01
Digital banking experiences
Onboarding, lending, and self-service journeys that cut branch dependency without cutting trust.
Industries — Banking & finance
Financial software where every paisa reconciles.
Digital banking journeys, payment automation, and risk analytics — engineered with the security posture and reconciliation discipline that money demands, for banks, NBFCs, and fintechs.
Where we help.
02
Payments & reconciliation
Payment flows, dispute handling, and reconciliation engines — we run ChargebackZero, our own payments product.
03
Risk & compliance systems
KYC/AML workflows, audit trails, and reporting that stand up to regulator scrutiny.
04
Legacy core modernization
Strangler-pattern modernization around core banking systems, without big-bang risk.
AI, applied to financial services.
Production AI use cases we build for this industry — governed, secure, and measured against outcomes.
AI use case
Document intelligence for lending
Automated extraction from bank statements, invoices, and KYC documents — decisions in minutes, fully logged.
AI use case
Fraud & anomaly detection
ML models that flag suspicious patterns in transactions with explainable scoring for investigators.
AI use case
Customer-service copilots
Governed assistants that resolve routine queries and draft agent responses with full oversight.
AI use case
Credit & risk analytics
Predictive models on your portfolio data, with the documentation risk committees expect.
Relevant services.
Frequently asked questions.
How do you approach security for financial systems?
Threat modeling at design time, least-privilege everything, secrets management, penetration-test readiness, and audit logging on every state change.
Can AI be used in regulated financial decisions?
Assistively, yes — we build explainable models with human decision gates and complete audit trails, aligned to your model-risk governance.
Do you have real payments experience?
Yes — ChargebackZero, our own chargeback-prevention product, plus payment and reconciliation systems for clients.
Can you work alongside our core banking vendor?
Yes — we regularly build around core platforms, integrating through their APIs while keeping upgrade paths intact.
Use cases
Where we put technology to work in banking & finance
KYC document intelligence
IDs, statements, and proofs extracted, validated, and matched against master data — onboarding cut from days to minutes.
Fraud & anomaly models
Transaction scoring with explainable features, tuned thresholds, and analyst feedback loops that reduce false positives.
Loan origination workflows
Digital application-to-disbursement pipelines with maker-checker controls and full audit trails.
Relationship-manager copilots
LLM assistants that answer policy, product, and portfolio questions inside the bank’s perimeter.
Reconciliation automation
Multi-source ledger matching that clears itself — exceptions queued with evidence attached.
Regulatory reporting pipelines
Governed data flows that assemble filings from source systems with lineage regulators can follow.
In depth
Banking and financial services: innovation at regulated speed
Financial institutions must move at fintech pace under bank-grade scrutiny. We build digital banking journeys, lending and origination workflows, payment integrations, and reconciliation systems where every transaction is traceable and every release is auditable.
Our AI work in finance concentrates where volume meets judgment: document intelligence for KYC and loan files, ML models for fraud and credit risk with explainability that satisfies model-risk teams, and LLM copilots that let relationship managers query policy and portfolio in plain language — inside the bank’s perimeter.
Engineering standards match the stakes: immutable audit logs, maker-checker controls, performance-tested cores for month-end peaks, and security woven through the SDLC. Compliance is a design input, not a launch-week discovery.
Traceable to the penny
Ledger-grade audit trails and reconciliation built into every workflow.
Explainable risk AI
Fraud and credit models with the transparency model-risk governance demands.
Peak-proof platforms
Month-end, payday, and campaign spikes engineered as capacity plans.