Orq.ai
UnclaimedThe Generative AI Collaboration Platform for building and operating production-grade GenAI systems.
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TL;DR - Orq.ai
- Deploys and manages autonomous AI agents with built-in tools and orchestration.
- Routes AI across 300+ models with failovers, caching, and budget controls.
- Provides RAG-as-a-Service and comprehensive monitoring for GenAI applications.
Pricing: Paid only
Best for: Enterprises & pros
Pros & Cons
Pros
- Significantly reduces AI build time and accelerates time-to-market.
- Unifies engineering, product, and data teams for seamless collaboration.
- Offers robust enterprise-grade security and compliance features like SOC 2 and GDPR.
- Provides extensive control and reliability for GenAI systems with guardrails and monitoring.
- Supports deployment in various environments, including cloud, private cloud, or on-premises.
Cons
- Pricing details are not transparently listed, requiring direct contact for enterprise plans.
- The platform's complexity might have a learning curve for new users.
- Specific integrations with third-party tools are mentioned but not fully detailed.
Key Features
Agent Runtime for deploying and managing autonomous agentsAI Gateway for routing across 300+ models with failovers and cachingKnowledge Base (RAG-as-a-Service) for data ingestion, chunking, and embeddingMonitoring & Observability with real-time traces, dashboards, and alertsEvaluation tools including golden sets, A/B testing, and human reviewPrompt library, prompt engineering, and structured outputsRole-based access control (RBAC) and Single Sign-On (SSO)Data residency options (EU) and on-prem deployment capabilities
Pricing Plans
Developer
Contact us
- 2 Users
- 1M Traces
- 14 days Custom Trace retention
- 1GB Custom Processed Data
- Platform API
- AI Gateway
- Multi-modality
- Prompt library
- Prompt engineering
- Structured outputs
- Playgrounds
- Experiments
- Evaluator library
- 3 Deployments (capped)
- Retries & fallbacks
- Versioning
- Contextual rules engine
- LLM cache
- File ingestion
- 10MB Custom Storage (Knowledge Bases)
- RAG-as-a-Service
- Chunk explorer
- Embedding & reranking
- RAG evaluators
- Document processing priority
- Real-time traces
- 14 days Custom Trace retention
- Dashboards
- Online evaluators
- Guardrails
- Experiment Exports
- 1 Unlimited Webhooks
- Human evaluations
- Corrections
- Feedback API
- Dataset curation
- PII filtering
- SOC 2 report
- Role-based access control
- AWS/Azure marketplace
- VPC deployment
- SSO / SCIM API
- HIPAA
- Audit Logs
- 50 calls/min Custom rate limits
- Uptime SLA
- Support center
- Email support
- Slack/Teams support
- Dedicated account manager
- Solutions engineer
- SLA
Enterprise
Contact us
- 2 Users
- 1M Traces
- 14 days Custom Trace retention
- 1GB Custom Processed Data
- Enterprise API
- AI Gateway
- Multi-modality
- Prompt library
- Prompt engineering
- Structured outputs
- Playgrounds
- Experiments
- Evaluator library
- 3 Deployments (capped)
- Retries & fallbacks
- Versioning
- Contextual rules engine
- LLM cache
- File ingestion
- 10MB Custom Storage (Knowledge Bases)
- RAG-as-a-Service
- Chunk explorer
- Embedding & reranking
- RAG evaluators
- Document processing priority
- Real-time traces
- 14 days Custom Trace retention
- Dashboards
- Online evaluators
- Guardrails
- Experiment Exports
- 1 Unlimited Webhooks
- Human evaluations
- Corrections
- Feedback API
- Dataset curation
- PII filtering
- SOC 2 report
- Role-based access control
- AWS/Azure marketplace
- VPC deployment
- SSO / SCIM API
- HIPAA
- Audit Logs
- 50 calls/min Custom rate limits
- Uptime SLA
- Support center
- Email support
- Slack/Teams support
- Dedicated account manager
- Solutions engineer
- SLA
About Orq.ai
By Toolradar Team·
Orq.ai is a comprehensive platform designed to streamline the development, deployment, and management of generative AI applications and autonomous agents. It provides a unified environment for engineering, product, and data teams to collaborate on AI projects, accelerating the transition from concept to production. The platform handles complex infrastructure requirements, allowing teams to focus on content and agent logic.
This platform is ideal for enterprises and development teams looking to build reliable, scalable, and controlled GenAI systems. It addresses critical needs such as model orchestration, evaluation, knowledge base management, and robust monitoring. By offering features like an AI Gateway, RAG-as-a-Service, and extensive observability tools, Orq.ai ensures that GenAI applications can be deployed safely and efficiently, with built-in guardrails and compliance features.
How we evaluate tools →Source: orq.ai
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Orq.ai FAQ
How does Orq.ai ensure the reliability and predictability of GenAI outcomes in production?
Orq.ai ensures reliability through features like guardrails, fallbacks, canaries, and rollbacks. It also provides live tracing and dashboards for real-time monitoring, allowing teams to catch cost, latency, and quality issues early and maintain predictable outcomes.
What kind of evaluation capabilities does Orq.ai offer for AI models and agents?
The platform includes comprehensive evaluation tools such as golden sets, A/B testing, LLM evaluators, and human-in-the-loop review. It also supports RAG evals, Python evals, and prompt scoring to assess and improve agent performance and output quality.
Can Orq.ai integrate with existing enterprise security and compliance frameworks?
Yes, Orq.ai is designed for enterprise assurance, offering features like RBAC, SSO, audit trails, PII filtering, and SOC 2 compliance. It also supports data residency options (EU) and on-prem deployments, aligning with GDPR and the EU AI Act.
How does the AI Gateway manage routing across multiple large language models?
The AI Gateway seamlessly routes AI across over 300 models. It applies intelligent controls such as failovers, caching, budget controls, model routing, and identity tracking to optimize performance, cost, and reliability across diverse LLM providers.
What is 'RAG-as-a-Service' within Orq.ai's Knowledge Base feature?
RAG-as-a-Service (Retrieval Augmented Generation) in Orq.ai's Knowledge Base handles all the pipelines required for effective RAG. This includes data ingestion, file processing, chunking, embedding, retrieval, and reranking, allowing users to focus solely on their content without managing the underlying infrastructure.
What are the deployment options available for Orq.ai, particularly for enterprises with specific infrastructure requirements?
Orq.ai offers flexible deployment options, including its cloud, your own cloud environment, or on your private servers. It supports private connections and provides features like VPC deployment, catering to enterprises with strict security or data residency needs.
Source: orq.ai