Orquesta
Orq.ai (Orquesta) is a generative AI collaboration platform for building, evaluating, deploying, and monitoring production-grade LLM systems and autonomous agents with enterprise controls and EU data residency options.
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Best for: AI Agents
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Orquesta
Orq.ai is a unified platform designed to speed up and secure the development, evaluation, and deployment of generative AI applications. It combines an Agent Runtime for running multi-agent systems, Evaluation tooling for large-scale and human-in-the-loop evaluation, an AI Gateway (AI Router) to route and manage models across providers, a Knowledge Base (RAG-as-a-Service) for connecting data, and Monitoring & Observability to trace prompts, tokens, tools, and production behavior. The product targets engineering teams, AI-native startups, consultancies, and enterprises that need collaboration, governance, and deploy-anywhere flexibility.
The platform emphasizes collaboration (shared workspaces, roles, reviews, and HITL), reliability (guardrails, canaries, rollbacks, dashboards and alerts), and compliance (EU data residency, data masking, enterprise sign-in and audit logging). Orq.ai can be deployed on their cloud, your cloud, hybrid, or on-prem with private connections supported.
Orq.ai (Orquesta) is a generative AI collaboration platform for building, evaluating, deploying, and monitoring production-grade LLM systems and autonomous agents with enterprise controls and EU data residency options.
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Claim this listingKey Features
Agent Runtime
Manage the full agent lifecycle with built-in tools, memory, orchestration, and multi-agent coordination without requiring customers to operate low-level infrastructure.
Evaluation
End-to-end evaluation tools including human evals, LLM-as-judge, A/B tests, golden sets, datasets, and experiment tracking to validate model quality and safety before release.
AI Gateway / AI Router
A unified API to route requests across 300+ models and providers, apply fallbacks, caching, budget controls, and model routing policies.
Knowledge Base (RAG-as-a-Service)
Pipelines for data ingestion, file processing, chunking, embedding, retrieval, reranking and RAG evaluation so teams can connect domain data to LLMs easily.
Monitoring & Observability
Trace every prompt, token, and tool call with real-time dashboards, alerts, automations, annotations, and AI insights to catch cost, latency and quality issues early.
Memory Store & Tooling
Persistent memory, tools and connector primitives for agents to maintain state and interact with systems during orchestration.
Reliability Controls
Guardrails, canaries, rollbacks, caching, retries and finops controls to keep quality and costs predictable in production.
Collaboration & Governance
Shared workspace, role-based access, reviews, human-in-the-loop workflows, change logs and enterprise auditing for teams to collaborate securely.
Deployment Flexibility
Deploy on Orq.ai cloud, your cloud, hybrid or on-prem with private connections and EU data residency options.
Third-party Integrations & Observability
Integrations with telemetry and observability tooling (e.g., OpenTelemetry), third-party systems and model providers.
Pricing
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Use Cases
Autonomous agents and orchestration
Build, run and monitor multi-agent systems with memory, tools and real-time orchestration without managing underlying infrastructure.
RAG-powered assistants
Connect internal data to LLMs via managed ingestion and retrieval pipelines to create knowledge-grounded applications.
Model evaluation and release gating
Run large-scale automated and human evaluations (A/B, golden sets, human-in-the-loop) to ensure model quality before production rollout.
Cost and reliability control for production LLMs
Route requests across providers, apply caching, budget controls and fallbacks to manage latency, availability and spend.
Cross-team prompt engineering and collaboration
Provide non-technical teammates access to prompt engineering, shared datasets and review workflows to scale AI development across functions.
Enterprise-grade deployment and compliance
Deploy across cloud, hybrid or on-premise setups while keeping data residency, masking and audit controls aligned with enterprise governance.
Integrations
LLM providers / BYOM
Route and operate across 300+ models and providers; bring-your-own-model (BYOM) support for integrating external models.
OpenTelemetry and observability tools
Integrate telemetry and tracing for detailed observability across prompts, tokens and tool calls.
Third-party systems
Connect to external data sources and tools as part of RAG ingestion and agent integrations (general third-party integrations supported).
Benefits
Limitations
Frequently Asked Questions
Does Orq.ai support on-prem or private cloud deployments?
Can I bring my own models (BYOM)?
How does Orq.ai handle data residency and privacy?
Is there built-in support for human-in-the-loop evaluation?
Getting Started
- 1 Step 1: Book a demo or click 'Get started' to request access and discuss requirements with Orq.ai.
- 2 Step 2: Explore the documentation and resources to understand platform concepts (Agent Runtime, Evaluation, AI Router, Knowledge Base, Observability).
- 3 Step 3: Connect data or model providers (bring your own model or use supported providers), configure RAG ingestion, build agents and run evaluations before deploying with routing and guardrails.
Support
Docs
Official documentation and resources are available (see platform docs link).
Book a demo / Sales
Request a demo or speak to sales via the 'Book a demo' flow on the website.
Contact
General inquiries and enterprise support via the website contact page.
Trust Center
Security, compliance and privacy information available through the Trust Center pages.
API
https://orq.ai/docs
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