Enterprise NLP Accelerated
Reduce your time to market by always building NLP-enabled products faster.
Unlocking the power of NLP
Our products and technology enable fast integration of NLP functionality for enterprise applications.
Streamlining NLP product lifecycle
For product managers
— Deliver prototypes and MVPs faster by adopting an iterative approach to NLP
— Facilitate collaboration and reduce misunderstandings between teams
— Collect and analyze early end-user feedback for better prioritization
— Optimize product development budget and increase ROILearn more about deepset Cloud
For ML/NLP professionals
— Avoid the need to build everything from scratch by leveraging pre-trained models and LLMs
— Use pipeline templates for common use cases to optimize application design
— Speed-up and simplify evaluation
— Share experiments and prototypes with key stakeholdersLearn more about deepset Cloud
For software engineers
— Focus on business logic and features rather than the infrastructure
— Quickly integrate NLP into existing or new applications
— Build for scalability and performance using production-ready backend architecture
— MLOps for NLP made easy — deploy fast while minimizing downtimeLearn more about deepset Cloud
Why build an NLP-driven solution?
Explore how NLP can benefit your business through these common use cases.
NLP for finance
Read how NLP helps finance sector organizations to be more competitive and customer-oriented.
NLP for legal
Learn how NLP helps implement innovative IT products for legal professionals.
Semantic search and question answering
The technology behind Google-like enterprise search experience.
Technical use case
Start building in deepset Cloud
From data to API-driven NLP backend services in no time.
Events and resources
Sign up for our upcoming events and download free resources below.
Beyond ChatGPT: Where to Start Improving Your Enterprise Search
Learn how hybrid search, pseudo-labelling and fine-tuning can drastically improve your search application.
Building Applications with LLM-based Agents
Learn how to implement Agent-driven systems with Haystack.
This event was recorded on 16.05.2023Watch on-demand
Natural Language Processing with Transformers
Read more about Transformers and building question answering with Haystack.
Sponsored O'Reilly ebook
Free downloadDownload now
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, such as corporate documents, financial reports, research papers, and legal contracts, presents a challenging problem for enterprise product teams. Typically, this type of data is difficult for enterprise software to process. NLP allows developers to apply the latest research to industry-relevant, real-world use cases, such as semantic search and question answering. By streamlining approximately 80% of mundane processing tasks, NLP technology ensures better efficiency in data processing, data analysis, reporting, as well as improved customer experience, reduced operational costs, and increased customer satisfaction. Leveraging natural language processing, companies can create intelligent solutions for 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).