Weaviate
Weaviate is an Amsterdam-based, open-source AI-native vector database company providing vector search, hybrid retrieval, RAG, and agentic services to thousands of customers via self-serve cloud, dedicated enterprise deployments, and major cloud marketplaces.
- Company typePrivate
- Founded2019
- HeadquartersAmsterdam, Netherlands
- Headcount51–100
- GTM typeB2B
- OfferingSoftware
What Weaviate does
Weaviate is an Amsterdam-based, open-source AI-native vector database company founded in 2019 and incorporated as Weaviate B.V. in the Netherlands. Its platform stores high-dimensional vectors alongside source objects and supports vector, keyword, and hybrid (BM25 + dense) retrieval, multi-tenancy at tens of thousands of indexes per cluster, named vectors, modular embedding integrations with OpenAI, Cohere, Anthropic, Hugging Face, Mistral, NVIDIA, VoyageAI, Google, and others, and billion-scale data ingestion via a Spark connector. On top of the database Weaviate has built agentic services — Query Agent, Transformation Agent, Personalization Agent, and the Engram managed memory service — and developer tooling such as Weaviate Agent Skills for AI coding agents and an AI Workbench.
The company monetizes through multiple complementary streams: a usage-based Weaviate Cloud Serverless tier with a permanent free tier; annual Dedicated Cloud and Bring-Your-Own-Cloud enterprise deployments sold with SLAs, SOC 2, HIPAA, and RBAC; Weaviate Embeddings (pay-as-you-go vector generation, launched December 2024); Engram (freemium managed memory from $45/month, GA June 2026); and enterprise support. Distribution combines a product-led open-source motion (20M+ downloads, Academy, community) with enterprise field sales, cloud marketplace listings on AWS, Google Cloud, Snowflake, and Databricks, and a new partner-led channel in Japan via Ricoh. Customers span highly regulated industries (NATO, Thales, Cedience in pharma, MBH Bank) and AI-native scale-ups (Loti at 9B vectors, DocsBot at 50K+ tenants, Instabase at 450+ data types), giving Weaviate a hybrid enterprise + startup GTM profile.
Weaviate firmographics
Firmographics- Name
- Weaviate
- Legal name
- Weaviate B.V.
- Website
- https://weaviate.io
- Company type
- Private
- Founded year
- 2019
- Operating status
- Operating
- Headcount range
- 51–100 employees
- Short description
- Weaviate is an Amsterdam-based, open-source AI-native vector database company providing vector search, hybrid retrieval, RAG, and agentic services to thousands of customers via self-serve cloud, dedicated enterprise deployments, and major cloud marketplaces.
- Ownership category
- akta.pro rank
Weaviate industry classification
Industry- Product category
- Vector Database
- NAICS
- Software Publishers (5132)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- Metadata, Catalog & Semantic Layer for Data Platforms (HDAEABAJ)
- akta.pro secondary industries
- Retrieval-Augmented Generation (RAG), Vector Databases & Knowledge Grounding (HDAAACAE), Model Hosting, Serving & Inference Platforms (HDAAACAB), In-Memory Databases (HDAEAAAD)
Keywords
Where Weaviate is headquartered
LocationHeadquarters
- HQ city
- Amsterdam
- HQ country
- Netherlands
- HQ region
- Europe
Offices2 records
Markets served
Weaviate business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Infrastructure, Marketing or Sales, Operations
Revenue model
- Weaviate Cloud subscription (Serverless / Shared Cloud): Usage-based subscription for the shared multi-tenant Weaviate Cloud with a permanent free tier (limited queries/storage) and paid tiers billed on consumption. 'Start Free' CTA and self-serve sign-up drive PLG conversion.
- Dedicated Cloud / Bring Your Own Cloud: Enterprise-tier cloud offering (formerly Enterprise Cloud) deployed as a dedicated tenant or inside the customer's VPC, sold under annual/multi-year contracts with SLAs, SOC 2, HIPAA, and dedicated support.
- Weaviate Embeddings (pay-as-you-go): SaaS service launched December 2024 hosting open-source and proprietary embedding models with no rate limits in production; pay-as-you-go pricing for vector generation across text, images, and other modalities.
