stack. Additional features include Orq MCP & Skills for querying traces and running experiments in plain English, Identities for tying traces to users or tenants with per-identity quotas, a Feedback API for capturing user ratings and corrections, and an Auto Router for optimizing model selection based on cost, latency, or quality.
Businesses benefit from faster time-to-market, improved collaboration, and reduced manual work. Orq.ai enables teams to deploy AI solutions more rapidly, especially for complex use cases. The platform supports flexible deployment methods, including cloud, hybrid, or on-premises, with enterprise-grade security and data residency options. It also offers features for data privacy, such as setting data retention policies and masking sensitive fields, alongside enterprise-grade access control and audit logging for compliance.
Orq.ai's Core Features
Agent Lifecycle Management
AI Gateway with 400+ models from 28+ providers
AI Observability for real-time tracing and monitoring
Evals for offline and online testing and version comparison
AI Governance with cost, compliance, and risk monitoring
Shared Library for reusable prompts, skills, and tools
Framework-agnostic integrations (LangGraph, CrewAI, etc.)
AI Router for optimizing model selection
Identity management for cost attribution and quotas
Feedback API for capturing user reviews and corrections
Data Residency options (EU, custom regions)
Enterprise security and compliance features
How to use Orq.ai?
Configure: Set up intelligent agents with memory, tools, and real-time execution.
Launch: Deploy agents and manage them through the platform.
Trace: Capture every prompt, tool call, and retrieval step in real time.
Measure: Score outputs using LLM-as-judge, code, and human review evaluators.
Iterate: Use production data to improve datasets and agents.
Govern: Monitor cost, compliance, and risk across all deployed agents.
Orq.ai's Use Cases
- AI Agent Development
- Model Routing
- AI Observability
- AI Governance
- Prompt Engineering
- Continuous Improvement
- Cost Management
- Framework Integration
