Portkey Alternatives

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

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.

Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real time with surgical precision. Software engineering relies on unit testing to build performant, production-ready applications. LangSmith provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith. LangSmith enables mission-critical observability with only a few lines of code. LangSmith is designed to help developers harness the power–and wrangle the complexity–of LLMs. We’re not only building tools. We’re establishing best practices you can rely on. Build and deploy LLM applications with confidence. Application-level usage stats. Feedback collection. Filter traces, cost and performance measurement. Dataset curation, compare chain performance, AI-assisted evaluation, and embrace best practices.

Bring LLM-powered features to production with tools for prompt engineering, semantic search, version control, quantitative testing, and performance monitoring. Compatible across all major LLM providers. Quickly develop an MVP by experimenting with different prompts, parameters, and even LLM providers to quickly arrive at the best configuration for your use case. Vellum acts as a low-latency, highly reliable proxy to LLM providers, allowing you to make version-controlled changes to your prompts – no code changes needed. Vellum collects model inputs, outputs, and user feedback. This data is used to build up valuable testing datasets that can be used to validate future changes before they go live. Dynamically include company-specific context in your prompts without managing your own semantic search infra.

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.

We offer a unified set of world class tools and assets for seamless conversion of ideas into production-ready AI solutions. Build and deploy end-to-end custom Generative AI solutions on our unified platform, skipping the hassle of tool fragmentation and platform-switching. Launch your next AI solution through a single API endpoint. Creating, maintaining, and improving AI systems has never been this easy. Discover is aiXplain’s marketplace for models and datasets from various suppliers. Subscribe to models and datasets to use them with aiXplain no-code/low-code tools or through the SDK in your own code.

OpenPipe provides fine-tuning for developers. Keep your datasets, models, and evaluations all in one place. Train new models with the click of a button. Automatically record LLM requests and responses. Create datasets from your captured data. Train multiple base models on the same dataset. We serve your model on our managed endpoints that scale to millions of requests. Write evaluations and compare model outputs side by side. Change a couple of lines of code, and you're good to go. Simply replace your Python or Javascript OpenAI SDK and add an OpenPipe API key. Make your data searchable with custom tags. Small specialized models cost much less to run than large multipurpose LLMs. Replace prompts with models in minutes, not weeks. Fine-tuned Mistral and Llama 2 models consistently outperform GPT-4-1106-Turbo, at a fraction of the cost. We're open-source, and so are many of the base models we use. Own your own weights when you fine-tune Mistral and Llama 2, and download them at any time.

Describe example API requests and responses. Define API endpoint logic in natural language. Test your API endpoints and fine-tune your prompt, response structure, and request structure. Deploy API endpoints with a single click and integrate into your applications. Build and deploy sophisticated application logic without writing any code in less than a minute. No individual LLM accounts required. Just sign up to Backengine and start building. Your endpoints run on our super fast backend architecture, available immediately. All endpoints are secure and protected so only you and your applications can use them. Easily manage your team members so everyone can work on your Backengine endpoints. Augment your Backengine endpoints with persistent data. A complete backend replacement. Use external APIs into your endpoints without doing any integration work yourself.

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.

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.

Ship AI faster with managed, cloud-hosted AI packages. Full, built-in support for GPT-4. No API tokens are necessary. Build with our low code framework. Integrations with all major models are built-in. Deploy for an instant API. Scale and share without managing infrastructure. Turn prompts, prompt chains, and basic Python into a managed API. Turn a clever prompt into a published API you can share. Add logic and routing smarts with Python. Steamship connects to your favorite models and services so that you don't have to learn a new API for every provider. Steamship persists in model output in a standardized format. Consolidate training, inference, vector search, and endpoint hosting. Import, transcribe, or generate text. Run all the models you want on it. Query across the results with ShipQL. Packages are full-stack, cloud-hosted AI apps. Each instance you create provides an API and private data workspace.

Now available—a next generation enterprise studio for AI builders to train, validate, tune and deploy AI models IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform, bringing together new generative AI (gen AI) capabilities powered by foundation models and traditional machine learning (ML) into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai offers: End-to-end AI governance: Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides. Hybrid, multi-cloud deployments: IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice.

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.

Embed and store documents, images, and more. High-performance retrieval workflows with no additional work. Connect your data via the UI or API. Baseplate handles embedding, storage, and version control so your data is always in-sync and up-to-date. Hybrid Search with custom embeddings tuned for your data. Get accurate results regardless of the type, size, or domain of the data you're searching through. Prompt any LLM with data from your database. Connect search results to a prompt through the App Builder. Deploy your app with a few clicks. Collect logs, human feedback, and more using Baseplate Endpoints. Baseplate Databases allow you to embed and store your data in the same table as the images, links, and text that make your LLM App great. Edit your vectors through the UI, or programmatically. We version your data so you never have to worry about stale data or duplicates.

