BreezoMeter vs Pinecone

Pinecone has a disclosed valuation of $750M, while BreezoMeter's valuation is not publicly available, making a direct size comparison difficult. Pinecone employs 150 people.

Pinecone has raised more in total funding at $138M, compared to BreezoMeter's $21M — a gap of $117M. Combined, the two companies have completed 6 known funding rounds.

Pinecone leads with an Awaira Score of 76/100, while BreezoMeter sits at 42/100. That 34-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

BreezoMeter was founded by Ran Korber in 2014. Pinecone was founded by Edo Liberty in 2019. Visit each company's profile on Awaira for a full founder biography.

BreezoMeter: BreezoMeter provides AI-powered environmental data APIs covering air quality, pollen, weather, and wildfire risk, aggregating data from government monitoring stations, satellite imagery, and IoT sensors and applying machine learning models to produce street-level resolution environmental intelligence that application developers and enterprises integrate into health, insurance, and mobility products. The Haifa company delivers real-time and forecast environmental data at hyperlocal granularity that government monitoring networks cannot match.\n\nThe company raised approximately $21 million in venture funding and was acquired by Google in 2022, integrating its environmental data capabilities into Google Maps, Google Search, and Google Nest products. Prior to acquisition, BreezoMeter had built API customers including insurance companies for climate risk underwriting, asthma and respiratory health applications for personalised air quality alerts, and HVAC companies for air filtration product recommendations tied to local pollution levels.\n\nBreezoMeter competed in the environmental data and climate intelligence market alongside AirVisual (IQAir), PurpleAir, and government air quality data portals. The acquisition by Google reflected the strategic value of hyperlocal environmental data as an enrichment layer for mapping, local search, and home automation products where air quality and pollen information enhances the relevance of location-based recommendations. The combination of machine learning interpolation and sensor fusion to generate street-level environmental data from sparse monitoring networks represented a technically defensible approach that aligned with Google investment in location data quality. Pinecone: Pinecone is a vector database platform founded in 2019 that enables developers to build and deploy AI applications using vector embeddings. The company provides a fully managed cloud service that indexes and searches high-dimensional vector data at scale, serving as critical infrastructure for retrieval-augmented generation (RAG) and other machine learning workflows. Pinecone's core offering allows applications to store, index, and query embeddings generated from text, images, and other data types, facilitating semantic search and similarity matching capabilities essential for modern AI systems. The platform operates in the rapidly expanding vector database market, competing with alternatives including Weaviate, Milvus, and cloud provider solutions. Pinecone's approach emphasizes ease of use through a serverless architecture that abstracts infrastructure complexity, targeting developers building generative AI applications without deep database expertise. The company has achieved significant adoption among enterprises and startups applying large language models for production systems. As of the latest disclosed information, Pinecone has raised $138 million in funding and holds a valuation of $800 million. The company remains in Series B stage, indicating substantial market validation while operating in the pre-profitability phase typical of infrastructure software companies. Its growth trajectory reflects increasing demand for vector storage solutions as enterprises integrate AI models into production workflows. Pinecone's serverless vector database architecture uniquely abstracts infrastructure complexity for developers building retrieval-augmented generation systems at scale.

BreezoMeter got there first, launching in 2014 — that's 5 years of extra runway. Pinecone didn't arrive until 2019. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

BreezoMeter has about 1-50 employees; Pinecone has about 150. 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 BreezoMeter and Pinecone compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.