Best AI Development Platforms for OpenAI

Build and manage AI agent teams using our Mixture of Experts (MoE) system. Create specialized digital workers with tailored knowledge, language models, triggers, and tools. Expand your workforce through computing power, not headcount. Simplify complex task automation without any coding needed.

InteraxAI, a No-Code White Label platform, offers monetizable or embeddable AI Widgets. Our wide selection of AI widgets can be easily integrated into any website, blog, or page. InteraxAI's AI widgets can improve your user experience and increase engagement. A chatbot can provide quick and accurate answers to users, while an image generator generates personalized images based upon user input. These widgets can be customized to meet your specific needs, making them easy to integrate into your digital platform. InteraxAI's AI widgets will allow you to create an engaging and interactive user experience that will keep your audience coming back.

Lyzr, a Generative AI enterprise company, offers private and secure AI Agents SDKs as well as an AI Management System. Lyzr helps businesses build, launch, and manage secure GenAI apps, whether they are on-prem or in the AWS cloud. No more sharing sensitive information with SaaS platforms, GenAI wrappers or GenAI platforms. Open-source tools are no longer prone to reliability and integration problems. Lyzr.ai is different from competitors like Cohere, Langchain and LlamaIndex. It follows a use case-focused approach. It builds full-service but highly customizable SDKs that simplify the addition of LLM functionality to enterprise applications. AI Agents Jazon - The AI SDR Skott is the AI digital marketer Kathy - the AI competitor analyst Diane - the AI HR manager Jeff - The AI Customer Success Manager Bryan - the AI inbound sales specialist Rachelz - the AI legal assistant

Klu.ai, a Generative AI Platform, simplifies the design, deployment, and optimization of AI applications. Klu integrates your Large Language Models and incorporates data from diverse sources to give your applications unique context. Klu accelerates the building of applications using language models such as Anthropic Claude (Azure OpenAI), GPT-4 (Google's GPT-4), and over 15 others. It allows rapid prompt/model experiments, data collection and user feedback and model fine tuning while cost-effectively optimising performance. Ship prompt generation, chat experiences and workflows in minutes. Klu offers SDKs for all capabilities and an API-first strategy to enable developer productivity. Klu automatically provides abstractions to common LLM/GenAI usage cases, such as: LLM connectors and vector storage, prompt templates, observability and evaluation/testing tools.

Build complex backend agents using multiple steps with an action-based orchestration. All LLMs are supported. Build a fully customized UI without writing a line of code for your agent, and serve it on your own domain. Track your agent's every move, literally, to cope with the nondeterministic nature LLMs. Access control can be built at a finer grain for your application, data and agent. A fine-tuned, specialized model to accelerate software development. Automatically handle concurrency and rate limiting.

Monitor your LLMs during production and discover and correct hallucinations and errors related to accuracy and quality with LLM outputs. Check your outputs to see if they contain hallucinations, misinformation or other issues. Configurable for any LLM application. Segment data to analyze in depth your cost, accuracy and response times. To debug generation, you can search, sort and filter your inference calls and trace your queries, retrievals and responses. Explore your conversations to learn what your users feel and what they are saying. You can also find out which conversations were unsuccessful. Compare your performance metrics between different models and prompts. Our insights will guide you to the best model for each use case. Our evaluators analyze and improve the outputs by using your data, configurations and feedback.

Langtail is a cloud-based development tool designed to streamline the debugging, testing, deployment, and monitoring of LLM-powered applications. The platform provides a no-code interface for debugging prompts, adjusting model parameters, and conducting thorough LLM tests to prevent unexpected behavior when prompts or models are updated. Langtail is tailored for LLM testing, including chatbot evaluations and ensuring reliable AI test prompts. Key features of Langtail allow teams to: • Perform in-depth testing of LLM models to identify and resolve issues before production deployment. • Easily deploy prompts as API endpoints for smooth integration into workflows. • Track model performance in real-time to maintain consistent results in production environments. • Implement advanced AI firewall functionality to control and protect AI interactions. Langtail is the go-to solution for teams aiming to maintain the quality, reliability, and security of their AI and LLM-based applications.

Test, launch and refine Gen AI prompting. RAG Agents. Datasets. Workflows. A single workspace for Engineers and Product Managers to explore LLM technology.