The prompt engineering platform to experiment with different prompt versions, evaluate and compare prompts across a suite of tests, optimize prompts with one-click, share, and more. Optimize your AI development workflow. Key features to help you get and identify the best prompts for your production use cases. Side-by-side comparison of prompts across test cases with evaluation. CSV import test cases, and define custom evaluation metrics. Improve LLM results with automatic prompt and template optimization. View and manage all prompt versions and create OpenAI functions. Access all of your prompts programmatically, including observability and analytics. Determine the costs, latency, and efficacy of each prompt. Start enhancing your prompt engineering workflow with Parea today. Parea makes it easy for developers to improve the performance of their LLM apps through rigorous testing and version control.

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.

Compose, test, optimize, and deploy reliable prompts for the leading language models and AI platforms to supercharge your apps and workflows. PROMPTMETHEUS is an Integrated Development Environment (IDE) for LLM prompts, designed to help you automate workflows and augment products and services with the mighty capabilities of GPT and other cutting-edge AI models. With the advent of the transformer architecture, cutting-edge Language Models have reached parity with human capability in certain narrow cognitive tasks. But, to viably leverage their power, we have to ask the right questions. PROMPTMETHEUS provides a complete prompt engineering toolkit and adds composeability, traceability, and analytics to the prompt design process to assist you in discovering those questions.

Build better AI with multiple models. AI models are a new kind of building block. Sieve is the easiest way to use these building blocks to understand audio, generate video, and much more at scale. State-of-the-art models in just a few lines of code, and a curated set of production-ready apps for many use cases. Import your favorite models like Python packages. Visualize results with auto-generated interfaces built for your entire team. Deploy custom code with ease. Define your environment compute in code, and deploy with a single command. Fast, scalable infrastructure without the hassle. We built Sieve to automatically scale as your traffic increases with zero extra configuration. Package models with a simple Python decorator and deploy them instantly. A full-featured observability stack so you have full visibility of what’s happening under the hood. Pay only for what you use, by the second. Gain full control over your costs.

Deploy all major ML frameworks such as Pytorch, Onnx, XGBoost etc with 1 line of code. Don't have your own models? Deploy our prebuilt models that have been optimised to run with sub-second latency. Fine-tune smaller models on particular tasks in order to decrease costs and latency while increasing performance. It takes just a few lines of code and don't worry about infrastructure, we got it. Integrate with top ML observability platforms in order to be alerted about feature or prediction drift, compare model versions and resolve issues quickly. Discover the root causes for prediction and feature drift to resolve degraded model performance. Understand which features are contributing most to the performance of your model.

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.

Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, and HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Deploy all your AI models to automatically compute outputs (inference) in your datastore in a single environment with simple Python commands.

Metal is your production-ready, fully-managed, ML retrieval platform. Use Metal to find meaning in your unstructured data with embeddings. Metal is a managed service that allows you to build AI products without the hassle of managing infrastructure. Integrations with OpenAI, CLIP, and more. Easily process & chunk your documents. Take advantage of our system in production. Easily plug into the MetalRetriever. Simple /search endpoint for running ANN queries. Get started with a free account. Metal API Keys to use our API & SDKs. With your API Key, you can use authenticate by populating the headers. Learn how to use our Typescript SDK to implement Metal into your application. Although we love TypeScript, you can of course utilize this library in JavaScript. Mechanism to fine-tune your spp programmatically. Indexed vector database of your embeddings. Resources that represent your specific ML use-case.

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).

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.

Declarative machine learning systems provide the best of flexibility and simplicity to enable the fastest-way to operationalize state-of-the-art models. Users focus on specifying the “what”, and the system figures out the “how”. Start with smart defaults, but iterate on parameters as much as you’d like down to the level of code. Our team pioneered declarative machine learning systems in industry, with Ludwig at Uber and Overton at Apple. Choose from our menu of prebuilt data connectors that support your databases, data warehouses, lakehouses, and object storage. Train state-of-the-art deep learning models without the pain of managing infrastructure. Automated Machine Learning that strikes the balance of flexibility and control, all in a declarative fashion. With a declarative approach, finally train and deploy models as quickly as you want.

Native support for ChatGPT and LangChain. Bing, HuggingFace and more coming soon. Add your API documentation manually or import an existing OpenAPI specification. Access the request prompt, parameters, headers, body and more. Inspect detailed live metrics about how your plugin is performing, including latencies, errors, and more. Configure your own dashboards, track funnels and aggregated metrics.

