Dataloop vs Patsnap

Patsnap has a disclosed valuation of $1B, while Dataloop's valuation is not publicly available, making a direct size comparison difficult. Patsnap employs 500-1000 people.

Patsnap has raised more in total funding at $300M, compared to Dataloop's $49M — a gap of $251M. Combined, the two companies have completed 4 known funding rounds.

Patsnap leads with an Awaira Score of 80/100, while Dataloop sits at 55/100. That 25-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Dataloop was founded by Eran Shlomo in 2017. Patsnap was founded by Jeffrey Tiong in 2007. Visit each company's profile on Awaira for a full founder biography.

Dataloop: Dataloop builds an AI data management and annotation platform that covers the full data pipeline for computer vision and NLP model development, combining data labelling tools, annotation workflow management, quality assurance automation, and model training integration in a single platform. The Tel Aviv company targets AI teams at enterprises and AI product companies that need to manage large-scale data labelling operations with quality controls and annotator workforce management.\n\nThe company raised approximately $49 million including a Series B round from investors including Viola Ventures and Samsung Next. Dataloop counts enterprise AI teams in automotive, retail, and agriculture verticals among its clients, with the platform used for large-scale computer vision dataset creation including bounding box annotation, semantic segmentation, and polygon annotation for object detection model training. The platform supports human-in-the-loop annotation workflows where model predictions are reviewed and corrected by human annotators to improve efficiency.\n\nDataloop competes in the data annotation and management market alongside Scale AI, Labelbox, Encord, and V7, as well as annotation services providers. The market has evolved from pure annotation tooling toward platforms that combine labelling with dataset management, model evaluation, and active learning capabilities. Dataloop positioning as a full data management platform rather than a labelling tool aims to capture more of the AI development workflow and reduce customer dependency on multiple point solutions across the data pipeline. Patsnap: Patsnap provides an AI-powered patent analytics and intellectual property intelligence platform that enables R&D teams, IP lawyers, and corporate strategy teams to search, analyse, and monitor global patent databases using machine learning to surface technology trends, competitor patent activity, and freedom-to-operate insights from over 170 million patent documents. The Singapore company integrates patent data with scientific literature and chemical structure databases to provide a comprehensive IP and technology intelligence environment.\n\nThe company raised approximately $300 million including a Series E round from investors including SoftBank Vision Fund 2, Tencent, and CPE Yunji, reaching a valuation exceeding $1 billion. Patsnap serves over 10,000 companies globally including R&D-intensive organisations in pharmaceuticals, semiconductors, automotive, and consumer electronics that use patent landscape analysis to inform technology strategy and investment decisions.\n\nPatsnap competes in the IP analytics market against Derwent Advancement (Clarivate), Questel Orbit, and Minesoft, as well as general enterprise search platforms that include patent data. Its AI capabilities for patent claim analysis, technology trend extraction, and cross-domain IP search differentiate it from traditional Boolean-search patent databases, enabling R&D strategy questions to be answered through AI-assisted analysis rather than manual patent review. The Singapore base provides access to both the Southeast Asian technology market and a sophisticated legal and financial services market for IP monetisation and licensing analytics.

Patsnap got there first, launching in 2007 — that's 10 years of extra runway. Dataloop didn't arrive until 2017. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Dataloop has about 100-500 employees; Patsnap has about 500-1000. 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 Dataloop and Patsnap compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.