
Navigate decision complexities with clarity, assurance, and confidence. We augment your decision-making by combining deep business context with evidence-driven insights.
We use cutting-edge data science techniques to meticulously assess the quality, relevance, and suitability of your data before you make key decisions.
High-quality and dependable data forms the cornerstone of our innovative approach. We assist you in securely integrating and managing your data efficiently.
Join forces with seasoned Silicon Valley innovators dedicated to revolutionizing how organizations navigate complex decisions. We help teams add contextual insights to their data, enabling more informed and effective decision-making.
We stand at the junction of industry knowledge and technological advancement. By forging collaborative partnerships with our clients, we ensure that the solutions we craft are desired by users and drive organizational success.
Agile, adaptable, and vision-driven, we specialize in crafting innovative solutions that first tackle the most impactful challenges. Our approach focuses on achieving meaningful transformation and setting a new standard in addressing significant issues efficiently and effectively.
Cuneiform® for Valuation Risk is an intuitive platform used by financial institutions to improve the fair-value estimation of assets and ease the P&L creation process by providing scenario and trend analysis, price backtesting, and contextual views of instrument prices using various datasets.
Cuneiform® for CRM (Salesforce) is a business data reliability application that enables CRM Admins, data stewards, and implementation teams to rapidly assess and quantify data challenges, prioritize business risks, and effectively manage improvement efforts and support desired business objectives.
Cuneiform® for Data Cloud is the first data management application on and for Salesforce Data Cloud that enables organizations to accelerate and derisk implementations, continually assess data quality against fit-for-purpose metrics, and reduce operational costs incurred by unnecessary reprocessing.