A Major Private Credit SaaS Platform

Client background

A SaaS leader in private lending sought to expand into the private credit sector by modernizing how lenders evaluate complex corporate loans. Traditionally, each opportunity required a team of three underwriters to spend 4–6 weeks manually reviewing a vast mix of borrower, guarantor, and company documents ranging from personal financials and bank statements to org charts, tax returns, insurance certificates, debt schedules, and pro formas before assembling a standardized loan memo. 

This time-intensive, document-driven process was the primary bottleneck limiting scale, speed, and consistency across the underwriting operation.

The problem

Additional Constraints

The client had no prior experience in the private credit sector, creating uncertainty around where to start and how to validate the opportunity. XTAM partnered closely through the discovery and design phases, helping identify and onboard design-partner lenders as part of the go-to-market strategy. 

This collaborative approach not only accelerated market learning but also built internal sponsorship and executive confidence, ultimately giving the client the conviction to pursue what became a transformative new business line.

What We Did

Discovery & Sourcing

• Partnered with the client’s product and underwriting teams to interview potential lenders and define the right  wedge into the private credit market.
• Cataloged diligence questions across finance/accounting, business/management, legal/compliance, underwriting/servicing, and technology/infosec — linking each to its corresponding source documents (e.g., AR/AP agings, bank statements, debt schedules, org charts, insurance certificates, UCC filings, SOC/ISO audits).
• Designed document ingestion and tagging processes so the AI could understand document scope,  relationships, and context for each deal.

Architecture Build Out

•Developed a secure, GCP-hosted AI pipeline for document retrieval, OCR, classification, and structured extraction, segmented by diligence category.
•Built REST APIs returning structured answers with confidence scores and source citations down to the page level, flagging low-confidence fields for human review.
•Delivered an embeddable conversational co-pilot API, allowing underwriters to query the AI directly  (e.g., “Show AR over 60 days for April” or “Where did we get guarantor net worth?”) and cross-reference across document categories.
•Implemented conversation logging per opportunity to maintain audit trails, support compliance, and enable continuous model improvement.

Pilot & Roll out

•Provided white-glove support through the first 10 loan memos, refining parsing, field mappings, and exception workflows.
•Supplied API documentation, an onboarding run-book, partnered with the Private Credit’s front end development team to implement the APIs, and a recommended Salesforce integration architecture, ensuring Salesforce remained the single pane of glass.
•Maintained a clear division of responsibilities — client owned UI, authentication, and approvals, while XTAM focused on AI reliability and performance.
•Trained the client’s development team to manage and extend the AI infrastructure long-term, building internal capability and ownership.

“

We made a big bet with XTAM and it’s worth every penny. This will  be transformational for our industry.
— Private Credit CEO

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