Akira AI Alternatives

Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.

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.

Deeploy helps you to stay in control of your ML models. Easily deploy your models on our responsible AI platform, without compromising on transparency, control, and compliance. Nowadays, transparency, explainability, and security of AI models is more important than ever. Having a safe and secure environment to deploy your models enables you to continuously monitor your model performance with confidence and responsibility. Over the years, we experienced the importance of human involvement with machine learning. Only when machine learning systems are explainable and accountable, experts and consumers can provide feedback to these systems, overrule decisions when necessary and grow their trust. That’s why we created Deeploy.

Watsonx is our upcoming enterprise-ready AI and data platform designed to multiply the impact of AI across your business. The platform comprises three powerful components: the watsonx.ai studio for new foundation models, generative AI and machine learning; the watsonx.data fit-for-purpose store for the flexibility of a data lake and the performance of a data warehouse; plus the watsonx.governance toolkit, to enable AI workflows that are built with responsibility, transparency and explainability. Watsonx is our enterprise-ready AI and data platform designed to multiply the impact of AI across your business. The platform comprises three powerful products: the watsonx.ai studio for new foundation models, generative AI and machine learning; the watsonx.data fit-for-purpose data store, built on an open lakehouse architecture; and the watsonx.governance toolkit, to accelerate AI workflows that are built with responsibility, transparency and explainability.

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.

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.

Viso Suite is the world’s only end-to-end platform for computer vision. It enables teams to rapidly train, create, deploy and manage computer vision applications – without writing code from scratch. Use Viso Suite to deliver industry-leading computer vision and real-time deep learning systems with low-code and automated software infrastructure. The use of traditional development methods, fragmented software tools, and the lack of experienced engineers are costing organizations lots of time and leading to inefficient, low-performing, and expensive computer vision systems. Build and deploy better computer vision applications faster by abstracting and automating the entire lifecycle with Viso Suite, the all-in-one enterprise vision platform.​ Collect data for computer vision annotation with Viso Suite. Use automated collection capabilities to gather high-quality training data. Control and secure all data collection. Enable continuous data collection to further improve your AI models.

Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.

Developing AI solutions requires an engineering approach that is resilient, open and repeatable to ensure necessary quality and agility is achieved. Until today these efforts are missing the foundation to address these challenges amid a sea of point tools and fast changing models and data. Collaborative developer platform for automating development and control of AI applications across multiple personas. Derive hyper-detailed customer profiles from enterprise data to predict behaviors in real-time and at scale. Generate AI-powered models designed to continuously learn and achieve clearly defined business outcomes. Enables organizations to explain and prove compliance with applicable rules and regulations. CognitiveScale's Cortex AI Platform addresses enterprise AI use cases through modular platform offerings. Our customers consume and leverage its capabilities as microservices within their enterprise AI initiatives.

Accelerate the end-to-end machine learning lifecycle. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.

Capture production data, evaluate outputs collaboratively, and fine-tune your LLM's performance. Know exactly what goes on in production with an in-depth log overview. Collaborate with product managers, domain experts and engineers to build reliable model outputs. Track AI metrics such as speed, quality scores, and token usage. Copilot automates evaluations and model improvements for your use case. Create, manage, and optimize prompts to achieve precise and relevant interactions between users and AI models. Compare foundation models, and fine-tuned versions to improve prompt performance and save tokens. Collaborate with your team to build a proprietary fine-tuning dataset for your AI models. Build custom fine-tuning datasets to optimize model performance for specific use cases.

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.

Empower your ML teams to deliver robust and performant AI models by auto-diagnosing and improving your data and models. The only platform that can auto-diagnose data and models, empowering ML teams to deliver robust and performant AI models faster. Covering camera noise, sign stickers, shadows, and others. Confirmed with real-world images on which the model systematically fails. While improving model accuracy by 0.2%. Our mission is to change the way the next generation of AI systems is built. If we are to use AI in our businesses, at doctor’s offices, on our roads, or in our homes, we need to build AI systems that companies and users can trust. We are leading AI professors and researchers from ETH Zurich with broad expertise in formal methods, symbolic reasoning, and machine learning. We started LatticeFlow with the goal of building the world’s first platform that enables companies to deliver robust AI models that work reliably in the wild.

