Nearshore AI · Financial Services · Production-Grade
Deploy Compliance-Ready AI in 6 Months — At 40% Lower Cost Than Onshore Teams.
The nearshore AI software factory purpose-built for regulated financial services — delivering production-grade models, sovereign infrastructure, and audit-ready governance, all within your time zone.
- Sovereign deployments — VPC, on-prem, or hybrid cloud with full data residency control
- Audit-ready governance — explainability, model cards, and documentation baked in from day one
- US time-zone collaboration — real-time standups, same-day code reviews, zero async lag
- Production-grade engineering — MLOps, CI/CD, and risk frameworks built for regulated environments
✓ SOC 2 aligned practices✓ DORA & Basel III compatible✓ No lock-in contracts
Designed for institutions navigating
FFIEC Guidelines
SR 11-7 Model Risk
OCC Fintech Framework
SEC AI Disclosure Rules
DORA Resilience
Basel III / IV
SOC 2 Type II
ISO 27001
The Problem
AI Is No Longer Optional.
But In Financial Services,
It's Complicated.
Regulatory Pressure Is Accelerating
The OCC, FFIEC, and SEC are issuing new AI-specific guidance at an unprecedented pace. Every model you deploy must now carry explainability documentation, bias testing, and model risk frameworks — before a single line hits production. The compliance bar isn't rising; it's already there.
AI Talent Is Scarce — and Expensive
Senior ML engineers who understand both financial modeling and regulated infrastructure command $220K–$320K in US markets. And they don't stay long. Your competitors are burning through capital trying to staff teams that evaporate in 18 months when projects stall or priorities shift.
Costs Are Spiraling Before Deployment
Most mid-sized financial institutions are spending 60–70% of their AI budget on integration, compliance scaffolding, and rework — not on models that generate revenue. Offshore providers offer low rates but introduce time-zone friction, documentation gaps, and security blind spots that quietly inflate total project cost.
Boards approve AI budgets. Executives announce AI strategies. And 73% of financial AI projects stall in pilot — never reaching production — because the gap between model development and regulated deployment is wider than anyone expected.
You're not behind because your team lacks ambition. You're behind because the standard playbook wasn't built for your environment.
The Only Nearshore AI Software Factory
Built for Regulated Financial Institutions.
We combine compliance-first engineering with nearshore cost efficiency — delivering production-ready AI at 40% lower cost than US onshore teams, without sacrificing governance, documentation, or security posture. Every sprint is structured around your regulatory reality, not retrofitted for it.
Two Paths to Production-Grade AI
Whether you need an embedded AI delivery machine or want to build sovereign in-house capabilities — we have a structured, compliance-first path to get you there.
Embedded AI pods that operate as an extension of your engineering org — owning full delivery from data pipeline to regulated production deployment.
- Cross-functional AI pods (ML Engineer, Data Engineer, MLOps, Compliance Lead)
- End-to-end MLOps infrastructure — experiment tracking, model registry, CI/CD
- Risk modeling: credit scoring, fraud detection, AML, market risk
- Secure data pipelines with encryption-at-rest and field-level access controls
- Automated audit documentation — model cards, bias reports, drift monitoring
- Regulatory alignment with FFIEC, SR 11-7, OCC, and SEC frameworks
Deploy in 6 months. Not 18.
Build a permanent, self-sufficient AI capability inside your institution — on your infrastructure, under your governance, with full knowledge transfer.
- VPC, on-premises, or hybrid deployment with zero third-party data exposure
- Data residency architecture — jurisdiction-compliant storage and processing
- Explainability frameworks built for examiner review (SHAP, LIME, custom)
- Compliance architecture: MRM policy, model inventory, validation workflows
- Full capability transfer — documentation, training, and runbooks for your team
- Ongoing advisory access post-transfer for governance and model refresh
Your AI. Your infrastructure. Your IP.
Built for Three Decision Makers
We speak the language of your boardroom, your risk committee, and your architecture review board — simultaneously.
You need AI that ships.
- Production-ready MLOps pipelines from day one, not prototypes
- Senior ML engineers embedded in your existing sprint cadence
- Architecture designed for scale — not just PoC demonstrations
- Full source ownership, no vendor lock-in, no black-box models
- CI/CD integration with your existing DevSecOps toolchain
- Real-time collaboration during US business hours
You need ROI that's provable.
