Best AI Development Platforms for Amazon S3

Retool is a platform that enables developers to combine the benefits of traditional software development with a drag-and-drop editor and AI to build internal tools faster. Every tool can be deployed anywhere, debugged with your toolchain, and shared reliably at any scale—ensuring good software by default. Retool is used by industry leaders such as Amazon, American Express, and OpenAI for mission critical custom software across operations, billing, and customer support.

Connecting every data source with analytics services on a single AI-powered platform will transform how people access, manage, and act on data and insights. All your data. All your teams. All your teams in one place. Create an open, lake-centric hub to help data engineers connect data from various sources and curate it. This will eliminate sprawl and create custom views for all. Accelerate analysis through the development of AI models without moving data. This reduces the time needed by data scientists to deliver value. Microsoft Teams, Microsoft Excel, and Microsoft Teams are all great tools to help your team innovate faster. Connect people and data responsibly with an open, scalable solution. This solution gives data stewards more control, thanks to its built-in security, compliance, and governance.

RZT aiOS provides all the benefits of a unified AI platform, and more. It's not just a platform, it's an Operating System that connects, manages, and unifies all your AI initiatives. AI developers can now do what used to take months in days thanks to aiOS process management which dramatically increases their productivity. This Operating System provides an intuitive environment for AI development. It allows you to visually build models, explore data and create processing pipelines. You can also run experiments and view analytics. It's easy to do all of this without any advanced software engineering skills.

Graphlit simplifies the process of building an AI copilot or chatbot or adding LLMs to your existing application. Graphlit is a serverless platform that automates complex data processes, including data ingestion and extraction, LLM conversations. It also integrates webhooks, alerting, semantic search, and alerting. Graphlit's workflow as code approach allows you to programmatically define every step in the workflow. Data ingestion, metadata indexing, data preparation and data enrichment. Integration with your applications is achieved through event-based webhooks, API integrations, and integrations with event-based Webhooks.

Diaflow is a platform that allows you to scale AI across your entire organization. It enables everyone to deploy AI workflows which drive innovation. Create powerful apps and workflows using any data source to automate manual processes or create fully automated ones. Automate manual business processes in a way that your team will enjoy. Diaflow's intuitive components and interfaces allow you to create powerful AI-driven apps for your business that you can be proud of. Diaflow AI-powered editor offers a new way to create and edit documents. Your expertise can be leveraged to provide 24/7 support. With a built-in AI spreadsheet solution, you can easily manage and transform your data. Diaflow makes it easy to create amazing products for your business. Diaflow allows you to create apps and workflows without coding in just minutes.

Build, test and optimize Generative AI apps that unlock the value in your data. Our industry-leading ML expertise, our state-of-the art test and evaluation platform and advanced retrieval augmented-generation (RAG) pipelines will help you optimize LLM performance to meet your domain-specific needs. We provide an end-toend solution that manages the entire ML Lifecycle. We combine cutting-edge technology with operational excellence to help teams develop high-quality datasets, because better data leads better AI.

An end-to-end solution gives you all the tools your data science team needs to scale your machine learning development, from research to production. cnvrg.io, the world's leading data science platform for MLOps (model management) is a leader in creating cutting-edge machine-learning development solutions that allow you to build high-impact models in half the time. In a collaborative and clear machine learning management environment, bridge science and engineering teams. Use interactive workspaces, dashboards and model repositories to communicate and reproduce results. You should be less concerned about technical complexity and more focused on creating high-impact ML models. The Cnvrg.io container based infrastructure simplifies engineering heavy tasks such as tracking, monitoring and configuration, compute resource management, server infrastructure, feature extraction, model deployment, and serving infrastructure.

Distributed training is possible without changing the model code. Determined takes care of provisioning, networking, data load, and fault tolerance. Our open-source deep-learning platform allows you to train your models in minutes and hours, not days or weeks. You can avoid tedious tasks such as manual hyperparameter tweaking, re-running failed jobs, or worrying about hardware resources. Our distributed training implementation is more efficient than the industry standard. It requires no code changes and is fully integrated into our state-ofthe-art platform. With its built-in experiment tracker and visualization, Determined records metrics and makes your ML project reproducible. It also allows your team to work together more easily. Instead of worrying about infrastructure and errors, your researchers can focus on their domain and build upon the progress made by their team.

