Build NLP features into your product

Implement semantic search, question answering or document similarity quickly and reliably with deepset Cloud.

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Why use deepset Cloud?

  • Start building in minutes

    All core NLP components in one platform. Pick a model, add documents, pre-process, index, and build a demo UI. Compose and deploy custom NLP pipelines.

  • Experiment faster

    Quickly iterate, evaluate, and compare models with your own metrics and evaluation datasets. Collect end user requirements and launch a demo within days, not months.

  • Launch product

    Deploy as many NLP pipelines as you want on our cloud. Focus on your product and not on running the infrastructure. Quickly integrate NLP in your app with APIs.

  • Collect user feedback early

    Once your NLP service is in production, use deepset Cloud for service monitoring and collecting user feedback. Improve model performance with our MLOps-focused tools.

Build NLP applications fast

From data to API-driven NLP backend services in days

  • No model lock-in — use any model at any time

    Pick any model from Hugging Face's Model Hub. Quickly deploy it for evaluation. Swap for a new one when needed.

  • Feature-rich model evaluation

    We are experts in model evaluation and fine-tuning. Behind the deepset Cloud workflows are our knowledge and years of experience. We will guide you, so you can be an expert too.

  • Custom NLP pipelines

    We believe one size doesn't fit all. You should have the flexibility to build solution-centric NLP pipelines for a variety of NLP tasks. It's easy to architect bespoke Haystack pipelines with deepset Cloud.

  • Scalable zero-downtime deployments

    Transformer models are no easy fit to deploy at scale. We've already architected the most scalable infrastructure for you to deploy your NLP backend services.

  • Involve everyone

    Modern NLP-enabled product lifecycle requires participation from various teams. We've been through a lot of projects like that, so we took care of the key stakeholders' needs in deepset Cloud — from developers to product owners to business end users.

  • Practical, robust, trusted

    deepset Cloud is the result of years of work helping enterprise clients to implement production-ready NLP services. The technology behind it is our renowned open source NLP framework — Haystack.

Our users' voice

  • “We chose to add document similarity to our flagship product, because it's all about speed and efficiency — if lawyers need less time to research their cases, they have more time to acquire new clients. With deepset Cloud the advantage of using a pipeline with a fine-tuned language model was very clear to us.”Manz

  • “Haystack NLP allowed us to easily build domain-specific question answering pipelines for many different contexts.”Etalab

We'd love to keep you posted!

Frequently asked questions

  • Natural language processing (NLP) is a branch of AI that enables machines to process and interpret human language. In general, by implementing NLP, companies can leverage human language to interact with computers and data. Areas of NLP include semantic search, question answering (QA), conversational AI (chatbots), text summarization, document similarity, question generation, text generation, machine translation, text mining, speech recognition — to name a few use cases.

  • Modern enterprises have been rapidly integrating NLP into their internal products, processes and workflows. It is not only Amazon AWS or Microsoft who implemented NLP, but also enterprises such as Airbus, Infineon, Alcatel-Lucent, government agencies across the globe, as well as startup tech companies who are utilizing NLP to create amazing new products and services. NLP can be used in the financial industry, legal field, science, manufacturing, and many other verticals. Practical applications of NLP usually involve implementing semantic search and question answering to automate data analysis, decision-making process, fraud monitoring, claim management, regulatory actions, to reduce costs and improve customer satisfaction.

  • At deepset we believe in open NLP. This includes open language models, open source tools to build neural search and question answering, open communication and discussion, sharing experiences, as well as educating the developers and the users of NLP-enabled solutions. We believe that only through transparency and openness it is possible to apply natural language processing to various problems that enterprises and governments are facing.

  • The ever increasing volume of unstructured data in the enterprise, e.g., corporate documents, financial reports, research papers, legal contracts presents a difficult problem to solve for the enterprise product teams. This kind of data is usually hard for the enterprise software to process. NLP allows the developers to apply latest research to industry relevant, real-world use cases, such as semantic search and question answering. Able to streamline 80% of the mundane processing tasks, the NLP technology helps to ensure better efficiency in data processing, data analysis, reporting, as well as better customer experience, reduced costs of operation, and improved customer satisfaction. By leveraging natural language processing companies can create smart solutions to common business problems.

  • Natural language processing solutions (NLP) offer a variety of benefits of using artificial intelligence and machine learning tools to solve a range of common business and technology problems related to processing, sorting and making sense of data. We have helped the largest European companies and public sector organizations to instrument semantic search and question answering (QA) to automate data processing, legal analysis, regulatory compliance, and decision making. We've also built an enterprise SaaS product to complement our open source NLP framework (Haystack).