Galileo Technologies, Inc.
UnclaimedGalileo Technologies, Inc. provides an enterprise AI reliability platform for evaluating, monitoring, and safeguarding AI agents and applications.
Overview
Galileo Technologies, Inc. is the enterprise AI reliability company behind Galileo’s evaluation, monitoring, and guardrail platform for generative AI. The company enables AI teams to assess, iterate, monitor, and protect AI applications at enterprise scale. Its approach focuses on building AI that is trustworthy, safe, and observable by providing end-to-end workflows for evaluation, real-time monitoring, and guardrail capabilities. Serving startups through large organizations, Galileo helps teams reduce hallucinations, improve performance, and move AI from experimentation to production with measurable confidence in behavior and outcomes. The organization emphasizes a holistic view of AI systems, supporting development lifecycle practices that align engineering, product, and governance around reliable AI deployments.
Mission statement
We believe AI can be trustworthy, safe, and observable, and we are building workflows that span evaluation, monitoring, observability, and guardrails to help developers ship reliable AI.
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What we offer
Galileo Evaluate
Streamline AI evaluations with tailored assessments for accurate and reliable outcomes.
Pricing not published
Galileo Observe
Achieve Real-Time Monitoring and Control Over Your AI Systems.
Pricing not published
observe.docs.galileo.ai/Galileo Protect
Ensure safe and reliable AI with real-time risk mitigation and policy enforcement.
Pricing not published
galileo.ai/protectGalileo Signals
Proactively detects hidden failures in AI systems to ensure reliability and improve performance.
Pricing not published
Luna-2
Luna-2 ensures reliable AI evaluations and guardrailing for enterprise applications.
Pricing not published
galileo.ai/luna-2Market segments
Market size by segment
Growth potential (CAGR)
Continuous model evaluation and validation
In-environment testing, continuous evaluations, drift detection, and validation workflows that assess models from pre-production through production to ensure policy compliance and performance.
Products: Galileo Evaluate, Galileo Signals, Luna-2
AI observability and trace analytics
Capture, store, query, and investigate agent traces, prompts, tool calls, and decisions at scale with natural-language search and fast full-text querying for root-cause analysis.
Products: Galileo Observe, Galileo Signals, Galileo Evaluate
Runtime AI protection
Real-time threat detection and context-aware enforcement for AI applications and autonomous agents to prevent prompt injection, data leakage, and unsafe actions with low-latency inline protections and runtime guardrails.
Products: Galileo Protect, Galileo Evaluate, Luna-2
Automated failure detection and remediation
Automated detection of failure patterns from production traces, instant generation of targeted evaluations, institutional memory, and mechanisms for rapid remediation.
Products: Galileo Signals, Galileo Observe, Galileo Evaluate
More information about our offering
Galileo Evaluate
Galileo Evaluate is an evaluation platform for generative AI at enterprise scale. It enables teams to evaluate, iterate, monitor, and govern AI applications, offering built-in evaluation capabilities and support for custom evaluators that encode domain knowledge across development lifecycles. Key features include governance through evaluations, real-time monitoring, and support for both prebuilt and customizable metrics.
Pricing not published
- Guides Behavior In ProductionEnsure that agent actions and tool accesses are closely monitored and adjusted based on evaluation results to maintain control and accountability.
- Transforms For Production GuardrailsAllows seamless transitions from testing environments to production-ready configurations, ensuring AI consistency and reliability are maintained.
- Prebuilt Evaluations AvailableProvides immediate access to essential evaluation tools, enabling faster deployment and adaptability to specific industry requirements.
- Monitors Performance ContinuouslyAutomatically detects anomalies and potential failures in real-time, allowing for immediate troubleshooting and adjustments.
- Simplifies IntegrationEmpowers teams to implement governance without extensive coding, facilitating quick setup and reducing development time.
- Tailors Evaluations To NeedsFacilitates a targeted approach to evaluation, ensuring results are aligned with specific business or operational objectives.
Galileo Observe
Galileo Observe is the production observability and monitoring solution that provides real-time visibility into AI agent behavior, enabling rapid debugging and performance optimization at scale. Key features include 24/7 monitoring, end-to-end visibility, and real-time alerts to enhance system performance.
Pricing not published
- Ensure Proactive Issue DetectionReal-time alerts and comprehensive monitoring keep your AI systems operational and efficient.