- Engram managed memory service: Production-grade memory service for AI agents launched GA in 2026 with a free tier and paid plans starting at $45 per month, billed monthly.
- Enterprise support and professional services: Paid support tiers (Slack, email, phone channels, target response times), complimentary training, and technical services packaged with Dedicated Cloud and Marketplace deployments.
- Open-source self-hosted license (BSD-3-Clause): Free open-source distribution under BSD-3-Clause license drives adoption and bottoms-up demand that converts into cloud and enterprise revenue.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Pay-as-you-go | Weaviate Cloud Serverless — free tier + usage-based pricing |
| Subscription | Annual | Dedicated Cloud / Bring Your Own Cloud |
| Freemium | Monthly | Engram managed memory service |
| Usage-based | Pay-as-you-go | Weaviate Embeddings (pay-as-you-go) |
| Other | Pay-as-you-go | Weaviate Database (open source) |
Go-to-market motion4 records
Distribution channels8 records
Marketing channels9 records
Weaviate product offering
Product offeringCore offering
Weaviate builds and distributes an open-source, AI-native vector database that stores and indexes high-dimensional vectors to power semantic search, hybrid (vector + keyword) retrieval, and retrieval-augmented generation (RAG). It sells Weaviate Cloud as a managed deployment (Serverless, Dedicated, Bring-Your-Own-Cloud) and complementary managed services including Weaviate Embeddings for vector generation, agentic services (Query, Transformation, Personalization agents), and Weaviate Engram for managed agent memory.
Product overview
Weaviate offers a unified AI database platform — built around the open-source Weaviate Vector Database — that combines vector search, hybrid search, and retrieval-augmented generation with built-in embedding generation (Weaviate Embeddings) and agentic services. The core database is complemented by the cloud-native Weaviate Query Agent for natural-language queries over multiple collections, the Weaviate Personalization Agent and Transformation Agent for autonomous data operations, and the newly generally available Weaviate Engram for managed agent memory. Developer-facing tooling includes the Weaviate AI Workbench, the Weaviate Agent Skills open-source repository for AI coding agents, the Spark Connector for large-scale data ingestion, and the Ref2Vec-centroid module for recommendation use cases. Weaviate Cloud delivers the platform as Serverless, Dedicated, and Bring Your Own Cloud deployments backed by SOC 2, HIPAA, RBAC, encryption, automated backups, and multi-AZ availability.
Differentiator
Problem solved
Functional benefit
Brands
- Weaviate Cloud: Managed cloud deployment service for the Weaviate vector database, including the free tier, Dedicated Cloud, and Serverless options.
- Engram
- Weaviate Agent Skills
- Weaviate Query Agent
Products and services
- Weaviate Vector Database Open-source, AI-native vector database that stores, indexes, and searches high-dimensional vectors at scale. Supports vector, keyword, and hybrid search, multi-tenancy, named vectors, full CRUD, replication, automated backups, sharding, and filtering for RAG and AI applications. Distributed under BSD-3-Clause license and used as the foundation for Weaviate Cloud and other services.
- Weaviate Cloud (Serverless, Dedicated Cloud, Bring Your Own Cloud) Fully managed deployment options for the Weaviate Vector Database, offered as usage-based Serverless (with a free tier), Dedicated Cloud (formerly Enterprise Cloud) single-tenant deployments sold under annual contracts with SLAs, and Bring Your Own Cloud (BYOC) deployments inside the customer's VPC. All tiers include SOC 2, HIPAA, RBAC, end-to-end encryption, automated backups, and multi-AZ high availability.
- Weaviate Embeddings SaaS service for vector generation across text, images, and other modalities, eliminating the need for an external embedding pipeline. Hosts open-source and proprietary embedding models (launched with Snowflake's Arctic-Embed) with no rate limits in production and pay-as-you-go pricing.
- Weaviate Query Agent Cloud-based agentic service that translates natural-language questions into optimized, multi-collection vector and hybrid queries with filters, sorts, and aggregations. Available in Ask Mode and Search Mode with a free tier of up to 250 ask / 1,000 search queries per month.