You can use advanced language models and coding to solve a variety of problems. To build cutting-edge applications, leverage large-scale, generative AI models that have deep understandings of code and language to allow for new reasoning and comprehension. These coding and language models can be applied to a variety use cases, including writing assistance, code generation, reasoning over data, and code generation. Access enterprise-grade Azure security and detect and mitigate harmful use. Access generative models that have been pretrained with trillions upon trillions of words. You can use them to create new scenarios, including code, reasoning, inferencing and comprehension. A simple REST API allows you to customize generative models with labeled information for your particular scenario. To improve the accuracy of your outputs, fine-tune the hyperparameters of your model. You can use the API's few-shot learning capability for more relevant results and to provide examples.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

Discuro is an all-in-one platform that allows developers to quickly build, test and consume complex AI workflows. Our UI makes it easy to define your workflow. When you are ready to execute, just make one API call to Discuro with any inputs and any meta-data. You can use an Orchestrator to feed the generated data back into GPT-3. Integrate with OpenAI to extract the data you need quickly. In minutes, create and consume your own flows. Everything you need to integrate OpenAI at scale has been built by us so that you can concentrate on the product. Integrating with OpenAI is not easy. We'll help you extract the data you need by collecting input/output descriptions. You can easily chain completions together to create large data sets. You can use our iterative input feature for GPT-3 output to feed back in and have us make successive calls to expand your data set. Easy to build and test complex, self-transforming AI workflows and datasets.

Metal is a fully-managed, production-ready ML retrieval platform. Metal embeddings can help you find meaning in unstructured data. Metal is a managed services that allows you build AI products without having to worry about managing infrastructure. Integrations with OpenAI and CLIP. Easy processing & chunking of your documents. Profit from our system in production. MetalRetriever is easily pluggable. Simple /search endpoint to run ANN queries. Get started for free. Metal API Keys are required to use our API and SDKs. Authenticate by populating headers with your API Key. Learn how to integrate Metal into your application using our Typescript SDK. You can use this library in JavaScript as well, even though we love TypeScript. Fine-tune spp programmatically. Indexed vector data of your embeddings. Resources that are specific to your ML use case.

The fastest & easiest way to integrate GPT in your apps & workflows. Make your SaaS and mobile apps stand out using GPT. Develop, test, monitor, and improve your prompts all in one place. Integrate with a single API call, regardless of the provider. Add powerful GPT features such as text generation, information extract, etc. to your SaaS application and attract new users. Promptitude allows you to be ready for production within a single day. It takes a lot of skill to create powerful, perfect GPT prompts. With Promptitude you can now develop, test and manage all of your prompts from one place. With a built-in rating system, you can easily improve your prompts. Make your hosted GPT & NLP APIs accessible to a large audience of SaaS and software developers. Promptitude's prompt management is a simple and easy way to increase API usage. You can mix and match different AI models and providers, saving money by choosing the smallest model.

AI agents that interact and answer questions with users and complete tasks using your data and APIs. AI that can answer questions, summarize and extract insights from any long document. Transfer styles and formats, as well as tags and summaries between documents and data sources. Stack AI is used by developer teams to automate customer service, process documents, qualify leads, and search libraries of data. With a single button, you can try multiple LLM architectures and prompts. Collect data, run fine-tuning tasks and build the optimal LLM to fit your product. We host your workflows in APIs, so that your users have access to AI instantly. Compare the fine-tuning services of different LLM providers.

Flowise is open source and will always be free to use for commercial and private purposes. Build LLMs apps easily with Flowise, an open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Open source MIT License, see your LLM applications running live, and manage component integrations. GitHub Q&A using conversational retrieval QA chains. Language translation using LLM chains with a chat model and chat prompt template. Conversational agent for chat model that uses chat-specific prompts.

Create AI apps that can be shared using a simple editor similar to Notion. No need to hire expensive developers or write code. We take care of the hosting, database and deployment. Typeblock empowers you to create AI tools in less than 2 minutes, whether you're a marketing team, an agency, or an entrepreneur. Create SEO-optimized blogs and publish them instantly to your CMS. Create a tool that will generate highly personalized cold email for your sales team. Create a tool that will help you write Facebook ads, LinkedIn posts or Twitter threads. Create an app to write landing page copy for the marketing team. Build tools that create highly engaging newsletters using AI.

LMOps is a stack that allows you to launch production-ready applications for monitoring, model management and more. Portkey is a replacement for OpenAI or any other provider APIs. Portkey allows you to manage engines, parameters and versions. Switch, upgrade, and test models with confidence. View aggregate metrics for your app and users to optimize usage and API costs Protect your user data from malicious attacks and accidental exposure. Receive proactive alerts if things go wrong. Test your models in real-world conditions and deploy the best performers. We have been building apps on top of LLM's APIs for over 2 1/2 years. While building a PoC only took a weekend, bringing it to production and managing it was a hassle! We built Portkey to help you successfully deploy large language models APIs into your applications. We're happy to help you, regardless of whether or not you try Portkey!