Klu.ai is a Generative AI platform that simplifies the process of designing, deploying, and optimizing AI applications. Klu integrates with your preferred Large Language Models, incorporating data from varied sources, giving your applications unique context. Klu accelerates building applications using language models like Anthropic Claude, Azure OpenAI, GPT-4, and over 15 other models, allowing rapid prompt/model experimentation, data gathering and user feedback, and model fine-tuning while cost-effectively optimizing performance. Ship prompt generations, chat experiences, workflows, and autonomous workers in minutes. Klu provides SDKs and an API-first approach for all capabilities to enable developer productivity. Klu automatically provides abstractions for common LLM/GenAI use cases, including: LLM connectors, vector storage and retrieval, prompt templates, observability, and evaluation/testing tooling.

vishwa.ai is an AutoOps platform for AI and ML use cases. It provides expert prompt delivery, fine-tuning, and monitoring of Large Language Models (LLMs). Features: Expert Prompt Delivery: Tailored prompts for various applications. Create no-code LLM Apps: Build LLM workflows in no time with our drag-n-drop UI Advanced Fine-Tuning: Customization of AI models. LLM Monitoring: Comprehensive oversight of model performance. Integration and Security Cloud Integration: Supports Google Cloud, AWS, Azure. Secure LLM Integration: Safe connection with LLM providers. Automated Observability: For efficient LLM management. Managed Self-Hosting: Dedicated hosting solutions. Access Control and Audits: Ensuring secure and compliant operations.

Train and deploy GPT models for any use case with the first no-code AI platform for businesses. Our prompt experts are here to help you. If you're looking to fine-tune open source models with your own data, our cost-effective tools are specifically designed for the same. Securely deploy your own open source model across multiple clouds without the need to rely on third-party vendors for your valuable data. Our team of experts will deliver the perfect app tailored to your specific requirements. Our tool enables you to effortlessly monitor your usage and reduce costs. Partner with us and let our expert team address your pain points effectively. Efficiently classify your customer calls and automate your company’s customer service with ease. Our advanced solution empowers you to streamline customer interactions and enhance service delivery. Build a robust system that detects fraud and anomalies in your data based on previously flagged data points.

Citrusˣ’s end-to-end platform for AI transparency and explainability allows organizations to maintain confidence in their models. Data scientists can use the Summary and Validation pages on the web UI and SDK to validate the performance of their models, investigate results, and address issues. Data science managers and Chief data officers can track the work of their teams, compare models, and ensure KPIs are being met. Risk officers and MRMs can use the web UI and reports to verify the soundness of the model, assess the risks, and ensure AI is being used responsibly and fairly according to regulatory requirements. Executives and regulators can use summarized custom reports to verify the model's strength and accuracy, understand the model's decisions, identify risks, and ensure compliance to protect the organization from potential lawsuits and maintain its reputation.

By using the best-performing model for each request, we can achieve higher performance than any single model. Martian outperforms GPT-4 across OpenAI's evals (open/evals). We turn opaque black boxes into interpretable representations. Our router is the first tool built on top of our model mapping method. We are developing many other applications of model mapping including turning transformers from indecipherable matrices into human-readable programs. If a company experiences an outage or high latency period, automatically reroute to other providers so your customers never experience any issues. Determine how much you could save by using the Martian Model Router with our interactive cost calculator. Input your number of users, tokens per session, and sessions per month, and specify your cost/quality tradeoff.

Ours is the world’s first & only end-to-end platform for all your AI-powered innovation needs — right from data cleansing & structuring, to creating & deploying advanced data-science models, to infusing advanced analytics algorithms with built-in Recommendation AI, to deducing the outcomes with easy-to-deduce visualization dashboards, as well as Explainable AI to backtrack how the outcomes were derived, our no-code AI platform can do it all! Our platform offers a holistic, seamless data science experience. With key features like a robust Data Lakehouse, a unique AI Studio, a comprehensive AI Marketplace, and a world-class data-science support team (on a need basis), FutureAnalytica is geared to reduce your time, efforts & costs across your data-science & AI journey. Initiate discussions with the leadership, followed by a quick technology assessment in 1–3 days. Build ready-to-integrate AI solutions using FA's fully automated data science & AI platform in 10–18 days.

