iMerit vs Weaviate

Weaviate has a disclosed valuation of $200M, while iMerit'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 iMerit's $24.3M — a gap of $43.2M. Combined, the two companies have completed 6 known funding rounds.

Weaviate leads with an Awaira Score of 72/100, while iMerit sits at 55/100. That 17-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

iMerit was founded by Radha Basu in 2012. Weaviate was founded by Bob van Luijt in 2019. Visit each company's profile on Awaira for a full founder biography.

iMerit: iMerit is an India-based data AI company founded in 2012 that specializes in providing high-quality training data for artificial intelligence and machine learning applications. The company operates in the data labeling and annotation space, a critical component of AI development pipelines. iMerit's core services include image annotation, video labeling, natural language processing data preparation, and autonomous vehicle training data collection. The company employs a distributed workforce model across India to deliver scalable data annotation solutions to enterprise clients developing AI systems. iMerit has positioned itself within the competitive data labeling market alongside competitors like Scale AI, Labelbox, and Superb AI. The company has secured $24M in total funding and operates at Series B stage, though its current valuation remains undisclosed. Its growth trajectory reflects increasing enterprise demand for quality-assured training datasets as AI adoption accelerates across industries. iMerit serves customers across computer vision, autonomous driving, natural language processing, and other AI domains requiring large-scale labeled datasets. The company's distributed India-based workforce provides cost-effective data annotation while maintaining quality standards through proprietary processes and quality control mechanisms. This operational model has enabled iMerit to scale efficiently while competing globally in the data preparation infrastructure space. iMerit employs India's distributed talent pool with proprietary quality assurance processes to deliver cost-effective training data at scale for enterprise AI applications. 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.

iMerit got there first, launching in 2012 — that's 7 years of extra runway. Weaviate didn't arrive until 2019. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

iMerit has about 5000 employees; Weaviate has about 80. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both iMerit and Weaviate compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.