RagaAI
RagaAI builds automated platforms that detect, diagnose, and help fix quality, safety, security, and reliability issues in AI applications. Its Catalyst platform targets LLM, RAG, and agentic workflows, while Prism focuses on data and model health across multimodal datasets.
At a Glance
- Enterprise data-science and machine-learning teams
- AI-first software companies
- Healthcare providers, hospitals, clinics, and clinical-research organizations
- E-commerce and customer-support operations
- +3 more
AI Tools by RagaAI
(1)
RagaAI Catalyst
LLM Agent Observability SDK
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Latest News
RagaAI Catalyst integrates with NVIDIA NeMo Agent Toolkit
RagaAI launches Catalyst as an open-source tool for evaluating and debugging AI agents
RagaAI Catalyst GitHub repository lists version 2.1.7 release commit
RagaAI partners with DeepHealth to power radiology AI agents
Products & Services
Automated test-and-fix and observability platform for LLM, RAG, and agentic applications, with tracing, evaluation, guardrails, prompt experimentation, synthetic data generation, custom metrics, model comparison, and feedback reinforcement-learning actions. The open-source Python SDK/repository is RagaAI-Catalyst.
Data-health and AI testing engine for image, video, text, OCR, and tabular datasets. It detects drift, outliers, imbalance, labeling issues, schema problems, regression errors, and other data-quality failure modes.
Purpose-built clinical-operations suites powered by Prism and Catalyst, including Allergy Clinic, Clinical Research/Trials, and Radiology workflows.
RagaAI platform offering listed alongside Prism and Catalyst for healthcare workflow operations.
Market Position
RagaAI positions Catalyst as a broad automated test-and-fix and observability platform spanning LLM, RAG, agentic, multimodal, and traditional AI, rather than a narrow single-model evaluator. Reported comparison points include Deepchecks, LangChain, Braintrust, and Arize AI; RagaAI differentiates through a large built-in metric library, guardrails, root-cause diagnosis, remediation/feedback actions, and private-cloud or on-premises deployment.
Leadership
Founders
Gaurav Agarwal
Founder and CEO; a technology veteran who previously held AI, smart mobility, and software-product-engineering leadership roles at OLA, worked in autonomous vehicles and computing at NVIDIA, and began his career at Texas Instruments.
Executive Team
Gaurav Agarwal
Founder and CEO
Serial entrepreneur and AI leader with 23+ years of experience; previously VP-level AI, smart mobility, and software-product-engineering leader at OLA and held autonomous-vehicle leadership roles at NVIDIA; earlier Texas Instruments.
Hitesh Hinduja
VP - Head of Applied AI & Product
Applied-AI and data-platform leader with 15+ years of experience; previously held senior roles at Microsoft Azure OpenAI, OLA and OLA Electric, Jio, and Accenture.
Founding Story
Gaurav Agarwal founded RagaAI after a near-miss in a semi-autonomous vehicle exposed how AI systems can fail in real-world conditions. The initial vision was to automate comprehensive AI testing so developers could detect issues, diagnose root causes, and improve safety and reliability before failures caused business or physical harm.
Business Model
Revenue Model
Enterprise AI-software platform sold to organizations through its web UI and Python interface, with deployment on customer private clouds or on-premises infrastructure; public pricing is not listed.
Target Markets
- Enterprise data-science and machine-learning teams
- AI-first software companies
- Healthcare providers, hospitals, clinics, and clinical-research organizations
- E-commerce and customer-support operations
- Automotive and autonomous-vehicle companies
- Aerospace and industrial companies
- Testing and monitoring LLM and RAG applications
- Evaluating and debugging agentic and multi-agent workflows
- Production observability and failure diagnosis
- AI safety, security, guardrails, and compliance
- Computer-vision model validation, drift detection, and edge-case testing
- OCR and text-quality testing, PII removal, and data balancing
- An e-commerce retailer using Catalyst/RagaAI to reduce hallucinations in a product-catalog chatbot
- An automotive customer using RagaAI to test vehicle detection in low-light conditions
- DeepHealth, for radiology AI-agent and imaging-informatics workflows
- NVIDIA NeMo Agent Toolkit users, through Catalyst observability integration