Alternatives to Arthur AI

Compare Arthur AI alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Arthur AI in 2026. Compare features, ratings, user reviews, pricing, and more from Arthur AI competitors and alternatives in order to make an informed decision for your business.

  • 1
    Gemini Enterprise Agent Platform
    Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
    Leader badge
    Compare vs. Arthur AI View Software
    Visit Website
  • 2
    Gantry

    Gantry

    Gantry

    Get the full picture of your model's performance. Log inputs and outputs and seamlessly enrich them with metadata and user feedback. Figure out how your model is really working, and where you can improve. Monitor for errors and discover underperforming cohorts and use cases. The best models are built on user data. Programmatically gather unusual or underperforming examples to retrain your model. Stop manually reviewing thousands of outputs when changing your prompt or model. Evaluate your LLM-powered apps programmatically. Detect and fix degradations quickly. Monitor new deployments in real-time and seamlessly edit the version of your app your users interact with. Connect your self-hosted or third-party model and your existing data sources. Process enterprise-scale data with our serverless streaming dataflow engine. Gantry is SOC-2 compliant and built with enterprise-grade authentication.
  • 3
    Evidently AI

    Evidently AI

    Evidently AI

    The open-source ML observability platform. Evaluate, test, and monitor ML models from validation to production. From tabular data to NLP and LLM. Built for data scientists and ML engineers. All you need to reliably run ML systems in production. Start with simple ad hoc checks. Scale to the complete monitoring platform. All within one tool, with consistent API and metrics. Useful, beautiful, and shareable. Get a comprehensive view of data and ML model quality to explore and debug. Takes a minute to start. Test before you ship, validate in production and run checks at every model update. Skip the manual setup by generating test conditions from a reference dataset. Monitor every aspect of your data, models, and test results. Proactively catch and resolve production model issues, ensure optimal performance, and continuously improve it.
    Starting Price: $500 per month
  • 4
    UpTrain

    UpTrain

    UpTrain

    Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users.
  • 5
    Arthur Online

    Arthur Online

    Arthur Online

    Arthur is an award-winning property management software designed to save your business time and money by streamlining each stage of the tenancy journey. Boost efficiency, increase your revenue and grow your portfolio. All your information on one dedicated financial console, directly integrated with market leading cloud accounting software. Arthur's powerful automation engine is designed to revolutionise your business. By systemising your workflows and offering powerful reporting, Arthur can save you hundreds of work hours, and we can even put everything in place for you.
    Starting Price: $64.30 per month
  • 6
    Arthur

    Arthur

    Arthur

    Arthur is intuitive to use and its functionalities aim at maximizing productivity for you and your team. Thanks to automated onboarding guides, it takes only very little time to be productive with Arthur. You’re free to work from wherever, with whoever, whenever you want in a truly collaborative environment. Significantly reduce spend on travels and office space, and save time for what really matters. The future of work is here. Increase your productivity and team output by using an immersive VR office space. Business travel is one of the largest contributors to C02 emission. Reduce your carbon footprint by 90%.
  • 7
    Langfuse

    Langfuse

    Langfuse

    Langfuse is an open source LLM engineering platform to help teams collaboratively debug, analyze and iterate on their LLM Applications. Observability: Instrument your app and start ingesting traces to Langfuse Langfuse UI: Inspect and debug complex logs and user sessions Prompts: Manage, version and deploy prompts from within Langfuse Analytics: Track metrics (LLM cost, latency, quality) and gain insights from dashboards & data exports Evals: Collect and calculate scores for your LLM completions Experiments: Track and test app behavior before deploying a new version Why Langfuse? - Open source - Model and framework agnostic - Built for production - Incrementally adoptable - start with a single LLM call or integration, then expand to full tracing of complex chains/agents - Use GET API to build downstream use cases and export data
    Starting Price: $29/month
  • 8
    Galileo