Create generative AI apps for engineers and not just ML practitioners. Focus on creating instead of configuring. No more switching platforms or wrestling with APIs. Use a familiar interface for AI and to prompt engineers. Workbooks can be easily streamlined into templates by using parameters. Create workflows using model outputs from LLMs and image and audio models. Create groups to manage workbooks between your teammates. Share your workbook with your team or the public, or to specific organizations that you define. Workbooks can be commented on and compared with your team. Create templates for you, your team or the developer community. Get started quickly by using templates to see what others are building.

PostgresML is an entire platform that comes as a PostgreSQL Extension. Build simpler, faster and more scalable model right inside your database. Explore the SDK, and test open-source models in our hosted databases. Automate the entire workflow, from embedding creation to indexing and Querying for the easiest (and fastest) knowledge based chatbot implementation. Use multiple types of machine learning and natural language processing models, such as vector search or personalization with embeddings, to improve search results. Time series forecasting can help you gain key business insights. SQL and dozens regression algorithms allow you to build statistical and predictive models. ML at database layer can detect fraud and return results faster. PostgresML abstracts data management overheads from the ML/AI cycle by allowing users to run ML/LLM on a Postgres Database.

Experience JinaChat - a LLM service designed for professionals. JinaChat is a multimodal chat service that goes beyond text and includes images. Enjoy our free short interactions below 100 tokens. Our API allows developers to build complex applications by leveraging long conversation histories. JinaChat is the future of LLM, with multimodal conversations that are long-memory and affordable. Modern LLM applications are often based on long prompts or large memory, which can lead to high costs if the same prompts are sent repeatedly to the server. JinaChat API solves this issue by allowing you to carry forward previous conversations, without having to resend the entire prompt. This is a great way to save both time and money when developing complex applications such as AutoGPT.

Choose the appropriate app type. Choose the output and input required for the app. Add data from existing sources such as files, URLs, sitemaps and YouTube links. You can also add data from Notion exports, Google Drive and other sources. Attach these data sources in the app builder. Save and publish your application. You can embed the code in your website or access it directly from the dedicated app page. Our APIs allow you to run the app directly from your application. Promptly offers embeddable widgets you can easily integrate in your website. These widgets can be used to create conversational AI applications, or to add a bot to your website. Customize the look and feel of the chatbot to match your website. Include a logo.

Lilac is a free open-source tool that allows data and AI practitioners improve their products through better data. Understanding your data is easy with powerful filtering and search. Work together with your team to create a single dataset. Use best practices for data curation to reduce the size of your dataset and training costs and time. Our diff viewer allows you to see how your pipeline affects your data. Clustering is an automatic technique that assigns categories to documents by analyzing their text content. Similar documents are then placed in the same category. This reveals your dataset's overall structure. Lilac uses LLMs and state-of-the art algorithms to cluster the data and assign descriptive, informative titles. We can use keyword search before we do advanced searches, such as concept or semantic searching.

OpenPipe provides fine-tuning for developers. Keep all your models, datasets, and evaluations in one place. New models can be trained with a click of a mouse. Automatically record LLM responses and requests. Create datasets using your captured data. Train multiple base models using the same dataset. We can scale your model to millions of requests on our managed endpoints. Write evaluations and compare outputs of models side by side. You only need to change a few lines of code. OpenPipe API Key can be added to your Python or Javascript OpenAI SDK. Custom tags make your data searchable. Small, specialized models are much cheaper to run than large, multipurpose LLMs. Replace prompts in minutes instead of weeks. Mistral and Llama 2 models that are fine-tuned consistently outperform GPT-4-1106 Turbo, at a fraction the cost. Many of the base models that we use are open-source. You can download your own weights at any time when you fine-tune Mistral or Llama 2.

Query and compare multiple proprietary and open-source models simultaneously. Replace expensive APIs with custom AI models. Customize foundational AI models using your private data and adapt them to fit your specific use case. Small, fine-tuned models perform at the same level as GPT-4 while being up to 90% less expensive. Airtrain's LLM-assisted scoring simplifies model grading using your task descriptions. Airtrain's API allows you to serve your custom models in the cloud, or on your own secure infrastructure. Evaluate and compare proprietary and open-source models across your entire dataset using custom properties. Airtrain's powerful AI evaluation tools let you score models based on arbitrary properties to create a fully customized assessment. Find out which model produces outputs that are compliant with the JSON Schema required by your agents or applications. Your dataset is scored by models using metrics such as length and compression.

PlugBear provides a low-code/no-code solution to connect communication channels with LLM applications (Large Language Model). It allows, for example, the creation of a Slack Bot from an LLM application in just a few simple clicks. PlugBear is notified when a trigger event occurs on the integrated channels. It then transforms messages into LLM applications, and initiates generation. PlugBear then transforms the generated results so that they are compatible with each channel. This allows users to interact with LLM applications seamlessly across different channels.