Fasal vs Weaviate

Weaviate has a disclosed valuation of $200M, while Fasal'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 Fasal's $12M — a gap of $55.5M. Combined, the two companies have completed 5 known funding rounds.

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

Fasal was founded by Ananda Verma in 2018. Weaviate was founded by Bob van Luijt in 2019. Visit each company's profile on Awaira for a full founder biography.

Fasal: Fasal is a precision farming platform that deploys IoT sensors in agricultural fields to collect real-time micro-climate, soil moisture, and pest pressure data, which is then analyzed by AI models to deliver actionable crop management advisories directly to farmers' smartphones. The platform helps farmers make data-driven decisions about irrigation, fertilization, and pest management to improve yields and reduce input costs.\n\nThe company raised approximately $12M in Series A funding from investors including Omnivore, and has deployed its sensor networks and AI advisory platform across thousands of farms in India covering crops including grapes, tomatoes, pomegranate, and rice. Fasal's AI models are trained on crop science and agronomic data to translate sensor readings into specific, actionable recommendations.\n\nIndian agriculture faces significant productivity gaps relative to global benchmarks, with irrigation overuse, input inefficiency, and pest losses representing measurable economic costs at the national scale. Fasal's data-driven precision agriculture approach addresses these inefficiencies in a market where increasing farm profitability and resource efficiency are national policy priorities. 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.

Fasal got there first, launching in 2018 — that's 1 year 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.

Fasal has about 50-200 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 Fasal and Weaviate compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.