- 40% lower blended cost vs. US onshore AI teams — guaranteed
- Outcome-based engagements with clear, measurable deliverables
- No headcount liability — flex up or down without severance risk
- Faster time-to-value: production in 6 months, not 18–24 months
- Transparent billing with fixed-scope options and predictable burn
- Cost avoidance from fewer compliance rework cycles
You need AI you can defend.
- Every model ships with examiner-ready documentation and model cards
- Bias testing, fairness audits, and disparate impact analysis included
- Model Risk Management aligned to SR 11-7 from initial design
- Full audit trail: data lineage, version control, decision logs
- Explainability frameworks that satisfy both OCC examiners and customers
- Dedicated compliance lead embedded in every delivery pod
Why Colombia is the
Smartest Nearshore Choice
for US Financial AI
Not all nearshore is created equal. Colombia's engineering talent pool has matured specifically around enterprise software and regulated industries — making it the premier destination for US financial services AI delivery.
- Same-day collaboration
UTC-5 (EST overlap) year-round — no daylight-saving mismatches, no 4 AM standups - Tier-1 engineering talent
Universidad de los Andes, EAFIT, and Uniandes consistently produce world-class ML and software engineers - English-fluent senior talent
Our engineers communicate directly with your architects, PMs, and examiners — no translation layer - Stable, US-treaty-aligned legal framework
Colombia's IP and data protection laws align with US commercial standards under TPA provisions - On-site availability
3-hour flight from Miami, 5 hours from NYC — key team members can be at your office within a business day - Growing fintech ecosystem
Colombia's financial technology sector is the third largest in Latin America, with deep domain expertise in financial regulation and banking systems
De-Risk Your AI Investment.
We've Already Built the Guardrails.
We understand why financial institutions are hesitant. The wrong AI partner can trigger a regulatory action, a model failure, or a $2M rework cycle. Here's how we've removed those risks from the equation:
- Compliance-first sprint structure — governance artifacts are deliverables, not afterthoughts
- Fixed-scope discovery engagements — know exactly what you'll get before you commit to full delivery
- Model validation independence — we support, not replace, your independent validation function
- No lock-in architecture — open-source stack, full IP transfer, zero proprietary dependencies
- Transparent failure protocols — if a model doesn't meet risk thresholds, we iterate, not hide
- Examiner-tested documentation — our templates have survived OCC and Fed examinations
- Data never leaves your perimeter — no cloud-hosted training, no third-party model APIs unless you mandate it
The institutions that will win the next decade aren't the ones who adopted AI fastest. They're the ones who adopted it in a way that survived a regulator's first question.
production
vs. onshore
incidents
Your regulatory examiners will approve. Your board will be briefed. Your engineers will ship.
We're not a consulting firm that hands you a roadmap and wishes you luck. We're an embedded delivery team that owns outcomes — from first sprint to production sign-off.
What Production-Grade AI
Looks Like in the Real World
Regional Bank Replaces Manual Credit Scoring with Explainable AI
A $12B asset regional bank needed to replace its 15-year-old scorecard with an ML-powered credit model that could survive OCC model validation. Our pod delivered an SR 11-7-aligned model with full SHAP explainability and 94% validation approval on first submission.
Fintech Lender Deploys Real-Time AML Transaction Monitoring
A Series C fintech needed production-grade AML monitoring before their banking charter application. Our sovereign deployment team built a VPC-isolated, real-time transaction scoring system with full FinCEN-aligned documentation in under 6 months.
Asset Manager Launches Personalized Portfolio Intelligence Platform
A mid-sized RIA wanted AI-powered portfolio insights without exposing client data to third-party LLM providers. We built a fully on-premises RAG architecture with client-permissioned data access, compliant with SEC Reg BI disclosure requirements.
Start With a
Compliance-First
AI Assessment
In 30 minutes, we'll map your specific regulatory context to a realistic AI deployment path — with cost, timeline, and risk estimates you can actually bring to your board.
In Your 30-Minute Call, You'll Walk Away With:
- Regulatory readiness gap analysis
Specific gaps between your current AI posture and examination-ready deployment - Realistic cost-to-production estimate
Honest numbers: blended team cost, timeline, and what your onshore alternative would actually cost - Use case prioritization framework
Which AI use cases in your pipeline carry the highest ROI vs. lowest regulatory risk — ranked - Recommended first sprint scope
A proposed first-sprint definition that you can validate with your team immediately after the call - No obligation, no sales pressure
If we're not the right fit, we'll tell you — and point you toward what is. Our reputation depends on honest conversations.