    Galileo

    Cisco

    Galileo is an AI observability and eval engineering platform that helps teams measure, protect, and improve AI systems in development and production. Now part of Cisco, the platform turns offline evaluations into production guardrails so teams can stop AI failures instead of only monitoring them. Galileo helps users build datasets from synthetic, development, and live production data, while capturing subject matter expert annotations as ground truth. The platform includes more than 20 out-of-the-box evals for RAG, agents, safety, security, and custom evaluation workflows. Its Luna models distill expensive LLM-as-judge evaluators into lower-cost, low-latency guardrails that can monitor production traffic. Built for enterprises and developers, Galileo helps teams debug failures, improve agent behavior, enforce AI policies, and ship AI applications with more confidence.
  • 9
    RagMetrics

    RagMetrics

    RagMetrics

    RagMetrics is a production-grade evaluation and trust platform for conversational GenAI, designed to assess AI chatbots, agents, and RAG systems before and after they go live. The platform continuously evaluates AI responses for accuracy, groundedness, hallucinations, reasoning quality, and tool-calling behavior across real conversations. RagMetrics integrates directly with existing AI stacks and monitors live interactions without disrupting user experience. It provides automated scoring, configurable metrics, and detailed diagnostics that explain when an AI response fails, why it failed, and how to fix it. Teams can run offline evaluations, A/B tests, and regression tests, as well as track performance trends in production through dashboards and alerts. The platform is model-agnostic and deployment-agnostic, supporting multiple LLMs, retrieval systems, and agent frameworks.
    Starting Price: $20/month
  • 10
    WhyLabs

    WhyLabs

    WhyLabs

    Enable observability to detect data and ML issues faster, deliver continuous improvements, and avoid costly incidents. Start with reliable data. Continuously monitor any data-in-motion for data quality issues. Pinpoint data and model drift. Identify training-serving skew and proactively retrain. Detect model accuracy degradation by continuously monitoring key performance metrics. Identify risky behavior in generative AI applications and prevent data leakage. Protect your generative AI applications are safe from malicious actions. Improve AI applications through user feedback, monitoring, and cross-team collaboration. Integrate in minutes with purpose-built agents that analyze raw data without moving or duplicating it, ensuring privacy and security. Onboard the WhyLabs SaaS Platform for any use cases using the proprietary privacy-preserving integration. Security approved for healthcare and banks.
  • 11
    Braintrust

    Braintrust

    Braintrust Data

    Braintrust is an AI observability and evaluation platform designed to help teams build, monitor, and improve AI systems in production. It enables users to capture and inspect real-time traces of AI interactions, including prompts, responses, and tool usage. The platform allows teams to measure performance using automated and human evaluations to ensure output quality. Braintrust helps identify issues such as hallucinations, regressions, and performance drops before they impact users. It supports prompt and model comparisons, making it easier to optimize AI workflows over time. With scalable trace ingestion and real-time monitoring, teams gain full visibility into how their AI systems behave. The platform integrates with multiple programming languages and tools, allowing developers to work within their existing tech stack. Overall, Braintrust provides a comprehensive solution for maintaining and improving AI quality at scale.
  • 12
    Censius AI Observability Platform
    Censius is an innovative startup in the machine learning and AI space. We bring AI observability to enterprise ML teams. Ensuring that ML models' performance is in check is imperative with the extensive use of machine learning models. Censius is an AI Observability Platform that helps organizations of all scales confidently make their machine-learning models work in production. The company launched its flagship AI observability platform that helps bring accountability and explainability to data science projects. A comprehensive ML monitoring solution helps proactively monitor entire ML pipelines to detect and fix ML issues such as drift, skew, data integrity, and data quality issues. Upon integrating Censius, you can: 1. Monitor and log the necessary model vitals 2. Reduce time-to-recover by detecting issues precisely 3. Explain issues and recovery strategies to stakeholders 4. Explain model decisions 5. Reduce downtime for end-users 6. Build customer trust
  • 13
    Respan

    Respan

    Respan

    Respan is a self-driving observability and evaluation platform built specifically for AI agents. It enables teams to trace full execution flows, including messages, tool calls, routing decisions, memory usage, and outcomes. The platform connects observability, evaluations, and optimization into a continuous improvement loop. Metric-first evaluations allow teams to define performance standards such as accuracy, cost, reliability, and safety. Respan also includes capability and regression testing to protect stable behaviors while improving new ones. An AI-powered evaluation agent analyzes failures, identifies root causes, and recommends next steps automatically. With compliance certifications including ISO 27001, SOC 2, GDPR, and HIPAA, Respan supports secure, large-scale AI deployments across industries.
    Starting Price: $0/month
  • 14
    Portkey

