Overview
RagaAI is an end-to-end AI testing and observability platform designed to evaluate, debug, enforce guardrails, and scale agentic AI, LLMs, RAG systems, computer vision and tabular models. Core product modules include Catalyst (evaluation, guardrails, agentic testing, real-time fixes and Feedback‑RL), Canvas (drag-and-drop builder and orchestration for multi-agent workflows with versioning, persistence and sandbox testing), Prism (data health, data quality and validation across vision, text and tabular data), and AgentNeo (open-source/SDK for agent observability and tracing). The company markets enterprise deployment options (on-prem/VPC), SOC 2 Type II claimed compliance, and 24/7 priority support as a vendor claim. Public site content highlights built-in evaluation metrics (300+ claimed), step-level tracing and trace logs, real-time low-latency guardrails, feedback-driven RL, prompt playground and A/B experimentation, modal data validation, integrations references (e.g., NVIDIA NeMo), and references to enterprise customers and adoption. No public pricing or free-trial details are published on the main site; interested parties are directed to contact sales or request a demo. Publicly available developer resources include docs, a GitHub organization, and an AgentNeo portal/SDK.
Key Features
Agentic testing & step-level tracing
Agentic testing with step-level tracing and trace logs for multi-agent workflows to inspect and debug agent behavior.
Built-in evaluation metrics
Site claims 300+ built-in evaluation metrics for automated evaluation of outputs across models and workflows.
Real-time guardrails
Policy enforcement and safety checks (tone, bias, PII, etc.) with low-latency, real-time policy/guardrail execution.
Feedback-driven RL (Feedback RL)
Mechanisms to convert evaluation feedback into model/workflow improvements via feedback-driven reinforcement learning.
Canvas orchestration & versioning
Drag-and-drop builder for multi-agent orchestration supporting versioning, persistence, sandbox testing, and canary deployments.
Prism data health engine
Data quality and validation across vision, text, and tabular data including automated tests, drift detection, and root-cause analysis.
Who Can Use This Tool?
- Enterprises:Large organizations seeking to evaluate, guardrail and scale agentic AI and multi-agent workflows; sales/POC required.
- ML engineers:Teams needing testing, observability, tracing and feedback-driven improvement for LLMs, RAG, CV and tabular models.
- Product/Platform teams:Product and platform teams orchestrating multi-agent applications, canary deployments, versioning and persistent memory.
Pricing Plans
No public pricing — contact sales for custom plans and trial/POC terms.
- ✓Custom enterprise pricing and deployment
- ✓Demo / POC via sales
- ✓Enterprise support and SLA (vendor claims)
Pros & Cons
✓ Pros
- ✓Comprehensive, end-to-end platform for evaluating and observing agentic AI and LLM workflows.
- ✓Dedicated modules for evaluation (Catalyst), orchestration (Canvas), and data quality (Prism).
- ✓Agent-level tracing and detailed logs enable step-level debugging of multi-agent flows.
- ✓Open-source SDK (AgentNeo) and GitHub presence for developer access and examples.
- ✓Enterprise-oriented deployment options and compliance claims (on-prem/VPC, SOC 2 Type II claimed).
✗ Cons
- ✗No public pricing or self-serve trial information on the main website; requires sales engagement.
- ✗Some vendor-facing claims (customer counts, metrics, compliance) should be validated during sales/POC.
- ✗Specific technical integration details for particular model providers or orchestration frameworks may require deeper doc/repo review or direct engineering contact.
Compare with Alternatives
| Feature | RagaAI | AgentOps | Lyzr |
|---|---|---|---|
| Pricing | N/A | $40/month | $99/month |
| Rating | 8.2/10 | 8.2/10 | 8.2/10 |
| Trace Granularity | Yes | Yes | Partial |
| Evaluation Suite | Yes | Partial | Yes |
| Runtime Guardrails | Yes | No | Yes |
| Feedback RL | Yes | No | No |
| Orchestration Versioning | Yes | No | Partial |
| Data Health Engine | Yes | No | No |
| SDK & Observability | Yes | Yes | Partial |
| Enterprise Governance | Partial | Yes | Yes |
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