Galileo
To help AI teams move from monitoring AI failures to stopping them by providing a complete agent reliability platform that brings unit testing and CI/CD rigor to the AI development lifecycle, making AI trustworthy, safe, and observable.
At a Glance
- Enterprise AI teams
- Fortune 500 companies
- AI developers and data scientists
- Machine learning engineers
- +8 more
AI Tools by Galileo
(1)
Galileo
GenAI Evaluation and Observability
Discussions
No discussions yet
Be the first to start a discussion about Galileo
Latest News
Galileo Announces Free Agent Reliability Platform for multi-agent AI systems
Introducing Luna-2: Next generation of small language models for real-time AI evaluations and guardrailing
Galileo launches Agentic Evaluations to fix AI agent errors before they cost enterprises
Galileo Raises $45M Series B Funding led by Scale Venture Partners, achieving 834% revenue growth
Products & Services
AI evaluation and observability platform that enables developers to build, evaluate, and monitor AI systems. Provides workflows for evaluation, monitoring, observability, and real-time guardrails to help developers fix unexpected behaviors in complex AI systems.
First-of-its-kind Evaluation Foundation Models (EFMs) designed to provide faster, more accurate, and cost-effective evaluations of generative AI responses. 30x cheaper than OpenAI GPT-3.5, provides results in milliseconds, and eliminates the need for ground truth data.
Real-time hallucination firewall designed to intercept malicious inputs and stop harmful responses like hallucinations in Large Language Model applications. Provides security and compliance guardrails without impacting user experience or performance with millisecond latency.
Next generation of small language models (SLMs) purpose-built for real-time AI evaluations and guardrailing. Available in 3B and 8B parameter sizes with sub-200ms latency, cost of $0.02 per million tokens, 128k token capacity, and multi-headed architecture for hundreds of metrics.
Market Position
Galileo is positioned as a purpose-built AI evaluation and observability platform designed specifically for autonomous AI agents and multi-agent systems with an 'agent-first' architecture. Unlike competitors that evolved from classical machine learning experiment tracking (like Weights & Biases), Galileo focuses on the unique challenges of agentic workflows. Key differentiators: (1) Uses proprietary small language models (Luna-2) for evaluation instead of expensive external LLM-as-judge models, achieving 97% cost reduction and sub-200ms latency, (2) Offers native, inline guardrails for real-time protection versus reactive logging, (3) Provides interactive Graph Engine for visualizing multi-step agent coordination, (4) Features automated Insights Engine for root cause analysis, (5) SOC 2 Type II compliant with flexible deployment options (SaaS, VPC, on-premises). Competes with Arize Phoenix, Weights & Biases, and other LLM observability platforms but specializes in production-grade reliability for enterprise agentic AI at scale.
Leadership
Founders
Vikram Chatterji
CEO and Co-Founder. Previously worked at Google AI for three years as Product Management Lead, where his team built large-scale applications using language models including work on BERT models. Has led product building from 0 to 1 multiple times across geographies, company sizes and business models, used by 100M+ users globally.
Atindriyo Sanyal
CPO and Co-Founder. Previously led engineering at Uber AI (Michelangelo) where he was co-architect of Uber's feature store, and was a senior software engineer at Apple focusing on Siri, developing the earliest versions of Siri. Played key engineering roles in influential AI infrastructure built at Uber and Apple.
Yash Sheth
CTO and Co-Founder. Previously led the speech recognition platform team at Google as staff software engineer, managing the Google Speech Recognizer platform and growing speech recognition 800x. Spent nearly nine years at Google working on speech-recognition models that recognize spoken words from audio.
Executive Team
Vikram Chatterji
Co-founder and CEO
Former Google AI Product Management Lead who built large-scale applications using language models
Atindriyo Sanyal
Co-founder and CPO
Former Uber AI and Apple Siri engineering leader, co-architect of Uber's feature store
Board of Directors
Founding Story
Founded in 2021 by former employees from Google AI, Google Brain, and Uber AI who were fed up with high AI project failure rates and the amount of time data scientists spend on menial data preparation tasks. The founders realized that AI developers could only be successful if they could manage the unpredictable nature of LLM applications. They started Galileo to create a machine learning data tooling stack and a collaborative system of record for AI model development, pursuing a vision of AI reliability.
Business Model
Revenue Model
SaaS subscription model with tiered pricing based on API usage, traces/month, and enterprise features. Revenue streams include: (1) Free tier for developers and small teams, (2) Pro tier with monthly/annual subscriptions scaling with usage, (3) Enterprise tier with custom pricing for unlimited scale and on-premise deployments.
Pricing Tiers
For developers and small teams. Includes 5,000 traces per month, unlimited users, and unlimited custom evals.
Built for growing apps. Pricing scales based on number of traces. Includes everything in Free plus 50,000 traces per month, standard RBAC, advanced analytics & insights, and dedicated Slack support.
For teams needing unlimited scale and security. Includes everything in Pro plus unlimited traces, custom rate limits, deployment options (Hosted, VPC, or on-prem), enterprise-grade security (RBAC, SSO), dedicated CSM, real-time guardrails, 24/7 support, low-latency dedicated inference servers, and forward deployed engineering support.
Target Markets
- Enterprise AI teams
- Fortune 500 companies
- AI developers and data scientists
- Machine learning engineers
- GenAI application developers
- Technology companies
- RAG (Retrieval-Augmented Generation) systems
- AI Agents and agentic workflows
- Multi-agent AI systems
- Enterprise AI safety and security monitoring
- High-stakes environments requiring strict CI/CD for AI
- Rapid debugging and deployment of LLMs
- Comcast
- Twilio
- HP
- Magid