Minerva is our proprietary AI platform that we use internally to build AI applications that perform real-world tasks requiring human-level understanding and explainability. As Minerva’s reach grows through the deployment of domain-specific AI applications, Minerva compounds knowledge, performs increasingly general tasks and connects interdisciplinary dots humans cannot. We use these powerful components to build our scalable AI applications such as Argus and Supernova. Use Minerva to build your own AI workforce and transcend information complexity to make more accurate mission-critical decisions at lightning speed. Minerva enables natural user interaction with various dashboards and APIs for consuming insight, providing feedback and securely integrating Accrete’s AI applications into existing enterprise workflows.

Cerebro is a cutting-edge generative AI platform designed for enterprises. This versatile multi-model platform enables users to create, manage, and deploy generative AI applications 10x faster. With Cerebro, ensure responsible AI development through meticulous governance and adherence to applicable regulations. Empower your organization to innovate and thrive in the AI era. Key Features: Multi-model support Accelerated development and deployment Robust governance and compliance Scalable and adaptable architecture

Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.

Monitor your LLMs in production, and discover and fix hallucinations, accuracy, and quality-related errors with LLM outputs seamlessly. Evaluate your outputs for hallucinations, misinformation, quality issues, and other bad outputs. Configurable for any LLM use case. Segment your data to analyze your cost, accuracy, response times, model usage, and feedback in depth. Search, sort, and filter through your inference calls, and trace through your queries, retrievals, prompts, responses, and feedback metrics to debug generations. Explore your conversations, understand what your users are talking about and how they feel, and learn which conversations ended badly. Compare your performance metrics across different models and prompts. Our insights will help you find the best-performing model for every use case. Our evaluators use your data, configurations, and feedback to get better and analyze the outputs better.

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.

Scale's mission is to accelerate the development of AI applications. Better data leads to more performant models. Performant models lead to faster deployment. We help deliver value from AI investments faster with better data by providing an end-to-end solution to manage the entire ML lifecycle. Combining cutting edge technology with operational excellence, we help teams develop the highest-quality datasets because better data leads to better 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!

Use Prompt Mixer to create prompts and chains. Combinе your chains with datasets and improve with AI. Develop a comprehensive set of test scenarios to assess various prompt and model pairings, determining the optimal combination for diverse use cases. Incorporate Prompt Mixer into your everyday tasks, from creating content to conducting R&D. Prompt Mixer can streamline your workflow and boost productivity. Use Prompt Mixer to efficiently create, assess, and deploy content generation models for various applications such as blog posts and emails. Use Prompt Mixer to extract or merge data in a completely secure manner and easily monitor it after deployment.

Use BenchLLM to evaluate your code on the fly. Build test suites for your models and generate quality reports. Choose between automated, interactive or custom evaluation strategies. We are a team of engineers who love building AI products. We don't want to compromise between the power and flexibility of AI and predictable results. We have built the open and flexible LLM evaluation tool that we have always wished we had. Run and evaluate models with simple and elegant CLI commands. Use the CLI as a testing tool for your CI/CD pipeline. Monitor models performance and detect regressions in production. Test your code on the fly. BenchLLM supports OpenAI, Langchain, and any other API out of the box. Use multiple evaluation strategies and visualize insightful reports.

Whether you're building AI chatbots, virtual assistants, or other intelligent applications, set up your workspace effortlessly by integrating GPT-powered language models with your provider keys for unparalleled performance. Accelerate the creation of your diverse AI applications using LLM Spark's GPT-driven templates or craft unique projects from the ground up. Test & compare multiple models simultaneously for optimal performance across multiple scenarios. Save prompt versions and history effortlessly while streamlining development. Invite members to your workspace and collaborate on projects with ease. Semantic search for powerful search capabilities to find documents based on meaning, not just keywords. Deploy trained prompts effortlessly, making AI applications accessible across platforms.