Enterprise-ready AI system that trains locally on your data, deploys on your cloud and scales to millions of users without an engineering team. Build customize and deploy your own chat-based AI. Finance chatbot. xFinance, a 13-billion parameter model fine-tuned on an open-source model using LoRA. Our goal was to show that it is possible to achieve impressive results in financial NLP tasks without breaking the bank. Personal AI assistant, your own AI to chat with your documents. Single or multiple documents, easy or complex questions, and much more. Effortless deep learning platform for enterprises, hardware efficient algorithms to speed up inference at a lower cost. Real-time logging and monitoring of resource utilization and cloud costs of deployed models. xTuring is an open-source AI personalization software. xTuring makes it easy to build and control LLMs by providing a simple interface to personalize LLMs to your own data and application.

Prototype and productionize generative AI apps, built for engineers, not just ML practitioners. No more switching between platforms or wrestling with different APIs, focus on creating, not configuring. Use a familiar interface to prompt engineer and work with AI. Use parameters to easily streamline your workbooks into reusable templates. Create workflows by chaining model outputs from LLMs, image, and audio models. Create organizations to manage workbooks amongst your teammates. Share your workbook to the public or specific organizations you define with your team. Comment on workbooks and easily review and compare workbooks with your team. Develop templates for yourself, your team, or the broader developer community, get started quickly with templates to see what people are building.

See how Savvi can quickly and easily solve your business challenges. Increase operational efficiency, and empower your team to succeed. Start with the decision, recommendation or prediction that you want to automate with AI. Easily integrate existing data or run a data cold start with a simple line of code in your app. Savvi handles your AI App end-to-end, define your prediction or decision options, identify business goals and publish. Savvi collects the data, trains the ML model, builds your objective function, deploys the AI App into your product. Savvi will continuously learn to improve to your goals. Savvi can securely collect data from your product and train an ML model in less than a few weeks. Just drop in a snippet of Savvi’s code and go. No need for a data architecture project to get started with AI.

Fine-tuning happens when you take a dataset and build out a model to use with AI. It isn't always easy to do this without code so we built a solution into RIku which handles everything in a very simple format. Fine-tuning unlocks a whole new level of power for AI and we're excited to help you explore it. Public Share Links are individual landing pages that you can create for any of your prompts. You can design these with your brand in mind in terms of colors and adding a logo and your own welcome text. Share these links with anyone publicly and if they have the password to unlock it, they will be able to make generations. A no-code writing assistant builder on a micro scale for your audience! One of the big headaches we found with projects using multiple large language models is that they all return their outputs slightly differently.

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.

Build, evaluate, deploy, and refine custom natural language processing models. Empower your team to automate workflows without hiring an AI expert team and costly infra. Metatext simplifies the process of creating customized AI/NLP models, even without expertise in ML, data science, or MLOps. With just a few steps, automate complex workflows, and rely on intuitive UI and APIs to handle the heavy work. Enable AI into your team using a simple but intuitive UI, add your domain expertise, and let our APIs do all the heavy work. Get your custom AI trained and deployed automatically. Get the best from a set of deep learning algorithms. Test it using a Playground. Integrate our APIs with your existing systems, Google Spreadsheets, and other tools. Select the AI engine that best suits your use case. Each one offers a set of tools to assist creating datasets and fine-tuning models. Upload text data in various file formats and annotate labels using our built-in AI-assisted data labeling tool.

alwaysAI provides developers with a simple and flexible way to build, train, and deploy computer vision applications to a wide variety of IoT devices. Select from a catalog of deep learning models or upload your own. Use our flexible and customizable APIs to quickly enable core computer vision services. Quickly prototype, test and iterate with a variety of camera-enabled ARM-32, ARM-64 and x86 devices. Identify objects in an image by name or classification. Identify and count objects appearing in a real-time video feed. Follow the same object across a series of frames. Find faces or full bodies in a scene to count or track. Locate and define borders around separate objects. Separate key objects in an image from background visuals. Determine human body poses, fall detection, emotions. Use our model training toolkit to train an object detection model to identify virtually any object. Create a model tailored to your specific use-case.

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.

We're building autonomous systems that write and deploy custom software to perform complex tasks, from just English instruction. Maya translates steps written in English into visual programs that you can edit & extend without writing code. Describe the business logic for your application in English to generate a visual program. Dependencies auto-detected, installed, and deployed in seconds. Use our drag-and-drop editor to extend functionality to 100s of nodes. Build useful tools quickly, to automate all your work. Stitch multiple data sources by just describing how they work together. Pipe data into tables, charts, and graphs generated from natural language descriptions. Build, edit, and deploy dynamic forms to help a human enter & modify data. Copy and paste your natural language program into a note-taking app, or share it with a friend. Write, modify, debug, deploy & use apps programmed in English. Describe the steps you want Maya to generate code for.