- Visualize Every InteractionGain complete clarity on how inputs affect outputs to optimize workflows and performance.
- Quickly Respond to IssuesInstant notifications help teams address problems without delays, reducing downtime.
- Identify Failure PointsDetailed tracing allows for precise identification of problem areas, streamlining debugging efforts.
- Enhance Monitoring EfficiencyCustomizable insights evolve with your system, ensuring ongoing relevance and optimization.
- Reduce DowntimeImmediate insights into root causes foster quicker solutions and continuous performance enhancements.
Galileo Protect
Galileo Protect provides guardrails and safeguards to production AI systems, enabling real-time risk mitigation and policy enforcement to prevent harmful or unsafe outputs. Key features include real-time guardrails, customizable policies, and proactive anomaly detection for enhanced security.
Pricing not published
- Blocks Unsafe OutputsAutomatically prevents harmful responses, ensuring only compliant outputs are generated.
- Customizable Safety ProtocolsTailor specific rules for your AI applications, addressing unique business requirements.
- Human OversightEnsure a safety net by routing uncertain outputs to human reviewers for evaluation.
- Detect Unknown IssuesPinpoint potential problems before they escalate into significant risks.
Galileo Signals
Galileo Signals automatically detects failure patterns in AI agents from production traces, surfacing unknown or emerging issues and enabling rapid evals and remediation. Key features include instant evaluation generation and proactive failure detection to support continuous improvement.
Pricing not published
- Generate Evals InstantlyTransform identified signals into evaluations with a single click, greatly enhancing workflow efficiency.
- Identify Failures EarlyDetect emerging issues and prevent potential disasters by analyzing 100% of production traces.
- Learn and ImproveBuild institutional knowledge over time to enhance the detection of issues that were previously unknown.
- Track Issue HistoryUtilize historical data to accurately assess and manage system reliability.
Luna-2
Luna-2 is Galileo’s production-oriented family of small language models designed for agent reliability and real-time evaluation, available in 3B and 8B parameter sizes and optimized for low latency. Key features include ultra-low latency and an optimized inference engine for consistent performance.
Pricing not published
- Achieve Fast EvaluationsLuna-2 can process evaluations with ultra-low latency, ensuring optimal performance in time-sensitive AI applications.
- Mitigate Risks InstantlyWith its real-time guardrails, Luna-2 can intercept harmful actions swiftly, enhancing reliability across AI systems.
- Ensure Consistent PerformanceLuna-2 operates on a tailored infrastructure designed for robust AI evaluations, ensuring reliability and speed.
- Choose Optimal Model SizeLuna-2's flexible configuration allows organizations to select a model that best fits their specific evaluation needs.
- Leverage Extensive Evaluation MetricsThis architecture allows for efficient monitoring and evaluation across various AI tasks without duplicating resources.
Sources
Methodology and sourcing behind the figures and links shown above.
Continuous model evaluation and validation
Multiple market reports for model evaluation/validation platforms cluster mid‑2020s market size between about $1.1–1.8B. I select a midpoint (~$1.5B) for the continuous evaluation/validation segment. Forecast CAGRs in the results vary widely (≈9.6%–28.5%); given rapid AI adoption, regulatory drivers, and the range of published forecasts, I estimate a realistic growth potential near 20% CAGR over the coming years.
- Market at USD 1.15 billion in 2026; expected USD 9.57 billion by 2035 at a CAGR of 9.57%.
- Market valued at USD 1.84 billion in 2025E; expected to reach USD 6.50 billion by 2033 at a CAGR of 17.17%.
- Global market size in 2024 stands at USD 1.31 billion; expected CAGR 28.5% reaching USD 11.97 billion by 2033.
- Expected to grow to $6.24 billion in 2030 at a compound annual growth rate (CAGR) of 27.5%.
AI observability and trace analytics
Estimate based on multiple market reports in the provided search results: specialist AI-observability research (Next Move / NextMSC) places AI observability at roughly USD 2.9B (2025) with very high growth (31.1% CAGR). Data-observability reports (Spherical Insights, Precedence) show smaller adjacent markets (USD ~1.1–1.93B in 2025) and lower CAGRs (≈11–15%), while broader observability platforms (MarketsandMarkets) are much larger but grow more slowly (~12% CAGR). Given the user segment (AI observability + trace/agent analytics) is narrower than general observability but aligned with AI/agent monitoring, the current market is estimated near USD 3.0B and growth potential is aligned with the AI-observability forecast (≈31.1% CAGR).