Semantic Kernel is a lightweight, open-source development kit that lets you easily build AI agents and integrate the latest AI models into your C#, Python, or Java codebase. It serves as an efficient middleware that enables rapid delivery of enterprise-grade solutions. Microsoft and other Fortune 500 companies are already leveraging Semantic Kernel because it’s flexible, modular, and observable. Backed with security-enhancing capabilities like telemetry support, hooks, and filters you’ll feel confident you’re delivering responsible AI solutions at scale. Version 1.0+ support across C#, Python, and Java means it’s reliable, and committed to nonbreaking changes. Any existing chat-based APIs are easily expanded to support additional modalities like voice and video. Semantic Kernel was designed to be future-proof, easily connecting your code to the latest AI models evolving with the technology as it advances.

Ever Efficient AI offers a powerful yet accessible AI automation platform helping businesses maximize efficiency - without hiring a full-time AI engineer on the team. Their flexible subscription plans connect you with AI experts who build customized data solutions tailored to your specific workflows and industry. No complex modeling or coding is required on your end. The collaborative process lets those with domain expertise guide tool development. EverEfficientAI's team manages the technical complexity behind the scenes, converting your datasets and processes into optimized AI systems. Bi-weekly agile sprints adapt the tools over time while providing transparency. With a focus on usability and rapid integration, EverEfficientAI makes advanced AI easily actionable by any organization. The future of work is here - are you ready to let your data work smarter for you?

Langtail is an end-to-end platform that accelerates the development and deployment of language model (LLM) applications. It enables companies to rapidly experiment, collaborate, and launch production-grade LLM products. Key features include: 1. No-code LLM playground for prompt debugging and ideation 2. Collaborative workspaces for sharing prompts and insights 3. Comprehensive observability suite with logging and analytics 4. Evaluation framework for systematically testing prompt performance 5. Deployment infrastructure for serving prompts via API in multiple environments 6. Upcoming fine-tuning capabilities to improve models with user feedback Langtail empowers both technical and non-technical teams to find high-value LLM use cases, refine prompts for reliable performance, and deploy applications with ease. It's the all-in-one platform to take your LLM projects from prototype to production faster than ever.

Guardrails are crucial in AI maintenance, LangWatch safeguards you and your business from exposing sensitive data, prompt injection and keeps your AI from going off the rails, avoiding unforeseen damage to your brand. Understanding the behaviour of both AI and users can be challenging for businesses with integrated AI. Ensure accurate and appropriate responses by constantly maintaining quality through oversight. LangWatch’s safety checks and guardrails prevent common AI issues including jailbreaking, exposing sensitive data, and off-topic conversations. Track conversion rates, output quality, user feedback and knowledge base gaps with real-time metrics — gain constant insights for continuous improvement. Powerful data evaluation allows you to evaluate new models and prompts, develop datasets for testing and run experimental simulations on tailored builds.

PredictSense is an end-to-end Machine Learning platform powered by AutoML to create AI-powered analytical solutions. Fuel the new technological revolution of tomorrow by accelerating machine intelligence. AI is key to unlocking value from enterprise data investments. PredictSense enables businesses to monetize critical data infrastructure and technology investments by creating AI driven advanced analytical solutions rapidly. Empower data science and business teams with advanced capabilities to quickly build and deploy robust technology solutions at scale. Easily integrate AI into the current product ecosystem and fast track GTM for new AI solutions. Incur huge savings in cost, time and effort by building complex ML models in AutoML. PredictSense democratizes AI for every individual in the organization and creates a simple, user-friendly collaboration platform to seamlessly manage critical ML deployments.

The NeoPulse Product Suite includes everything needed for a company to start building custom AI solutions based on their own curated data. Server application with a powerful AI called “the oracle” that is capable of automating the process of creating sophisticated AI models. Manages your AI infrastructure and orchestrates workflows to automate AI generation activities. A program that is licensed by the organization to allow any application in the enterprise to access the AI model using a web-based (REST) API. NeoPulse is an end-to-end automated AI platform that enables organizations to train, deploy and manage AI solutions in heterogeneous environments, at scale. In other words, every part of the AI engineering workflow can be handled by NeoPulse: designing, training, deploying, managing and retiring.

