Revolutionize your
unstructured data lifecycle

Businesses today are inundated with vast volumes of purchase orders and invoices coming through multiple channels-emails, paper mail, fax-and often in unstructured, inconsistent formats. This unstructured data flow creates significant operational challenges, as manual processing of these documents is time-consuming, inefficient and expensive. On average, manual invoice processing takes about 14 days per invoice, with some industries experiencing cycle times extending up to 25 days, leading to delayed payments and strained vendor relationships. The cost of manual processing ranges from approximately $10 to $16 per invoice, but can escalate to $30 or more when factoring in error correction and exception handling. Considering that many organizations process thousands to tens of thousands of invoices and purchase orders monthly, the cumulative annual expense runs into millions of dollars globally. Moreover, manual processes come with error rates between 12% and 15%, causing further financial leakage through duplicate payments, missed discounts, and compliance penalties. Despite these inefficiencies, nearly half of companies still rely on manual or semi-manual workflows, underscoring the urgent need for smarter solutions.

The global private debt market reached approximately $1.5 trillion at the start of 2024, up from $1 trillion in 2020, and is projected to grow to $2.6 trillion by 2029. As these markets expand rapidly and become increasingly complex, AI-driven solutions offer a powerful lens for different stakeholders—investors, fund managers, lenders, and regulators—to gain deeper, real-time insights into risk exposures and portfolio vulnerabilities.

A $6Tr Financial Services Industry spends more than $40Bn in acquiring and managing data. According to a survey by TMM Data & Digital Analytics Association, ~40% of data professionals spend more than 20 hrs / wk accessing, blending and preparing data rather than performing actual analysis. With more than 90% of all new enterprise data appearing in unstructured sources, businesses face an arduous challenge of making the data usable before losing its economic value. While legacy solutions are rigid, expensive and difficult to implement, companies lack tools to synthesize valuable unstructured information at scale. Refer to the visual representation of unstructured data flows across various organizations within Capital Markets.