1
Tethr
Austin, Texas, United States
Tethr operates as an AI-powered conversation intelligence platform.
- Revenue
- $10M
- Customers
- -
- Year founded
- 2013
- Funding
- $51.2M
- Team size
- 25
- Growth
- -
Top 1,474 Natural Language Processing (NLP) Software SaaS Companies in July 2026
As of July 2026, there are 1,474 SaaS companies in Natural Language Processing (NLP) Software. They have combined revenues of $82B and employ 82.6K people. They have raised $250.1B and serve 1.5B customers combined.
Natural Language Processing (NLP) Software refers to technology that enables computers to comprehend, interpret, and generate human language in a valuable manner. This category of software applies various techniques from artificial intelligence and linguistics to allow machines to interact with text and speech data effectively. Common use cases include sentiment analysis, language translation, chatbots, and automated content generation, making NLP tools vital in customer service, marketing, and data analysis sectors. The primary features of NLP software often include text parsing, language understanding, emotion detection, and machine learning capabilities to improve interaction over time. Typical users of NLP software range from data scientists and software developers to business analysts and marketing professionals who seek to leverage language data for insights or enhance user experiences. As organizations increasingly rely on data-driven decision-making, NLP software has become essential in bridging the gap between human communication and machine processing.
Filters
Sorting: Highest -> Lowest
Top Natural Language Processing (NLP) Software Companies
Showing 10 of 148 companies ranked by annual revenue.
2
ProNavigator
Kitchener, Ontario, Canada
Developer of an insurance AI platform designed to empower insurance agencies and carriers to better support those interactions, on the customer's terms, using practical applications of artificial intelligence. The company's platform uses artificial intelligence to guide customers though the purchase and service experience by combining chat, smart dialogue systems, machine learning and natural language processing, enabling insurance companies to engage with their customers, answer questions and make policy changes in a cost-effective manner.
- Revenue
- $10M
- Customers
- 25K
- Year founded
- 2016
- Funding
- $6.4M
- Team size
- 32
- Growth
- -
3
Rollio
Brooklyn, New York, United States
Tired of updating your CRM? Our Salesforce Automation Software can help. What used to take 30 minutes now takes 5 with our voice to text technology!
- Revenue
- $10M
- Customers
- -
- Year founded
- 2014
- Funding
- -
- Team size
- 13
- Growth
- -
4
Airstrip AI
Mountain View, California, United States
Airstrip is an AI-powered legal co-pilot for your startup. Airstrip provides compliant personalized legal documents for your use case, provides AI powered personalized legal assistance, and provides expert insights. Launch confidently with Airstrip! ✈️
- Revenue
- $10M
- Customers
- -
- Year founded
- -
- Funding
- -
- Team size
- 2
- Growth
- -
5
Siro
New York, NY, United States
Siro records and transcribes face-to-face conversations to unlock missing revenue with AI. Leadership teams use Siro for strategic insight to understand what is happening in the field. Reps and technicians use Siro to build successful habits by listening to real examples from top performers on their own team. Proud to be an Alchemist Accelerator and Grand Central Tech company. Backed by CRV, Fika, and Index.
- Revenue
- $10M
- Customers
- -
- Year founded
- 2020
- Funding
- -
- Team size
- 40
- Growth
- -
6
Recall.ai
San Francisco, California, United States
The universal API for meeting video, audio and metadata
- Revenue
- $10M
- Customers
- 2K
- Year founded
- 2020
- Funding
- $38M
- Team size
- 25
- Growth
- 376.19%
7
Exa
San Francisco, California, United States
Exa was built with a simple goal — to organize all knowledge. After several years of heads-down research, we developed novel representation learning techniques and crawling infrastructure so that LLMs can intelligently find relevant information.
- Revenue
- $10M
- Customers
- -
- Year founded
- 2021
- Funding
- $335M
- Team size
- 90
- Growth
- 110.53%
8
Wispr Flow
San Francisco, California, United States
The voice-to-text AI that turns speech into clear, polished writing in every app.
- Revenue
- $10M
- Customers
- -
- Year founded
- 2021
- Funding
- $315M
- Team size
- 50
- Growth
- -
9
Revuze
Palo Alto, California, United States
Revuze is a leader in Generative AI analysis for online reviews, revolutionizing the consumer insights landscape. With years of experience leveraging LLM training, Revuze unlocks the full potential of insights from verified buyers across multiple e-commerce sources. Our cutting-edge solutions empower businesses to seamlessly integrate review analytics into their marketing and product processes, enabling strategic decision-making. Through high-quality data, insightful predictions, and scalable capabilities across sources and regions, we offer real-time analysis with intuitive features, dynamic dashboards, and comprehensive reports. From data collection to final visualization, Revuze’s end-to-end solutions ensure you can navigate the rapidly changing landscape of your categories and confidently make daily data-driven decisions. Discover the power of Revuze, the GPT of the consumer insights industry, and gain a deeper understanding of your customers and competitors.
- Revenue
- $9.9M
- Customers
- -
- Year founded
- 2013
- Funding
- -
- Team size
- 90
- Growth
- -
10
Pibit.ai
Palo Alto, California, United States
Transforming Commercial P&C Industry with LLM-Powered AI
- Revenue
- $9.8M
- Customers
- -
- Year founded
- 2020
- Funding
- -
- Team size
- 63
- Growth
- -
Inclusion Criteria
- Must enable understanding and processing of human language in text or speech formats. - Should include features for text analysis, such as sentiment analysis and language translation. - Must facilitate automated responses or interactions, like chatbots or virtual assistants. - Should support machine learning techniques to improve accuracy over time. - Not just focused on simple keyword extraction; must also provide deeper context understanding.