    Portkey

    Portkey.ai

    Launch production-ready apps with the LMOps stack for monitoring, model management, and more. Replace your OpenAI or other provider APIs with the Portkey endpoint. Manage prompts, engines, parameters, and versions in Portkey. Switch, test, and upgrade models with confidence! View your app performance & user level aggregate metics to optimise usage and API costs Keep your user data secure from attacks and inadvertent exposure. Get proactive alerts when things go bad. A/B test your models in the real world and deploy the best performers. We built apps on top of LLM APIs for the past 2 and a half years and realised that while building a PoC took a weekend, taking it to production & managing it was a pain! We're building Portkey to help you succeed in deploying large language models APIs in your applications. Regardless of you trying Portkey, we're always happy to help!
    Starting Price: $49 per month
  • 15
    Arize AI

    Arize AI

    Arize AI

    Automatically discover issues, diagnose problems, and improve models with Arize’s machine learning observability platform. Machine learning systems address mission critical needs for businesses and their customers every day, yet often fail to perform in the real world. Arize is an end-to-end observability platform to accelerate detecting and resolving issues for your AI models at large. Seamlessly enable observability for any model, from any platform, in any environment. Lightweight SDKs to send training, validation, and production datasets. Link real-time or delayed ground truth to predictions. Gain foresight and confidence that your models will perform as expected once deployed. Proactively catch any performance degradation, data/prediction drift, and quality issues before they spiral. Reduce the time to resolution (MTTR) for even the most complex models with flexible, easy-to-use tools for root cause analysis.
    Starting Price: $50/month
  • 16
    Fiddler AI

    Fiddler AI

    Fiddler AI

    Fiddler is a pioneer in Model Performance Management for responsible AI. The Fiddler platform’s unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. Model monitoring, explainable AI, analytics, and fairness capabilities address the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale, build trusted AI solutions, and increase revenue.
  • 17
    Mona

    Mona

    Mona

    Gain complete visibility into the performance of your data, models, and processes with the most flexible monitoring solution. Automatically surface and resolve performance issues within your AI/ML or intelligent automation processes to avoid negative impacts on both your business and customers. Learning how your data, models, and processes perform in the real world is critical to continuously improving your processes. Monitoring is the ‘eyes and ears' needed to observe your data and workflows to tell you if they’re performing well. Mona exhaustively analyzes your data to provide actionable insights based on advanced anomaly detection mechanisms, to alert you before your business KPIs are hurt. Take stock of any part of your production workflows and business processes, including models, pipelines, and business outcomes. Whatever datatype you work with, whether you have a batch or streaming real-time processes, and for the specific way in which you want to measure your performance.
  • 18
    Athina AI

    Athina AI

    Athina AI

    Athina is a collaborative AI development platform that enables teams to build, test, and monitor AI applications efficiently. It offers features such as prompt management, evaluation tools, dataset handling, and observability, all designed to streamline the development of reliable AI systems. Athina supports integration with various models and services, including custom models, and ensures data privacy through fine-grained access controls and self-hosted deployment options. The platform is SOC-2 Type 2 compliant, providing a secure environment for AI development. Athina's user-friendly interface allows both technical and non-technical team members to collaborate effectively, accelerating the deployment of AI features.
  • 19
    Comet

    Comet

    Comet

    Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.
    Starting Price: $179 per user per month
  • 20
    Orq.ai

    Orq.ai

    Orq.ai

    Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security.
  • 21
    Giskard

    Giskard

    Giskard

    Giskard provides interfaces for AI & Business teams to evaluate and test ML models through automated tests and collaborative feedback from all stakeholders. Giskard speeds up teamwork to validate ML models and gives you peace of mind to eliminate risks of regression, drift, and bias before deploying ML models to production.
  • 22
    Scorable