- Weaviate Engram Managed memory and context service for agentic AI applications that automatically extracts, transforms, deduplicates, and persists memories via asynchronous pipelines and serves them through hybrid search. Memories are scoped per project, user, and property to support personalization, continual learning, and multi-agent shared state.
- Weaviate Agent Skills Open-source repository providing structured skills, six slash commands, and production-ready cookbooks that equip AI coding agents such as Claude Code, Cursor, GitHub Copilot, VS Code, and Gemini CLI to generate production-ready Weaviate code.
- Weaviate Spark Connector Native Apache Spark / PySpark connector (io.weaviate:spark-connector) that ingests large-scale Spark DataFrames into Weaviate collections with automatic schema inference, designed for billion-scale imports on Databricks and other Spark platforms.
Quantifiable outcome
- 9 billion vectors in production at Loti with 200+ hours saved on database maintenance.
- +7 more outcomes
Companies that use Weaviate
Customer profileNamed customers19 records
Segments4 records
Ideal customer profiles3 records
Weaviate technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration20 records
AI capability13 records
Feature10 records
Weaviate partnerships and signals
Strategic signalPartnerships
Twelve partnerships are on record, tiered flagship, core and minor.
- Google CloudflagshipWeaviate Cloud is natively built on Google Cloud and scales using Google Kubernetes Engine. Native integrations with Vertex AI, Gemini Pro and Ultra, and PaLM. One-click deployment via Google Cloud Marketplace; joint blog posts and integrations with Google AI Workbench.
- SnowflakecoreRun Weaviate inside Snowflake's Snowpark Container Services so all data operations including embeddings and vector searches remain within the customer's secure Snowflake environment. Integration with Snowflake Cortex for LLM-augmented retrieval.
- CoherecoreNative text2vec-cohere module for vectorization and generative-cohere module for RAG; supports Cohere's multilingual embedding models including embed-multilingual-v2.0.
- OpenAIcoreNative text2vec-openai and generative-openai (and OpenAI Azure) modules for embeddings and generative search.
- AnthropiccoreListed as an API-based model provider integration for embedding and generative use cases within Weaviate.
- Hugging FacecoreNative text2vec-huggingface module enabling any Hugging Face transformer model for vectorization; used historically for the Sphere dataset demo.
- Mistral AIcoreListed as a model provider integration within Weaviate for embedding and generative use cases.
- NVIDIAcoreNative integration with NVIDIA models via model provider module within Weaviate.
- VoyageAIcoreNative VoyageAI integration for embeddings within Weaviate; VoyageAI is also listed as a Weaviate subprocessor.
- DatabrickscoreNative integration with Databricks Foundation Model APIs via text2vec-databricks and generative-databricks modules. Weaviate Spark Connector enables large-scale data ingestion into Weaviate from Databricks; planned integration with Databricks Mosaic AI Agent Framework and Unity Catalog.
- SmartCatminorBuilt the Weaviate Spark Connector in collaboration with Weaviate's partner team; credited in joint blog posts and the spark-connector GitHub repository.
- Amazon Web Services (AWS)flagshipWeaviate is available on AWS Marketplace and leverages Amazon Bedrock to help customers build semantic search and generative AI functionality within AWS. Byron Voorbach heads sales engineering for cloud expansion.
Scale indicators14 records
Recent moves6 records
Expansion highlights6 records
Weaviate competitors and assessment
Company assessmentDirect peers
- Chroma: Open-source embedding database widely adopted by AI developers; competes head-to-head with Weaviate in developer-led vector search use cases and is increasingly shipping managed/enterprise features.
- Qdrant: Rust-based open-source vector database with a managed cloud offering; competes with Weaviate on performance, hybrid search, and metadata filtering for production AI workloads.
- Pinecone: Managed vector database purpose-built for AI applications; directly competes with Weaviate's cloud offering for semantic search and RAG workloads, with a similar PLG + enterprise GTM motion.
- Milvus (Zilliz): Open-source vector database built for billion-scale similarity search; directly competes with Weaviate on architecture, scale claims, and enterprise deployments, with a managed cloud offering via Zilliz.
