MSME & Micro-Lending
Automate credit decisions for unstructured evidence: handwritten ledgers, crumpled receipts, local IDs. Zero-shot document intelligence — no template training.
Where every decision must be correct, fast, and auditable. We turn "messy reality" — unstructured documents, images, logs — into deterministic outcomes using domain-trained SLMs deployed inside your VPC.
THE PROBLEM
When decisions are manual, the business cannot scale safely.
Documents, images, logs, exceptions. Unstructured evidence that legacy OCR can't handle without months of template training.
Brittle logic breaks under compliance. Policy exceptions compound. Manual overrides become the norm.
Slow, costly, inconsistent. Every new workflow means more headcount, more training, more risk.
"There is no infrastructure layer for regulated decisions. Until now."
THE SOLUTION
One engine. Many decision workflows. Every decision is explainable, traceable, and production-grade.
Domain-trained SLMs and VLMs interpret messy real-world evidence: documents, images, invoices, IDs, handwritten logs.
Zero-shot document intelligence. No template configuration. No 6-month training ramp-up.
Policy and business logic applied deterministically. Regulatory rules, risk thresholds, SOPs — enforced, not suggested.
Same input, same output, every time. No temperature variance. No hallucination risk.
Auto-approve, reject, or escalate to humans — with full justification and audit trail. Humans only handle true exceptions.
Every decision is explainable, reproducible, and compliance-ready.
Multi-modal engine: extracting deterministic decisions across image, video, text, and unstructured logs.
{
"evidence": "multi_modal",
"decision": "APPROVE",
"confidence": 0.99,
"latency_ms": 42,
"policy_flag": null
}WHY GENERAL AI FAILS HERE
WHERE IT PAYS OFF FASTEST
Automate credit decisions for unstructured evidence: handwritten ledgers, crumpled receipts, local IDs. Zero-shot document intelligence — no template training.
VLMs analyze storefront photos to verify business viability. Cross-reference physical imagery against EXIF geospatial metadata for fraud defense.
Apply underwriting rules to extracted data. Auto-approve, escalate, or reject with full auditable justification.
Interpret referrals, medical notes, and lab results using domain-trained SLMs. Apply payer and clinical policy rules to auto-approve or escalate.
Pre-screen claims using documents, images, and structured data to route only high-risk cases to human investigators.
Verify licenses, certifications, and compliance documents automatically during onboarding and audits.
All decisions are explainable, auditable, and run inside the customer's VPC.
ENTERPRISE GUARANTEES
The inference engine runs inside your secure cloud environment. No customer PII leaves your perimeter.
Powered by edge-based SLMs, Qwen-family VLMs, Rust, and low-latency GPU orchestration via vLLM. Backed by elite infra partnerships granting our team access to massive compute clusters, the newest GPUs, and frontier developer tools like Claude Code.
Ephemeral processing. Documents processed in-memory and instantly purged. Zero data retention.
Compliant with BSP IT Risk Management, Data Privacy Act, HIPAA, and EU AI Act requirements.
Designed for production, not pilots.
THE TEAM
DJ brings over a decade of expertise at the intersection of AI, regulated finance, and hyper-scale infrastructure. Prior to BPOptima, he served as Interim CTO/VP at a $200M ARR NBFC, where he launched an AI-driven risk engine processing $34M+ in credit disbursements. He previously founded Sauda Tech (processing ~$67M GMV), drove blitz-scale growth at multiple VC backed B2B SaaS ventures and has angel-invested in 18 startups (3 exits, 27% realized IRR). His operator background ensures BPOptima is architected for the strict compliance and throughput demands of institutional CTOs.
BPOptima's sovereign decision infrastructure is currently deployed in production for a Tier-1 digital bank in APAC. We partner with institutional risk officers and enterprise operators to automate complex, multi-modal workflows where strict compliance, speed, and zero data leakage are mandatory.
Backed by Antler, BPOptima's core infrastructure group brings together deep-tech engineering talent specialized in edge-based Small Language Models (SLMs), Vision Language Models (VLMs), and low-latency GPU orchestration (via vLLM). Our engineering foundation is built on memory-safe (Rust), deterministic policy layers deployed exclusively within secure enterprise VPC environments. We don't build wrappers, we deploy sophisticated Sovereign AI that keeps your data private & in your control.
NEXT STEP
We map one real workflow and show how it runs end-to-end without human bottlenecks.
Deployed inside customer cloud · Policy-constrained · Fully auditable