    Scorable

    Scorable

    Scorable is an AI evaluation and monitoring platform designed to help developers measure, control, and improve the behavior of applications built with large language models. It enables teams to create customized automated evaluators, sometimes referred to as AI “judges”, that assess how an AI system responds to users and whether its outputs meet defined quality standards such as accuracy, relevance, helpfulness, tone, and policy compliance. Developers can describe what they want to measure in plain language, and the platform generates a tailored evaluation stack that tests AI outputs against context-specific criteria rather than generic benchmarks. These evaluators can be embedded directly into application code, allowing AI systems such as chatbots, retrieval-augmented generation (RAG) systems, or autonomous agents to be continuously monitored in production environments.
    Starting Price: $19 per month
  • 23
    Openlayer

    Openlayer

    Openlayer

    Openlayer is the AI governance and observability platform that accelerates the evaluation and observability of agentic systems through 100+ automated tests and real-time guardrails that prevent prompt injections, PII leakage, bias, toxicity, and hallucinations, powering secure enterprise innovation. Designed to support both traditional ML and GenAI systems, Openlayer helps teams seamlessly handle everything from data-quality detection to automating comprehensive model evaluations, with full traceability across RAG, agents, and complex multi-step workflows. Trusted by Fortune 500 companies from early experimentation through production deployment and automated governance capabilities (NIST, EU AI Act, etc.)., Openlayer enables safe, reliable, and responsible AI operations.
  • 24
    Apache Geronimo
    Apache Geronimo is an open-source set of projects that are focused on providing JavaEE/JakartaEE libraries and Microprofile implementations. We are actively delivering reusable Java EE components though. They are widely used and still actively maintained! Apache Geronimo provides libraries for the implementations of the Java EE and Jakarta EE specifications. The implementations are also focused on providing OSGi bundle metadata. The goal of XBean project is to create a plugin-based server analogous to Eclipse is a plugin-based IDE. XBean will be able to discover, download and install server plugins from an Internet-based repository. In addition, we include support for multiple IoC systems, support for running with no IoC system, JMX without JMX code, lifecycle and class loader management, and rock-solid Spring integration. Apache Geronimo hosts several Microprofile implementations. Apache Geronimo Arthur is an effort to build a thin layer on top of Oracle GraalVM.
  • 25
    Arize Phoenix
    Phoenix is an open-source observability library designed for experimentation, evaluation, and troubleshooting. It allows AI engineers and data scientists to quickly visualize their data, evaluate performance, track down issues, and export data to improve. Phoenix is built by Arize AI, the company behind the industry-leading AI observability platform, and a set of core contributors. Phoenix works with OpenTelemetry and OpenInference instrumentation. The main Phoenix package is arize-phoenix. We offer several helper packages for specific use cases. Our semantic layer is to add LLM telemetry to OpenTelemetry. Automatically instrumenting popular packages. Phoenix's open-source library supports tracing for AI applications, via manual instrumentation or through integrations with LlamaIndex, Langchain, OpenAI, and others. LLM tracing records the paths taken by requests as they propagate through multiple steps or components of an LLM application.
  • 26
    MLflow

    MLflow

    MLflow

    MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.
  • 27
    Maxim

    Maxim

    Maxim

    Maxim is an agent simulation, evaluation, and observability platform that empowers modern AI teams to deploy agents with quality, reliability, and speed. Maxim's end-to-end evaluation and data management stack covers every stage of the AI lifecycle, from prompt engineering to pre & post release testing and observability, data-set creation & management, and fine-tuning. Use Maxim to simulate and test your multi-turn workflows on a wide variety of scenarios and across different user personas before taking your application to production. Features: Agent Simulation Agent Evaluation Prompt Playground Logging/Tracing Workflows Custom Evaluators- AI, Programmatic and Statistical Dataset Curation Human-in-the-loop Use Case: Simulate and test AI agents Evals for agentic workflows: pre and post-release Tracing and debugging multi-agent workflows Real-time alerts on performance and quality Creating robust datasets for evals and fine-tuning Human-in-the-loop workflows
    Starting Price: $29/seat/month
  • 28
    Weights & Biases

