Cervest vs Weights and Biases

Weights and Biases has a disclosed valuation of $1.3B, while Cervest's valuation is not publicly available, making a direct size comparison difficult. Weights and Biases employs 300 people.

Weights and Biases has raised more in total funding at $250M, compared to Cervest's $32M — a gap of $218M. Combined, the two companies have completed 7 known funding rounds.

Weights and Biases leads with an Awaira Score of 80/100, while Cervest sits at 45/100. That 35-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Cervest was founded by Iggy Bassi in 2016. Weights and Biases was founded by Lukas Biewald in 2017. Visit each company's profile on Awaira for a full founder biography.

Cervest: Cervest builds a climate intelligence platform that quantifies climate risk for physical assets including agricultural land, commercial real estate, and infrastructure, using AI models that integrate climate science projections with asset-level data to produce probabilistic risk scores across multiple climate scenarios and time horizons. The London company targets institutional investors, insurers, and corporate treasury teams seeking to quantify physical climate risk in their portfolios.\n\nThe company raised approximately $32 million including a Series A round with investors including Astanor Ventures, Alumni Ventures, and the Future Planet Capital fund. Cervest built its EarthScan product as a SaaS platform delivering climate risk analytics for millions of individual assets, compatible with financial reporting frameworks including TCFD and SFDR that require climate risk disclosure from institutional investors. The platform covers risk categories including flood, drought, heat, wildfire, and storm surge across global geographies.\n\nCervest competes in the physical climate risk analytics market alongside Jupiter Intelligence, The Climate Service, and Verisk Climate, as well as large financial data providers including Moody ESG Solutions and S&P Sustainable. Regulatory pressure on financial institutions to disclose climate-related physical risks under TCFD and forthcoming mandatory climate disclosure regimes represents the primary demand driver for the company products. The market is growing rapidly as regulators in Europe, the UK, and North America formalise climate risk reporting requirements for banks, insurers, and listed companies. Weights and Biases: Weights and Biases is a machine learning platform founded in 2017 that provides infrastructure for experiment tracking, model management, and collaboration in AI development. The company's core product enables data scientists and ML engineers to log, visualize, and compare machine learning experiments, addressing the reproducibility and collaboration challenges inherent in modern AI workflows. The platform integrates with popular ML frameworks including PyTorch, TensorFlow, and scikit-learn, allowing teams to track metrics, parameters, and outputs across training runs. W&B's offering extends to model registry capabilities, enabling organizations to version, document, and deploy models systematically. The company serves enterprises across computer vision, natural language processing, and reinforcement learning domains. As of its Series C funding stage, Weights and Biases has raised $250 million at a $1.3 billion valuation, positioning it among well-capitalized AI infrastructure startups. The company competes in the ML operations space alongside platforms like Databricks and Neptune, differentiating through its focus on experiment tracking and accessibility to individual practitioners and teams. Notable adoption spans research institutions and technology companies implementing large-scale ML pipelines. The platform's freemium model has facilitated rapid adoption within the academic and startup ecosystems, while enterprise offerings target organizations requiring advanced governance and integration capabilities. Growth trajectory reflects increasing enterprise demand for ML operations infrastructure. Weights and Biases occupies a critical position in the ML operations stack by specializing in experiment tracking and model management, essential infrastructure that bridges individual data scientist workflows and enterprise-scale ML deployment.

Cervest got there first, launching in 2016 — that's 1 year of extra runway. Weights and Biases didn't arrive until 2017. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Cervest has about 1-50 employees; Weights and Biases has about 300. 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 Cervest and Weights and Biases compete in AI Data, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.