In just a few clicks, you can build, deploy, and monitor AI-powered solutions, with no coding or ML expertise required. Stop puzzling together disjointed tools, featuring-engineering your way to production, and calling in favors to get results. Managing all your AI initiatives is a breeze with a platform engineered to build, monitor, and improve your AI solutions across the entire lifecycle. No more feature engineering and hyperparameter tuning. Anything built in Graft is guaranteed to work in the production environment because the platform is the production environment. Every business is unique, and so should your AI solution. From foundation models to pretraining to fine-tuning, control remains firmly in your grasp to tailor solutions to meet your business and privacy needs. Unlock the value of your unstructured and structured data, including text, images, video, audio, and graphs. Control and customize your solutions at scale.

Wordware enables anyone to develop, iterate, and deploy useful AI agents. Wordware combines the best aspects of software with the power of natural language. Remove constraints of traditional no-code tools and empower every team member to iterate independently. Natural language programming is here to stay. Wordware frees prompt from your codebase by providing both technical and non-technical users with a powerful IDE for AI agent creation. Experience the simplicity and flexibility of our interface. Empower your team to easily collaborate, manage prompts, and streamline workflows with an intuitive design. Loops, branching, structured generation, version control, and type safety help you get the most out of LLMs, while custom code execution allows you to connect to virtually any API. Easily switch between various large language model providers with one click. Optimize your workflows with the best cost-to-latency-to-quality ratios for your application.

Developer-centric tool to monitor and improve AI features powered by LLMs and other foundation models. Our simple SDK gives you an intuitive and actionable view of how your generative AI applications are performing in production. Integrate LLM management into your existing codebase and developer workflow. Use our fine-grained access controls and audit logs to maintain full control over your data. Derive actionable insights on how to improve LLM user interactions. Not only are these teams best-equipped to integrate these new capabilities into existing software products, but their proclivity to deploy, iterate, and improve will also be ever more pertinent going forward. As software becomes increasingly malleable, we believe engineering teams will be the driving force behind turning that malleability into delightful and hyper-personalized user experiences. Developers will be at the center of the generative AI revolution.

Release high-quality LLM apps quickly without compromising on testing. Never be held back by the complex and subjective nature of LLM interactions. Generative AI produces subjective results. Knowing whether a generated text is good usually requires manual labor by a subject matter expert. If you’re working on an LLM app, you probably know that you can’t release it without addressing countless constraints and edge-cases. Hallucinations, incorrect answers, bias, deviation from policy, harmful content, and more need to be detected, explored, and mitigated before and after your app is live. Deepchecks’ solution enables you to automate the evaluation process, getting “estimated annotations” that you only override when you have to. Used by 1000+ companies, and integrated into 300+ open source projects, the core behind our LLM product is widely tested and robust. Validate machine learning models and data with minimal effort, in both the research and the production phases.

Train and serve large AI models at scale with a single command. Point to your S3 bucket and go. We handle the rest, orchestration, efficiency, node failures, and infrastructure. Simple and scalable. MosaicML enables you to easily train and deploy large AI models on your data, in your secure environment. Stay on the cutting edge with our latest recipes, techniques, and foundation models. Developed and rigorously tested by our research team. With a few simple steps, deploy inside your private cloud. Your data and models never leave your firewalls. Start in one cloud, and continue on another, without skipping a beat. Own the model that's trained on your own data. Introspect and better explain the model decisions. Filter the content and data based on your business needs. Seamlessly integrate with your existing data pipelines, experiment trackers, and other tools. We are fully interoperable, cloud-agnostic, and enterprise proved.

TorqCloud is designed to help users source, move, enrich, visualize, secure, and interact with data via AI agents. As a comprehensive AIOps solution, TorqCloud allows users to build or integrate end-to-end custom LLM applications using a low-code interface. Built to handle vast amounts of data to deliver actionable insights as a critical tool for any organization looking to stay competitive in today’s digital landscape. Our approach combines seamless integration across disciplines, an intense focus on user needs, test-and-learn methodologies that enable us to get the right product to market fast, and a close working relationship with your teams, including skills transfer and training. Starting with empathy interviews we perform stakeholder mapping exercises where we dive into the customer journey, needed behavioral changes, problem sizing, and linear unpacking.