Granica AI efficiency platform lowers costs for storing and accessing data, while maintaining its privacy so that it can be used to train. Granica is native to AWS/GCP, a petabyte-scale platform, and developer-first. Granica makes AI pipelines faster, more efficient, and more performant. Efficiency is a layer of the AI stack. Byte-granular reduction of data uses novel compression algorithms to reduce costs for storing and transferring objects in Amazon S3 or Google Cloud Storage up to 80%, and API costs up to 90%. Estimate your cloud environment in 30 minutes, using a sample of read-only data from your S3/GCS. No need to allocate budgets or perform a total cost of ownership. Granica deploys to your environment and VPC while respecting your security policies. Granica supports many data types for AI/ML/analytics. It also offers lossy and lossless compression options. Detect and protect sensitive information even before it's persisted in your cloud object store.

No one wants to have their AI respond to a client with outdated information. Neum AI provides accurate and current context for AI applications. Set up your data pipelines quickly by using built-in connectors. These include data sources such as Amazon S3 and Azure Blob Storage and vector stores such as Pinecone and Weaviate. Transform and embed your data using built-in connectors to embed models like OpenAI, Replicate and serverless functions such as Azure Functions and AWS Lambda. Use role-based controls to ensure that only the right people have access to specific vectors. Bring your own embedding model, vector stores, and sources. Ask us how you can run Neum AI on your own cloud.

Simulations based on historical data can be used to improve models and update them incrementally. Data governance, access control, and versioning allow for easy collaboration. Ikigai has a wide range of integrations that make it easy to integrate with tools already in your workflow. Ikigai has 200+ connectors that allow you to connect to almost any data source. Want to push your ML to a dashboard or website? Integrate directly using Ikigai’s web integrations. Triggers can be used to run data synchronizations, and retrieve updates every time you run an automation flow. You can integrate Ikigai seamlessly by using your own APIs or creating APIs for your data stack.

Create automations and manage exceptions in intuitive English. Automate in a simple and intuitive way processes that have large volumes of transactions, unstructured and structured data, and workflows with complex exceptions. RPA has historically had difficulty automating processes that encounter exceptions. Document-heavy workflows are a good example. Kognitos uses a fundamentally new approach, allowing users to teach automation how to handle exceptions by using natural language. Kognitos mimics how we teach each other to resolve errors and edge-cases by using intuitive prompting, which puts humans in charge. Automation can be trained just like you would train a human to work through experience and examples.

Savvi is a powerful tool that can help you solve business challenges quickly and easily. Increase operational efficiency and empower your team for success. Start with the decision, prediction or recommendation that you would like to automate using AI. With a single line of code, you can easily integrate existing data into your app or run a cold start on data. Savvi manages your AI App from start to finish. Define your prediction or decision options. Identify business goals. Savvi collects data, trains ML models, builds your objective functions, and deploys your AI App. Savvi will learn continuously to improve according to your goals. Savvi will securely collect data and train a ML model from your product in less than few weeks. Savvi code can be dropped in and you're ready to go. You don't need to start with a data architecture project in order to use AI.

You can embed and store images, documents, and other information. No additional work required for high-performance retrieval workflows. Connect your data via the UI and API. Baseplate handles storage, embedding, and version control to ensure that your data is always up-to-date and in-sync. Hybrid Search with customized embeddings that are tailored to your data. No matter what type, size or domain of data you are searching for, you will get accurate results. Any LLM can be generated using data from your database. Connect search results to an App Builder prompt. It takes just a few clicks to deploy your app. Baseplate Endpoints allow you to collect logs, human feedback, etc. Baseplate Databases enable you to embed and store data in the same table with images, links, text, and other elements that make your LLM app great. You can edit your vectors via the UI or programmatically. We can version your data so that you don't have to worry about duplicates or stale data.

Discover. Analyze. Optimize. Use [impaction.ai]’s intuitive semantic search to easily sift conversational data. Type 'find me conversation where ...', and let our engine handle the rest. Meet Columbus, your intelligent data co-pilot. Columbus analyzes conversations and highlights key trends. It can even recommend which dialogues you should pay attention to. Take data-driven action to improve user engagement and create a smarter and more responsive AI product. Columbus is not only a great source of information, but also offers suggestions on how to improve the situation.