- The global AI observability market size was valued at USD 2.94 billion in 2025; expanding at a 31.1% CAGR between 2026 and 2035.
- The Global Data Observability Market Size Was Estimated at USD 1.927 billion in 2025; CAGR of around 15.44% (2026–2035).
- The observability tools & platforms market is estimated at USD 11.71 billion in 2026 and projected to reach USD 20.72 billion by 2031, at a CAGR of 12.1%.
Runtime AI protection
Estimate based on recent market reports for runtime application self-protection (RASP) and AI TRiSM/runtime protection. ResearchNester and MarketsandMarkets place the RASP/AI TRiSM market around $3.1–3.5B in 2026; MarketsandMarkets calls out ~30%+ CAGR for AI TRiSM and 33.1% for AI security & runtime protection. A midpoint current-size (~$3.3B) and a high-growth CAGR (~30%) reflect the segment’s alignment with rapid AI/agent adoption and cited subsegment growth rates, while acknowledging lower RASP estimates (≈18.9% CAGR) in some reports.
- In the year 2026, the industry size of runtime application self-protection is evaluated at USD 3.47 billion.
- The AI TRiSM market is projected to grow from USD 3.09 billion in 2026 to USD 11.61 billion by 2031, at a CAGR of 30.3%.
- Global runtime application self-protection market Size Expected to Grow from USD 874.26 million in 2026 to USD 4180.89 million by 2035, at a CAGR of 18.9%.
Automated failure detection and remediation
Estimate based on multiple industry reports for the closely related "fault detection and classification" market (covers automated failure detection/remediation). Future Market Insights cites USD 5.5 billion (2025) and a 8.7% CAGR; other reports show similar 2025 valuations (≈$5.35–$6.58B) and CAGRs around 8.7–9.0%, so I use USD 5.5B and CAGR 8.7% as a conservative central estimate.
- projected to grow from USD 5.5 billion in 2025 to USD 12.7 billion by 2035, at a CAGR of 8.7%.
- The Fault Detection and Classification Market size was valued at USD 6.58 billion in 2025 and is expected to grow to USD 15.34 billion by 2035.
- increase from $5.35 billion in 2025 to $5.83 billion in 2026, representing a compound annual growth rate (CAGR) of 9.0%.
- Galileo Technologies, Inc.
- Galileo Observe
- Galileo Protect
- Luna-2
- Market at USD 1.15 billion in 2026; expected USD 9.57 billion by 2035 at a CAGR of 9.57%.
- Market valued at USD 1.84 billion in 2025E; expected to reach USD 6.50 billion by 2033 at a CAGR of 17.17%.
- Global market size in 2024 stands at USD 1.31 billion; expected CAGR 28.5% reaching USD 11.97 billion by 2033.
- Expected to grow to $6.24 billion in 2030 at a compound annual growth rate (CAGR) of 27.5%.
- The global AI observability market size was valued at USD 2.94 billion in 2025; expanding at a 31.1% CAGR between 2026 and 2035.
- The Global Data Observability Market Size Was Estimated at USD 1.927 billion in 2025; CAGR of around 15.44% (2026–2035).
- The observability tools & platforms market is estimated at USD 11.71 billion in 2026 and projected to reach USD 20.72 billion by 2031, at a CAGR of 12.1%.
- In the year 2026, the industry size of runtime application self-protection is evaluated at USD 3.47 billion.
- The AI TRiSM market is projected to grow from USD 3.09 billion in 2026 to USD 11.61 billion by 2031, at a CAGR of 30.3%.
- Global runtime application self-protection market Size Expected to Grow from USD 874.26 million in 2026 to USD 4180.89 million by 2035, at a CAGR of 18.9%.
- projected to grow from USD 5.5 billion in 2025 to USD 12.7 billion by 2035, at a CAGR of 8.7%.
- The Fault Detection and Classification Market size was valued at USD 6.58 billion in 2025 and is expected to grow to USD 15.34 billion by 2035.
- increase from $5.35 billion in 2025 to $5.83 billion in 2026, representing a compound annual growth rate (CAGR) of 9.0%.
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