Emly Labs is an AI framework designed to make AI accessible for users at all technical levels through a user-friendly platform. It offers AI project management with tools for guided workflows and automation for faster execution. The platform encourages team collaboration and innovation, provides no-code data preparation, and integrates external data for robust AI models. Emly AutoML automates data processing and model evaluation, reducing human input. It prioritizes transparency, with explainable AI features and robust auditing for compliance. Security measures include data isolation, role-based access, and secure integrations. Additionally, Emly's cost-effective infrastructure allows on-demand resource provisioning and policy management, enhancing experimentation and innovation while reducing costs and risks.

Achieve peak model performance with the best data. Create & manage training data for any visual modality, debug models and boost performance, and make foundation models your own. Expert review, QA and QC workflows help you deliver higher quality datasets to your artificial intelligence teams, helping improve model performance. Connect your data and models with Encord's Python SDK and API access to create automated pipelines for continuously training ML models. Improve model accuracy by identifying errors and biases in your data, labels and models.

Build and deploy deep learning models for custom use cases. Our automated machine learning process allows customers to create powerful AI solutions built on our best-in-class models and tailored to the specific challenges they face. Digital platforms can quickly create models specifically made to fit their guidelines and needs. Build large language models for specialized use cases such as customer and technical support bots. Create image classification models to better understand image libraries for search, organization, and more.

The Intel Distribution of OpenVINO toolkit makes it simple to adopt and maintain your code. Open Model Zoo provides optimized, pretrained models and Model Optimizer API parameters make it easier to convert your model and prepare it for inferencing. The runtime (inference engine) allows you to tune for performance by compiling the optimized network and managing inference operations on specific devices. It also auto-optimizes through device discovery, load balancing, and inferencing parallelism across CPU, GPU, and more. Deploy your same application across combinations of host processors and accelerators (CPUs, GPUs, VPUs) and environments (on-premise, on-device, in the browser, or in the cloud).

Entry Point AI is the modern AI optimization platform for proprietary and open source language models. Manage prompts, fine-tunes, and evals all in one place. When you reach the limits of prompt engineering, it’s time to fine-tune a model, and we make it easy. Fine-tuning is showing a model how to behave, not telling. It works together with prompt engineering and retrieval-augmented generation (RAG) to leverage the full potential of AI models. Fine-tuning can help you to get better quality from your prompts. Think of it like an upgrade to few-shot learning that bakes the examples into the model itself. For simpler tasks, you can train a lighter model to perform at or above the level of a higher-quality model, greatly reducing latency and cost. Train your model not to respond in certain ways to users, for safety, to protect your brand, and to get the formatting right. Cover edge cases and steer model behavior by adding examples to your dataset.

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.

Build and optimize text and image AI for your needs, train, fine-tune, and generate from your data. We use best-in-class open source models for image and language generation and can train them in minutes thanks to LoRA fine-tuning. Click the share button to create a link to your session, or create a bot. Optionally deploy to your own fully private infrastructure. You can start chatting with open source language models and generating images with Stable Diffusion XL by creating a free account right now. Fine-tuning your model on your own text or image data is as simple as drag’n’drop, and takes 3-10 minutes. You can then chat with and generate images from those fine-tuned models straight away, all using a familiar chat interface.

Onboard your data and models to Openlayer and collaborate with the whole team to align expectations surrounding quality and performance. Breeze through the whys behind failed goals to solve them efficiently. The information to diagnose the root cause of issues is at your fingertips. Generate more data that looks like the subpopulation and retrain the model. Test new commits against your goals to ensure systematic progress without regressions. Compare versions side-by-side to make informed decisions and ship with confidence. Save engineering time by rapidly figuring out exactly what’s driving model performance. Find the most direct paths to improving your model. Know the exact data needed to boost model performance and focus on cultivating high-quality and representative datasets.

We’ve included some common examples, but the list is far from exhaustive. Our solution engineering team will work with you to customize Kolena for your workflows and your business metrics. Aggregate metrics don't tell the full story — unexpected model behavior in production is the norm. Current testing processes are manual, error-prone, and unrepeatable. Models are evaluated on arbitrary statistical metrics that align imperfectly with product objectives. ‍ Tracking model improvement over time as the data evolves is difficult and techniques sufficient in a research environment don't meet the demands of production.