List of Weaviate Customers
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Since 2010, our global team of researchers has been studying Weaviate customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Weaviate for AI Database from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Weaviate for AI Database include: StackAI, a United States based Professional Services organisation with 25 employees and revenues of $2.90 billion, Loti AI, a United States based Professional Services organisation with 120 employees and revenues of $3.0 million, Kapa, a Denmark based Professional Services organisation with 20 employees and revenues of $1.0 million and many others.
Contact us if you need a completed and verified list of companies using Weaviate, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Weaviate customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Kapa | Professional Services | 20 | $1M | Denmark | Weaviate | Weaviate | AI Database | 2024 | n/a |
In 2024, Kapa implemented Weaviate as its core vector database to power documentation and developer-support chatbots for support and documentation use cases across Europe. Kapa uses Weaviate as the AI Database that centralizes semantic search and retrieval tasks, accelerating time-to-value and enabling rapid onboarding for developer and documentation workflows.
The implementation leverages embeddings and RAG-style retrieval patterns, with Weaviate hosting vector indexes and serving nearest-neighbor retrieval to conversational layers. The team built a working integration in seven days, configuring embedding pipelines and retrieval logic to support doc-chat flows and developer support interactions, and the full application name Weaviate is used as the primary store for vectorized documentation.
Operational coverage focused on support and documentation business functions within the companys European footprint, with the Weaviate AI Database integrated into chatbot workflows to enable support-deflection and doc-chat scenarios. The team reports cost and accuracy advantages for those use cases, and rollout emphasized rapid iteration and onboarding rather than broad enterprise governance processes.
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Loti AI | Professional Services | 120 | $3M | United States | Weaviate | Weaviate | AI Database | 2024 | n/a |
In 2024, Loti AI implemented Weaviate, an AI Database, to store and search extremely large-scale multimodal vectors for likeness and digital-identity protection. Loti AI is a United States professional services firm of about 120 employees and the deployment is focused on security and content-moderation workflows.
The Weaviate deployment emphasizes multimodal embeddings for face and voice vectors and high-volume vector indexing to support likeness detection and similarity search. The production environment handles extreme scale, operating approximately 9 billion vectors and ingesting 120 to 140 million images and videos daily, leveraging dense vector indexing and high-throughput ingestion capabilities typical of an AI Database.
Operational scope centers on automated scanning and takedown workflows for digital-identity protection and content-moderation across Loti AI operations in the United States. Governance and process changes concentrated on instrumenting automated takedown pipelines and feeding vector search signals into security workflows. The implementation produced stated operational efficiencies, including saving over 200 hours per year.
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StackAI | Professional Services | 25 | $2.9B | United States | Weaviate | Weaviate | AI Database | 2024 | n/a |
In 2024, StackAI implemented Weaviate as its vector database to power an enterprise AI agent and orchestration platform. Deployment targeted operations, finance, and healthcare functions in the United States, with Weaviate positioned as the AI Database backbone for agent-driven knowledge retrieval and orchestration.
Implementation focused on vector storage, hybrid semantic search and metadata filtering to support contextual retrieval and policy-aware response selection. Configuration included vector indexing, semantic nearest neighbor search combined with structured metadata filters, and schema design to map embeddings to business entities used by the AI agent. The deployment emphasized operational capabilities for agent workflows and centralized semantic search across internal datasets.
Governance incorporated metadata-level filtering and access controls to align search results with security requirements and to meet the needs of security-conscious customers. StackAI reports tens of thousands of dollars in cost savings versus alternatives and improved enterprise-readiness as explicit outcomes of the Weaviate deployment. The Weaviate AI Database now underpins agent orchestration for operations, finance, and healthcare within the United States.
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Buyer Intent: Companies Evaluating Weaviate
- Unnsse Khan US, a United States based Professional Services organization with 10 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
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