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.

Make AI a trusted part of your business. Build better, deploy faster, and audit easily with the flexibility of a cloud-native platform and the power to deploy anywhere. Easily import models and search cataloged models from across your organization. Save time by annotating data rapidly with model-in-the-loop hinting. Understand the full provenance of your data, models, workflows, and inferences. Deploy models where you need them, including for edge and IoT use cases. Getting valuable insights from your data is not just for data scientists. With Chariot’s low-code interface, meaningful collaboration can take place across teams. Train models rapidly using your organization's production data. Deploy models with one click and monitor models in production at scale.

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.

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.

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.

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.

Scale your machine learning development from research to production with an end-to-end solution that gives your data science team all the tools they need in one place. As the leading data science platform for MLOps and model management, cnvrg.io is a pioneer in building cutting-edge machine learning development solutions so you can build high-impact machine learning models in half the time. Bridge science and engineering teams in a clear and collaborative machine learning management environment. Communicate and reproduce results with interactive workspaces, dashboards, dataset organization, experiment tracking and visualization, a model repository and more. Focus less on technical complexity and more on building high impact ML models. Cnvrg.io container-based infrastructure helps simplify engineering heavy tasks like tracking, monitoring, configuration, compute resource management, serving infrastructure, feature extraction, and model deployment.

Powerful language models a click away. Join over 8,000 developers building the next wave of world-changing applications. Fine-tune and deploy GPT-J, GPT-NeoX, Codegen, and FLAN-T5. Multiple models, each with different capabilities and price points. GPT-J is the fastest model, while GPT-NeoX is the most powerful—and more are on the way. Use these models for classification, entity extraction, code generation, chatbots, content generation, summarization, paraphrasing, sentiment analysis, and much more. These models have been pre-trained on a vast amount of text from the open internet. Fine-tuning improves upon this for specific tasks by training on many more examples than can fit in a prompt, letting you achieve better results on a wide number of tasks.

Fireworks partners with the world's leading generative AI researchers to serve the best models, at the fastest speeds. Independently benchmarked to have the top speed of all inference providers. Use powerful models curated by Fireworks or our in-house trained multi-modal and function-calling models. Fireworks is the 2nd most used open-source model provider and also generates over 1M images/day. Our OpenAI-compatible API makes it easy to start building with Fireworks. Get dedicated deployments for your models to ensure uptime and speed. Fireworks is proudly compliant with HIPAA and SOC2 and offers secure VPC and VPN connectivity. Meet your needs with data privacy - own your data and your models. Serverless models are hosted by Fireworks, there's no need to configure hardware or deploy models. Fireworks.ai is a lightning-fast inference platform that helps you serve generative AI models.

GradientJ provides everything you need to build large language model applications in minutes and manage them forever. Discover and maintain the best prompts by saving versions and comparing them across benchmark examples. Orchestrate and manage complex applications by chaining prompts and knowledge bases into complex APIs. Enhance the accuracy of your models by integrating them with your proprietary data.

Discuro is the all-in-one platform for developers looking to easily build, test & consume complex AI workflows. Define your workflow in our easy-to-use UI, and when you're ready to execute, simply make one API call to us, with your inputs, any meta-data, and we'll do the rest. Use an Orchestrator to feed generated data back into GPT-3. Reliably integrate with OpenAI and extract the data you need with ease. Create & consume your own flows in minutes. We've built everything you need to integrate with OpenAI, at scale, so you can focus on the product. The first challenge in integrating with OpenAI is extracting the data you need, we'll handle this for you by collecting input/output definitions. Easily chain completions together to build large data sets. Use our iterative input feature to feed GPT-3 output back in, and have us make consecutive calls to expand your data set, and much more. Easily build & test complex self-transforming AI workflows & datasets.

Utilize the efficiency of OpenAI’s GPT engine to build supervised large language models which are backed by your very own data. Enterprises looking to integrate AI into their current business can use Supervised to build scalable AI apps. Building your own LLM can be tough. That’s why we let you build and sell your own AI apps with Supervised. Supervised AI provides you an environment to build custom LLM & AI Apps that are powerful and scalable. Using our custom models and data sources, you can build high-accuracy AI at a fast pace. Businesses are utilizing AI in a very layman's way right now, where most of its potential is yet to unlock. At Supervised, we let you harness your data to build a completely new AI model from scratch. Build custom AI apps on data sources and models built by other developers.

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.

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.

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.