Broad incumbents
- Redis (with vector search): Incumbent in-memory data platform that has added vector search (Redis Vector Library / RediSearch); competes with Weaviate for low-latency vector retrieval use cases, particularly for real-time recommendation and caching.
- MongoDB Atlas Vector Search: Incumbent document database that has added native vector search and AI integrations; competes with Weaviate for the same enterprise workloads, particularly with customers already standardized on MongoDB.
- Snowflake (Cortex AI / Vector Search): Cloud data platform that has added vector search and AI functions via Snowflake Cortex and partners with Weaviate via Snowpark Container Services; competes for AI workloads running inside customer Snowflake environments.
- Databricks (Mosaic AI / Vector Search): Lakehouse platform with native vector search and Mosaic AI; partners with Weaviate through the Spark Connector and Foundation Model integrations but also competes for enterprise RAG workloads inside the Databricks ecosystem.
- Elasticsearch / Elastic: Established search and analytics platform with vector search and hybrid retrieval capabilities; competes with Weaviate on hybrid search use cases within enterprises already running the Elastic stack.
Emerging players
- Vespa: Open-source search and vector database from Yahoo; serves production-grade semantic search and AI-native ranking at scale, with overlapping developer positioning to Weaviate though smaller community footprint.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
Weaviate social profiles
Digital presenceWeaviate compliance and trust
Trust signalCompliance5 records
Weaviate financial estimates
Financial estimateRevenue estimate
Valuation estimate
Weaviate leadership team
Management profileNumber of profiles
Profiles6 records
Weaviate funding detail
Funding detailFunding overview
Funding rounds3 records
Investors8 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Weaviate M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Weaviate
What does Weaviate do?
Weaviate builds and distributes an open-source, AI-native vector database that stores and indexes high-dimensional vectors to power semantic search, hybrid (vector + keyword) retrieval, and retrieval-augmented generation (RAG). It sells Weaviate Cloud as a managed deployment (Serverless, Dedicated, Bring-Your-Own-Cloud) and complementary managed services including Weaviate Embeddings for vector generation, agentic services (Query, Transformation, Personalization agents), and Weaviate Engram for managed agent memory.
Is Weaviate a public or private company?
Weaviate is a private company. It is classified as venture growth investor backed and is currently operating.
When was Weaviate founded?
Weaviate was founded in 2019. It employs 51 to 100 people.
Where is Weaviate based?
Weaviate is headquartered in Amsterdam, Netherlands, in the Europe region.
How does Weaviate make money?
Six revenue lines are on record. Weaviate Cloud subscription (Serverless / Shared Cloud) is the primary driver. The others are dedicated Cloud / Bring Your Own Cloud, weaviate Embeddings (pay-as-you-go), engram managed memory service, enterprise support and professional services and open-source self-hosted license (BSD-3-Clause).
Who are Weaviate's main competitors?
Direct peers on record are Chroma, Qdrant, Pinecone and Milvus (Zilliz). Broad incumbents are Redis (with vector search), MongoDB Atlas Vector Search, Snowflake (Cortex AI / Vector Search), Databricks (Mosaic AI / Vector Search) and Elasticsearch / Elastic. Vespa is listed as an emerging player.
Does Weaviate have an API?
Yes. Weaviate exposes public REST, GraphQL, and gRPC APIs for vector, keyword, hybrid, and generative search, batch import, collection/object management, and agentic operations. Endpoints support authentication via API keys and OIDC and are documented at docs.weaviate.io. SDKs are available for Python, JavaScript/TypeScript, Go, Java, and C#. Weaviate Cloud offers a free sandbox tier and an Agent Skills repository for generating production-ready code via AI coding assistants such as Claude Code, Cursor, GitHub Copilot, VS Code, and Gemini CLI. Developer documentation is at docs.weaviate.io/weaviate/api/rest.
What industry is Weaviate in?
Weaviate's product category is Vector Database. Its primary akta.pro industry code is HDAEABAJ, Metadata, Catalog & Semantic Layer for Data Platforms, with a secondary code of HDAAACAE, Retrieval-Augmented Generation (RAG), Vector Databases & Knowledge Grounding. Its NAICS code is 5132 and its SIC code is 7372.