Anodot vs Weaviate

Weaviate has a disclosed valuation of $200M, while Anodot's valuation is not publicly available, making a direct size comparison difficult. Weaviate employs 80 people.

Weaviate has raised more in total funding at $67.5M, compared to Anodot's $66M — a gap of $1.5M. Combined, the two companies have completed 3 known funding rounds.

Weaviate holds the higher Awaira Score at 72/100, compared to Anodot's 55/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 17-point gap that reflects meaningful differences in scale or traction.

Anodot was founded by David Drai in 2014. Weaviate was founded by Bob van Luijt in 2019. Visit each company's profile on Awaira for a full founder biography.

Anodot: Anodot provides autonomous business monitoring powered by AI, using time-series anomaly detection algorithms to continuously monitor business metrics including revenue, usage, and operational KPIs across enterprise data sources and alert teams to significant deviations before they become customer-visible incidents. The Herzliya company machine learning models learn seasonality, trends, and normal variance patterns for each metric automatically, reducing alert noise by filtering out expected variation and surfacing only genuine anomalies.\n\nThe company raised approximately $66 million in venture funding including a Series C from investors including Aleph VC, Redline Capital, and Disruptive AI. Anodot serves telecommunications, fintech, gaming, and digital media clients including T-Mobile, Pandora, and Wix, deploying monitoring across billions of data points daily across client environments. The platform connects to data warehouses, streaming pipelines, and cloud monitoring sources through native integrations.\n\nAnodot competes in the AIOps and business monitoring market against Datadog, New Relic, and Sumo Logic for infrastructure monitoring use cases, and against business intelligence anomaly detection features in Tableau, Looker, and Power BI for business metric monitoring. Its focus on business-layer metric anomaly detection rather than infrastructure-layer monitoring differentiates it in the revenue operations and product analytics segments, where engineering-focused monitoring tools are insufficient for the metric breadth and business context that business operations teams require. Weaviate: Weaviate is a Netherlands-based vector database company founded in 2019 that enables organizations to build AI applications using vector search and semantic search capabilities. The platform stores, indexes, and searches unstructured data—including text, images, and audio—by converting them into vector embeddings, making it suitable for large language model applications and retrieval-augmented generation (RAG) systems. The core product is an open-source vector database with both community and enterprise versions. Weaviate allows developers to perform similarity searches and build knowledge graphs with semantic understanding. The platform integrates with machine learning frameworks and supports various embedding models, enabling organizations to power AI applications without extensive machine learning infrastructure expertise. Founded during the emergence of modern AI applications, Weaviate operates in the expanding vector database category competing with Pinecone, Milvus, and Qdrant. The company has raised $68 million across funding rounds with a valuation of $200 million as of its Series B stage. Weaviate serves use cases across e-commerce recommendation systems, content discovery, semantic search, and enterprise search applications. The company has gained adoption among developers and organizations building AI-powered products. Its open-source approach provides both community engagement and enterprise monetization pathways. The vector database market has experienced significant growth as organizations increasingly adopt large language models requiring efficient vector storage and retrieval infrastructure. Weaviate combines open-source accessibility with enterprise vector database capabilities positioned to capture growth in RAG and semantic search application development.

Anodot was founded first in 2014, giving it 5 years of additional market experience. Weaviate was founded later in 2019. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Anodot has approximately 100-500 employees, while Weaviate has approximately 80. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Anodot and Weaviate are direct competitors — both operate in the AI Data space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.