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About Weaviate
Industries
Data & Analytics
AI & Machine Learning
Company Size
51-200
Company Stage
Series B
Total Funding
$65.9M
Headquarters
Amsterdam, Netherlands
Founded
2019
Overview
Weaviate specializes in vector search technology, which uses mathematical vectors to represent data, allowing for information retrieval based on meaning rather than just keywords. This method is particularly beneficial in eCommerce, as it enhances user experience by understanding the context behind search queries. Weaviate integrates with popular AI frameworks like OpenAI and Huggingface Transformers, offering both an open-source version for users who prefer community support and a managed service called the Weaviate Cluster Service for enterprises needing direct support and infrastructure management. The company operates on a subscription-based model, providing a fully managed environment for clients, which includes different pricing tiers based on support levels. Weaviate serves a wide range of clients, from startups to large enterprises in sectors such as eCommerce, healthcare, and finance, aiming to deliver advanced search capabilities that give them a competitive edge.
Simplify's Take
What believers are saying
- Increased interest in vector databases boosts demand for Weaviate's offerings.
- Integration with major cloud providers enhances Weaviate's appeal to enterprises.
- The launch of Weaviate Embeddings attracts AI developers with flexible data solutions.
What critics are saying
- AI agents like Cognition AI's Devin may overshadow Weaviate's vector search technology.
- Popularity of RAG techniques could reduce demand for traditional vector search methods.
- Rapid AI expansion may strain Weaviate's resources if competitors offer better integrations.
What makes Weaviate unique
- Weaviate specializes in vector search technology, enhancing data retrieval by meaning, not keywords.
- It integrates with AI frameworks like OpenAI and Huggingface, offering seamless AI solutions.
- Weaviate provides both open-source and managed services, catering to diverse enterprise needs.
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Funding
Total Funding
$65.9M
Above
Industry Average
Funded Over
3 Rounds
Battery VenturesIndustry standards
Growth & Insights and Company News
6 month growth
↓ -1%1 year growth
↓ -6%2 year growth
↓ -6%Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. If 2023 was the year of generative AI-powered chatbots and search, 2024 was all about AI agents. What started from Devin earlier this year grew into a full-blown phenomenon, offering enterprises and individuals a way to transform how they work at different levels, from programming and development to personal tasks such as planning and booking tickets for a holiday.Among these wide-ranging applications, we also saw the rise of data agents this year — AI-powered agents that handle different types of tasks across the data infrastructure stack. Some did basic data integration work while others handled downstream tasks, such as analysis and management in the pipeline, making things simpler and easier for enterprise users. The benefits were improved efficiency and cost savings, leading many to wonder: How will things change for data teams in the years to come?Gen AI Agents took over data tasksWhile agentic capabilities have been around for some time, allowing enterprises to automate certain basic tasks, the rise of generative AI has taken things entirely to the next level.With gen AI’s natural language processing and tool use capabilities, agents can go beyond simple reasoning and answering to actually planning multi-step actions, independently interacting with digital systems to complete actions while collaborating with other agents and people at the same time. They also learn to improve their performance over time.Cognition AI’s Devin was the first major agentic offering, enabling engineering operations at scale
Vector database company Weaviate launched a new hosted embedding service for AI applications this month.
Weaviate has recently launched a brand new embedded service platform called Weaviate Embeddings, designed to provide AI developers with a more flexible and efficient data vectorization solution.
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. When large language models (LLMs) emerged, enterprises quickly brought them into their workflows. They developed LLMs applications using Retrieval-Augmented Generation (RAG), a technique that tapped internal datasets to ensure models provide answers with relevant business context and reduced hallucinations. The approach worked like a charm, leading to the rise of functional chatbots and search products that helped users instantly find the information they needed, be it a specific clause in a policy or questions about an ongoing project.However, even as RAG continues to thrive across multiple domains, enterprises have run into instances where it fails to deliver the expected results. This is the case of agentic RAG, where a series of AI agents enhance the RAG pipeline
Weaviate integrates its solution with Google Cloud, Azure, AWS, Confluent, and Snowflake.
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About Weaviate
Industries
Data & Analytics
AI & Machine Learning
Company Size
51-200
Company Stage
Series B
Total Funding
$65.9M
Headquarters
Amsterdam, Netherlands
Founded
2019
There are no jobs for Weaviate right now.
Find jobs on Simplify and start your career today