Case 001FintechLending Infrastructure

How we built a neo-lending platform from zero to $8M disbursed in 6 weeks

CarePal Money came to us with a partner deal, a runway clock, and no engineering team. Six weeks later they were live, compliant, and disbursing real loans.

Book a call hello@solprime.ai
6 Weeks
Kickoff to first live disbursement
$8M+
Disbursed in the first quarter post-launch
3
Lending partners integrated end-to-end before launch
01 · Context

The brief

CarePal Money’s CEO approached Solprime with a closed lending partnership but no platform to operationalize it. Their constraint was brutal: their partner had given them a 60-day window to go live, or the deal would lapse. They had no in-house engineering team and three failed conversations with traditional dev shops who had quoted 5–6 months and $250,000+.

They needed three things at once: a borrower-facing onboarding flow, a working lending engine integrated with bureau and KYC providers, and a partner-side reconciliation system. All production-grade. All compliance-ready. All in under two months.

02 · Decision

Why they chose Solprime

CarePal Money’s CEO told us in our first call that every other agency had pitched them a “discovery phase.” They didn’t have time for discovery, they had a deal closing. We scoped the build in a 90-minute working session and committed to a 6-week timeline with weekly visible sprints. No black box. No surprises.

We also brought something the other agencies didn’t: an AI-native build philosophy. From day one, AI wasn’t a feature bolted on at the end, it was baked into underwriting decisioning, document parsing, and borrower support.

03 · Delivery

What we built

The lending platform stack, four layers that ship together.

Layer 01Onboarding
Borrower onboarding & KYC
A mobile-first onboarding flow with bureau pull, video KYC integration, and document upload. We integrated three KYC providers with automatic failover so dropout rates stayed below 12% even when one provider had downtime.
Layer 02Underwriting
AI-native underwriting engine
A rules-plus-ML decisioning layer. Hard rules handle compliance and policy gates; a lightweight ML scorer handles thin-file applicants where bureau data is incomplete. LangChain orchestration for document understanding, salary slips, bank statements, with structured output extraction running against Claude and a fallback to a fine-tuned smaller model for cost control.
Layer 03Disbursement
Partner & disbursement layer
Real-time API integrations with three lending partners, each with their own contract terms, repayment schedules, and reconciliation formats. We built a unified abstraction so CarePal Money’s team could onboard a fourth partner in days, not weeks.
Layer 04Operations
Operations & audit
Full audit trail of every decision, every document, every disbursement, built compliance-ready from day one. SOC2-aligned logging, role-based access, and an ops console for CarePal Money’s customer-success team.
04 · Technology

The stack

Frontend

Next.js (borrower-facing web app), React + TypeScript (component layer & type safety), Tailwind (design system & tokens)

Backend

Node.js (core API & orchestration), PostgreSQL (loan records & audit trail), Redis (session & decisioning cache)

AI Layer

LangChain (document orchestration), Claude (primary; reasoning & extraction), OpenAI (fallback; redundancy layer), Pinecone (document retrieval)

Infrastructure

AWS (EKS + RDS + S3; compute, database, storage), CloudFront (global CDN), AWS WAF (web application firewall)

Integrations

3 KYC providers (automatic failover), 2 credit bureaus (bureau pull on onboarding), 3 lending partners (unified abstraction layer), Stripe (repayment rails)

Compliance

SOC2-aligned logging (full audit trail from day one), Encrypted PII (at rest and in transit), Regulatory audit trails (every decision captured)

05 · Execution

How the six weeks looked

Six one-week sprints. Full visibility at every gate. CarePal Money’s CEO could see working software on Friday of every week, not slides, not a status update, a running build.

Week 1
Scope, architecture & partner API contracts
Locked the full architecture in a 2-day working session. Signed off integration contracts with all three lending partners. Defined the data model, the decisioning contract, and the compliance logging schema. Borrower flow wireframes signed off by Friday.
Week 2
Onboarding & KYC
Shipped the full borrower onboarding flow with all three KYC integrations and automatic failover. Bureau pull wired and tested. CarePal Money’s team could complete a test application end-to-end by Friday standup. Dropout rate in testing: under 10%.
Week 3
Underwriting engine
Built the rules engine and the AI document-parsing layer. LangChain orchestration live, Claude extraction running against salary slips and bank statements with structured output. First test loan decisioned by AI on Thursday. Hard rules layer reviewed with CarePal Money’s compliance advisor.
Week 4
Partner integration & disbursement
All three lending partner APIs integrated. Reconciliation formats built for each. Money movement tested end-to-end in sandbox, loan application through to simulated disbursement and repayment schedule generation. The unified abstraction layer was already working well enough that CarePal Money’s CEO started mapping their fourth partner.
Week 5
Operations console, audit logging & security review
Internal ops tooling built: loan queue, manual review workflow, reconciliation dashboard, and role-based access for CarePal Money’s customer-success team. SOC2-aligned audit logging wired throughout. External security review completed. UAT with CarePal Money’s team, nine issues found, all resolved by Thursday.
Week 6
Production deployment & first live disbursement
Production push on Tuesday. Final smoke tests Wednesday morning. First real loan disbursed Thursday afternoon. We stayed on standby for the next 14 days under our Operate SLA, monitoring production, handling the first edge cases, and handing off a stable platform to CarePal Money’s team with full runbooks.
06 · Results

The outcomes

Numbers from the first quarter of live operation. Every figure below reflects real borrower behaviour and real money movement on the production platform.

$8M+
Disbursed in the first quarter post-launch. The partner deal that was at risk of lapsing became the foundation of a live, operating lending business within 6 weeks of our first call. The $8M figure covers real loans to real borrowers on the production platform, not test transactions.
<12%
Borrower onboarding dropout, well below the industry benchmark of 25–30%. The failover logic across three KYC providers meant that provider downtime, which typically causes dropout spikes in lending onboarding flows, had no visible effect on the completion rate. Borrowers who started the application finished it.
71%
Of applications handled by AI-driven decisioning without human review in month one. The underwriting engine processed the majority of loan applications fully automatically, bureau pull, document parsing, scoring, decision, with no human in the loop. The remaining 29% were routed to manual review by the rules layer, not by system failure.
Zero
Production incidents in the first 60 days post-launch under our Operate SLA. The platform ran without a single production-impacting incident through the first two months of live operation. The stability was a direct result of the security review, the UAT process, and the two-week post-launch standby period baked into our delivery model.
Week 9
Fourth lending partner onboarded by CarePal Money’s own team, three weeks after launch, without our involvement. The unified partner abstraction layer we built in week four meant CarePal Money’s team could onboard a new lending partner using our integration pattern without writing custom code. The platform was designed to grow from day one.
07 · In Their Words

What CarePal Money’s CEO said

“We came to Solprime with a partner deal, a runway clock, and no engineering team. Six weeks later, we were live and disbursing real loans. Six months in, we’ve crossed $8M+ in disbursements, and the same architecture still runs the business. They didn’t just ship us an MVP; they shipped us infrastructure.”

CEO, CarePal Money

08 · Implications

Why this matters for your build

If you’re a founder with a closed partnership, a runway clock, or an investor expectation that you’ll ship by a specific date, the lesson from this build is straightforward: the bottleneck is almost never the technology, it’s the operating model of the team building it. Six-month timelines from traditional agencies are an artifact of how they staff and bill, not how long the actual work takes.

We built this in six weeks because we ran it as six one-week sprints with full visibility, made the AI layer a first-class architectural decision rather than an afterthought, and stayed on the platform after launch instead of handing off the mess.

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