    Weights & Biases

    Weights & Biases

    Experiment tracking, hyperparameter optimization, model and dataset versioning with Weights & Biases (WandB). Track, compare, and visualize ML experiments with 5 lines of code. Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard. Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models. Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation. It's never been easier to share project updates. Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script. W&B Weave is here to help developers build and iterate on their AI applications with confidence.
  • 29
    Aquarium

    Aquarium

    Aquarium

    Aquarium's embedding technology surfaces the biggest problems in your model performance and finds the right data to solve them. Unlock the power of neural network embeddings without worrying about maintaining infrastructure or debugging embedding models. Automatically find the most critical patterns of model failures in your dataset. Understand the long tail of edge cases and triage which issues to solve first. Trawl through massive unlabeled datasets to find edge-case scenarios. Bootstrap new classes with a handful of examples using few-shot learning technology. The more data you have, the more value we offer. Aquarium reliably scales to datasets containing hundreds of millions of data points. Aquarium offers solutions engineering resources, customer success syncs, and user training to help customers get value. We also offer an anonymous mode for organizations who want to use Aquarium without exposing any sensitive data.
    Starting Price: $1,250 per month
  • 30
    Langtrace

    Langtrace

    Langtrace

    Langtrace is an open source observability tool that collects and analyzes traces and metrics to help you improve your LLM apps. Langtrace ensures the highest level of security. Our cloud platform is SOC 2 Type II certified, ensuring top-tier protection for your data. Supports popular LLMs, frameworks, and vector databases. Langtrace can be self-hosted and supports OpenTelemetry standard traces, which can be ingested by any observability tool of your choice, resulting in no vendor lock-in. Get visibility and insights into your entire ML pipeline, whether it is a RAG or a fine-tuned model with traces and logs that cut across the framework, vectorDB, and LLM requests. Annotate and create golden datasets with traced LLM interactions, and use them to continuously test and enhance your AI applications. Langtrace includes built-in heuristic, statistical, and model-based evaluations to support this process.
  • 31
    DeepEval

    DeepEval

    Confident AI

    DeepEval is a simple-to-use, open source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning, LangChain, or LlamaIndex, DeepEval has you covered. With it, you can easily determine the optimal hyperparameters to improve your RAG pipeline, prevent prompt drifting, or even transition from OpenAI to hosting your own Llama2 with confidence. The framework supports synthetic dataset generation with advanced evolution techniques and integrates seamlessly with popular frameworks, allowing for efficient benchmarking and optimization of LLM systems.
  • 32
    Teammately

    Teammately

    Teammately

    Teammately is an autonomous AI agent designed to revolutionize AI development by self-iterating AI products, models, and agents to meet your objectives beyond human capabilities. It employs a scientific approach, refining and selecting optimal combinations of prompts, foundation models, and knowledge chunking. To ensure reliability, Teammately synthesizes fair test datasets and constructs dynamic LLM-as-a-judge systems tailored to your project, quantifying AI capabilities and minimizing hallucinations. The platform aligns with your goals through Product Requirement Docs (PRD), enabling focused iteration towards desired outcomes. Key features include multi-step prompting, serverless vector search, and deep iteration processes that continuously refine AI until objectives are achieved. Teammately also emphasizes efficiency by identifying the smallest viable models, reducing costs, and enhancing performance.
    Starting Price: $25 per month
  • 33
    Trusys AI
    Trusys.ai is a unified AI assurance platform that helps organizations evaluate, secure, monitor, and govern artificial intelligence systems across their full lifecycle, from early testing to production deployment. It offers a suite of tools: TRU SCOUT for automated security and compliance scanning against global standards and adversarial vulnerabilities, TRU EVAL for comprehensive functional evaluation of AI applications (text, voice, image, and agent) assessing accuracy, bias, and safety, and TRU PULSE for real-time production monitoring with alerts for drift, performance degradation, policy violations, and anomalies. It provides end-to-end observability and performance tracking, enabling teams to catch unreliable output, compliance gaps, and production issues early. Trusys supports model-agnostic evaluation with a no-code, intuitive interface and integrates human-in-the-loop reviews and custom scoring metrics to blend expert judgment with automated metrics.
  • 34
    InsightFinder

