Auquan

Auquan

Auquan builds agentic AI workflows that automate the repetitive execution work consuming finance professionals' time. Its platform transforms raw data into ready-to-review outputs for credit analysis, sustainability monitoring, and investor reporting — compressing two-day tasks like IC memo generation and covenant monitoring into 30-minute autonomous processes. The system ingests both proprietary client data and a global universe of over 2 million sources in 76 languages, producing complete audit trails for every insight. Clients span institutional asset managers, private equity firms, and wealth managers who collectively oversee more than $1 trillion in analyzed assets. Deal screening and credit memo production anchor the credit module, where Auquan claims to cut diligence cycles from days to half an hour. A partner at a private equity firm with over $30 billion in AUM described the platform as effectively reducing false positives and negatives in pre-diligence screening (per firm website). On the sustainability side, the firm automates ESG screening, portfolio monitoring, and regulatory compliance documentation for clients including Delancey and a top-25 global asset manager with over $1 trillion in AUM (per firm website). Investor relations workflows replaced include limited partner reporting, DDQ responses, and side-letter compliance tracking. Auquan does not disclose its own assets under management, headcount, or founding year, positioning itself purely as a technology vendor rather than a capital allocator. Its customer base reaches across Europe and North America, with named users at Federated Hermes and Amati Global Partners illustrating an appetite among emerging-market and small-cap equity managers for its unstructured-data surveillance (per firm website). The product claims to eliminate the 32-plus hours per week that finance professionals report spending on manual execution tasks. Auquan's structural distinction lies in pairing agentic automation with an auditable evidence chain — an architecture that rejects black-box AI in favor of fully sourced outputs. Unlike traditional data terminals or outsourced research providers, the system does not deliver raw information; it completes entire workflows and surfaces only the finished product, leaving investment professionals to exercise judgment on pre-assembled materials. That design targets a cost-per-output model that scales coverage without proportional headcount growth.