    InsightFinder

    InsightFinder

    InsightFinder Unified Intelligence Engine (UIE) platform provides human-centered AI solutions for identifying incident root causes, and predicting and preventing production incidents. Powered by patented self-tuning unsupervised machine learning, InsightFinder continuously learns from metric time series, logs, traces, and triage threads from SREs and DevOps Engineers to bubble up root causes and predict incidents from the source. Companies of all sizes have embraced the platform and seen that business-impacting incidents can be predicted hours ahead with clearly pinpointed root causes. Survey a comprehensive overview of your IT Ops ecosystem, including patterns, trends, and team activities. Also view calculations that demonstrate overall downtime savings, cost of labor savings, and number of incidents resolved.
    Starting Price: $2.5 per core per month
  • 35
    SquareML

    SquareML

    SquareML

    SquareML is a no-code machine learning platform designed to democratize access to advanced data analytics and predictive modeling, particularly in the healthcare sector. It enables users, regardless of technical expertise, to harness machine learning capabilities without extensive coding knowledge. The platform specializes in data ingestion from multiple sources, including electronic health records, claims databases, medical devices, and health information exchanges. Key features include a no-code data science lifecycle, generative AI models for healthcare, unstructured data conversion, diverse machine learning models for predicting patient outcomes and disease progression, a library of pre-built models and algorithms, and seamless integration with various healthcare data sources. SquareML aims to streamline data processes, enhance diagnostic accuracy, and improve patient care outcomes by providing AI-powered insights.
  • 36
    LayerLens

    LayerLens

    LayerLens

    LayerLens is an independent AI model evaluation platform for understanding how models perform through verified results across benchmarks, prompt-level results, agentic benchmarks, and audit-ready comparisons across vendors. It helps teams compare more than 200 AI models side by side, with transparent benchmarks, model comparison tools, and consistent evaluation methods for accuracy, latency, behavior, and real-world applicability. LayerLens is built for deep model analysis through Spaces, where teams can group benchmarks and evaluations, explore task strengths, and track performance patterns in context. It supports continuous evaluation by running ongoing evals across model versions, prompt changes, judge updates, and live traces, helping teams detect quality regressions, drift, silent failures, contamination, and policy issues before they affect production.
  • 37
    Manot

    Manot

    Manot

    Your insight management platform for computer vision model performance. Pinpoint precisely where, how, and why models fail, bridging the gap between product managers and engineers through actionable insights. Manot provides an automated and continuous feedback loop for product managers to effectively communicate with engineering teams. Manot's simple user interface allows both technical and non-technical team members to benefit from the platform. Manot is designed with product managers in mind. Our platform provides actionable insights in the form of images pinpointing how, where, and why your model will perform poorly.
  • 38
    Ragas

    Ragas

    Ragas

    Ragas is an open-source framework designed to test and evaluate Large Language Model (LLM) applications. It offers automatic metrics to assess performance and robustness, synthetic test data generation tailored to specific requirements, and workflows to ensure quality during development and production monitoring. Ragas integrates seamlessly with existing stacks, providing insights to enhance LLM applications. The platform is maintained by a team of passionate individuals leveraging cutting-edge research and pragmatic engineering practices to empower visionaries redefining LLM possibilities. Synthetically generate high-quality and diverse evaluation data customized for your requirements. Evaluate and ensure the quality of your LLM application in production. Use insights to improve your application. Automatic metrics that helps you understand the performance and robustness of your LLM application.
  • 39
    ScoopML

    ScoopML

    ScoopML

    Easy-to-Use Build advanced predictive models without math & coding - in just a few clicks. Complete Experience. From cleaning data to building models to making predictions, we provide you all. Trustworthy. Know the 'why' behind AI decisions and drive business with actionable insights. Data Analytics in minutes, without writing code. The total process of building ML algorithms, explaining results, and predicting outcomes in one single click. Machine Learning in 3 Steps. Go from raw data to actionable analytics without writing a single line of code. Upload your data. Ask questions in plain english. Get the best performing model for your data and Share your results. Increase Customer Productivity. We help Companies to leverage no code Machine learning to improve their Customer Experience.
  • 40
    Scale Evaluation
    Scale Evaluation offers a comprehensive evaluation platform tailored for developers of large language models. This platform addresses current challenges in AI model assessment, such as the scarcity of high-quality, trustworthy evaluation datasets and the lack of consistent model comparisons. By providing proprietary evaluation sets across various domains and capabilities, Scale ensures accurate model assessments without overfitting. The platform features a user-friendly interface for analyzing and reporting model performance, enabling standardized evaluations for true apples-to-apples comparisons. Additionally, Scale's network of expert human raters delivers reliable evaluations, supported by transparent metrics and quality assurance mechanisms. The platform also offers targeted evaluations with custom sets focusing on specific model concerns, facilitating precise improvements through new training data.
  • 41
    LLM Council

    LLM Council

    LLM Council

    LLM Council is a lightweight multi-model orchestration tool that enables users to query several large language models simultaneously and synthesize their outputs into a single, higher-confidence response. Instead of relying on one AI system, it routes a prompt to a panel of models, each of which produces an independent answer before anonymously reviewing and ranking the others’ work. A designated “Chairman” model then combines the strongest insights into a unified final output, mimicking the dynamics of a panel of experts reaching consensus. It typically runs as a simple local web interface with a Python backend and React frontend and connects through aggregation services to access models from providers such as OpenAI, Google, and Anthropic. This structured peer-review workflow is designed to surface blind spots, reduce hallucinations, and improve answer reliability by introducing multiple perspectives and cross-model critique.
    Starting Price: $25 per month
  • 42
    fixa

    fixa

    fixa

    fixa is an open source platform designed to help monitor, debug, and improve AI-driven voice agents. It offers comprehensive tools to track key performance metrics, such as latency, interruptions, and correctness in voice interactions. Users can measure response times, track latency metrics like TTFW and p50/p90/p95, and flag instances where the voice agent interrupts the user. Additionally, fixa allows for custom evaluations to ensure the voice agent provides accurate responses, and it offers custom Slack alerts to notify teams when issues arise. With simple pricing models, fixa is tailored for teams at different stages, from those just getting started to organizations with custom needs. It provides volume discounts and priority support for enterprise clients, and it emphasizes data security with SOC 2 and HIPAA compliance options.
    Starting Price: $0.03 per minute
  • 43
    Onyx Security

    Onyx Security

    Onyx Security

    Onyx is a secure AI control plane for discovering, protecting, governing, optimizing, and measuring AI agents and models across the enterprise. It gives security, governance, and AI teams visibility into sanctioned and shadow AI across SaaS, cloud, endpoints, and code, including prompts, responses, and agent actions. AI Security helps strengthen posture, identify vulnerabilities, and enforce real-time safeguards against threats and misuse, while AI Governance supports security standards and regulatory requirements with opt-in coverage and policy controls defined in natural language. AI Orchestration reduces friction when setting up agents and MCPs and helps optimize for cost, accuracy, and latency. AI ROI measures adoption, sets goals, and tracks outcomes across departments. The Onyx Guardian Agent acts as a supervisory AI that continuously identifies risks and remediates issues across the platform, helping organizations manage large numbers of agents at scale.
  • 44
    Selene 1
    Atla's Selene 1 API offers state-of-the-art AI evaluation models, enabling developers to define custom evaluation criteria and obtain precise judgments on their AI applications' performance. Selene outperforms frontier models on commonly used evaluation benchmarks, ensuring accurate and reliable assessments. Users can customize evaluations to their specific use cases through the Alignment Platform, allowing for fine-grained analysis and tailored scoring formats. The API provides actionable critiques alongside accurate evaluation scores, facilitating seamless integration into existing workflows. Pre-built metrics, such as relevance, correctness, helpfulness, faithfulness, logical coherence, and conciseness, are available to address common evaluation scenarios, including detecting hallucinations in retrieval-augmented generation applications or comparing outputs to ground truth data.
  • 45
    Humanloop

    Humanloop

    Humanloop

    Eye-balling a few examples isn't enough. Collect end-user feedback at scale to unlock actionable insights on how to improve your models. Easily A/B test models and prompts with the improvement engine built for GPT. Prompts only get your so far. Get higher quality results by fine-tuning on your best data – no coding or data science required. Integration in a single line of code. Experiment with Claude, ChatGPT and other language model providers without touching it again. You can build defensible and innovative products on top of powerful APIs – if you have the right tools to customize the models for your customers. Copy AI fine tune models on their best data, enabling cost savings and a competitive advantage. Enabling magical product experiences that delight over 2 million active users.
  • 46
    Helicone

    Helicone

    Helicone

    Track costs, usage, and latency for GPT applications with one line of code. Trusted by leading companies building with OpenAI. We will support Anthropic, Cohere, Google AI, and more coming soon. Stay on top of your costs, usage, and latency. Integrate models like GPT-4 with Helicone to track API requests and visualize results. Get an overview of your application with an in-built dashboard, tailor made for generative AI applications. View all of your requests in one place. Filter by time, users, and custom properties. Track spending on each model, user, or conversation. Use this data to optimize your API usage and reduce costs. Cache requests to save on latency and money, proactively track errors in your application, handle rate limits and reliability concerns with Helicone.
    Starting Price: $1 per 10,000 requests
  • 47
    RagaAI

    RagaAI

    RagaAI

    RagaAI is the #1 AI testing platform that helps enterprises mitigate AI risks and make their models secure and reliable. Reduce AI risk exposure across cloud or edge deployments and optimize MLOps costs with intelligent recommendations. A foundation model specifically designed to revolutionize AI testing. Easily identify the next steps to fix dataset and model issues. The AI-testing methods used by most today increase the time commitment and reduce productivity while building models. Also, they leave unforeseen risks, so they perform poorly post-deployment and thus waste both time and money for the business. We have built an end-to-end AI testing platform that helps enterprises drastically improve their AI development pipeline and prevent inefficiencies and risks post-deployment. 300+ tests to identify and fix every model, data, and operational issue, and accelerate AI development with comprehensive testing.
  • 48
    Mistral Forge

    Mistral Forge

    Mistral AI

    Mistral AI’s Forge platform enables enterprises to build customized AI models tailored to their internal data, workflows, and domain expertise. It provides end-to-end model development capabilities, covering everything from pre-training and synthetic data generation to reinforcement learning and evaluation. Organizations can integrate proprietary datasets and decision frameworks to create models that align closely with their business needs. Forge supports flexible deployment options, allowing companies to run models on-premises, in private cloud environments, or through Mistral infrastructure. The platform emphasizes security and governance, ensuring strict data isolation and compliance with enterprise policies. It also includes advanced evaluation tools that measure performance based on business-specific KPIs rather than generic benchmarks. By managing the full AI lifecycle in one system, Forge helps companies transform institutional knowledge into high-performing AI.
  • 49
    Arena.ai

    Arena.ai

    Arena.ai

    Arena is a community-powered platform designed to evaluate AI models based on real-world usage and feedback. Created by researchers from UC Berkeley, it enables users to test and compare frontier AI models across various tasks. The platform gathers insights from millions of builders, researchers, and creative professionals to generate transparent performance rankings. Arena’s public leaderboard reflects how models perform in practical scenarios rather than controlled benchmarks. Users can compare models side by side and provide feedback that helps shape future AI development. It supports a wide range of use cases, including text generation, coding, image creation, and video production. By leveraging collective input, Arena advances the understanding and improvement of AI technologies.
  • 50
    Randoli

    Randoli

    Randoli

    Randoli is an OpenTelemetry-native observability and cost management platform for Kubernetes, multicloud, hybrid, and AI/ML workloads. It brings infrastructure health, application performance, logs, metrics, traces, incidents, and cloud costs into one control plane, helping teams replace fragmented tools with a correlated view of system behavior. Its federated architecture separates the control plane from the data plane, analyzes telemetry locally, extracts relevant signals, and retrieves data on demand during investigations, reducing ingestion and egress while supporting data sovereignty. Randoli monitors clusters, nodes, pods, workloads, services, dependencies, latency, errors, throughput, and resource usage across AWS, Azure, Google Cloud, OpenShift, and on-premises environments. OpenTelemetry and eBPF provide automatic, low-overhead instrumentation, filtering, enriched telemetry, and real-time signal correlation.
    Starting Price: $0.04 per hour