Enterprise AI fintech development & infrastructure
Dual-engine engineering for institutional financial systems. We provide custom fintech software development and build financial platforms where deterministic transaction systems and AI-driven decision models operate as one controlled architecture.
Core fintech solutions we develop
Our services cover custom fintech software development of systems that form the operational backbone of financial products, from transaction processing to compliance-driven workflows.
High-throughput transaction systems
We develop transaction-processing infrastructure that executes payments, settlements, and other financial operations in real time. The system supports high transaction volumes, maintains consistent performance, and ensures accuracy across complex financial workflows.
AI-driven KYC/AML & fraud vectorization
We build machine learning systems that analyze transactional behavior and evaluate financial activity in real time. The system identifies patterns across large data streams, supports compliance processes, and delivers precise fraud detection with controlled model behavior.
Core banking modernization
We transform legacy banking systems into flexible, API-driven architecture. New components are introduced gradually, allowing the system to evolve while maintaining full operational continuity and stable transaction processing.
ISO 20022 payment infrastructure
We implement payment systems aligned with modern financial messaging standards. The system enables structured, data-rich transactions and supports seamless communication across banks, payment networks, and financial platforms.
Institutional tokenization & smart contract security
We develop blockchain-based systems for managing tokenized assets and automated financial operations. The system ensures transparent transaction flows, verified execution logic, and infrastructure designed for institutional-grade usage.
High-throughput transaction systems
We develop transaction-processing infrastructure that executes payments, settlements, and other financial operations in real time. The system supports high transaction volumes, maintains consistent performance, and ensures accuracy across complex financial workflows.
AI-driven KYC/AML & fraud vectorization
We build machine learning systems that analyze transactional behavior and evaluate financial activity in real time. The system identifies patterns across large data streams, supports compliance processes, and delivers precise fraud detection with controlled model behavior.
Core banking modernization
We transform legacy banking systems into flexible, API-driven architecture. New components are introduced gradually, allowing the system to evolve while maintaining full operational continuity and stable transaction processing.
ISO 20022 payment infrastructure
We implement payment systems aligned with modern financial messaging standards. The system enables structured, data-rich transactions and supports seamless communication across banks, payment networks, and financial platforms.
Institutional tokenization & smart contract security
We develop blockchain-based systems for managing tokenized assets and automated financial operations. The system ensures transparent transaction flows, verified execution logic, and infrastructure designed for institutional-grade usage.
Dual-engine fintech engineering
SumatoSoft operates as a Dual-Engine engineering firm.
We develop systems that combine deterministic transaction execution and AI-driven decisioning within a single, controlled architecture. Every transaction and every decision follows defined logic, measurable outputs, and consistent system behavior.
Deterministic execution systems
AI-driven decision systems
Deterministic execution systems
This layer handles the core of financial operations.
Transaction processing, payment orchestration, settlement logic, and ledger integrity are implemented as stable, predictable systems. Every operation executes with full traceability, controlled performance, and alignment with regulatory requirements.
These systems form the execution backbone of the platform, ensuring consistency under high load and across complex financial workflows.
AI-driven decision systems
This layer introduces intelligence directly into operational processes.
KYC and AML evaluation, fraud detection, risk scoring, and financial forecasting operate as embedded components within the system. Each model produces traceable outputs, aligned with defined rules and business logic.
Decisions are applied in real time, enriching transaction flows while maintaining a governed and observable system behavior.
Benefits fintech systems bring
We design and build fintech systems as structured, production-ready infrastructure. Each system is defined by its architecture, transaction logic, and integration model, enabling it to operate predictably under real financial workloads and regulatory requirements.
Faster product launch
Bring new financial products to market with defined architecture and predictable delivery timelines.
Full control over transaction infrastructure
Manage performance, data, and business logic within systems designed around your operations.
Operational efficiency at scale
Transaction processing, validation, and AI-driven decision logic operate as part of a unified execution flow across high-volume financial workflows.
Scalable system architecture
Expand transaction capacity, integrations, and product lines without redesigning core systems.
Built-in regulatory alignment
Keep reporting, monitoring, and audit processes aligned with financial requirements.
Long-term system evolution
Extend your platform with new services, integrations, and AI capabilities as your business grows.
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Start building the financial future you envision today.
Pilot and prove your fintech system in 4-6 weeks
We run a structured pilot phase that validates your fintech system under real operating conditions before full-scale development. Within 4-6 weeks, you receive a working system foundation, measured performance data, and clear cost visibility for production rollout.
We define architecture, transaction flows, integrations, and decision logic aligned with your business model.
We build core components, connect data sources, and establish processing pipelines that support both transactional and analytical workloads.
We simulate real transaction scenarios to evaluate throughput, latency, and system behavior under operational conditions.
We validate how AI models and automated decision flows operate within your transaction systems, ensuring consistent outputs and controlled behavior.
We finalize performance benchmarks, cost models, and define the architecture and rollout plan for full-scale deployment.
Advanced financial engineering capabilities
We extend financial systems beyond transaction processing by embedding intelligence directly into operations. These capabilities function as controlled components within your architecture, expanding how data is processed, interpreted, and applied across the business.
Financial RAG systems
A structured retrieval layer connects internal documentation, financial reports, and external data sources into a unified knowledge system.
Users query this system in natural language and receive precise, context-aware answers with traceable references to the original data. We design these systems to ensure that every output remains grounded in verified sources and aligned with your internal data boundaries.
Agentic ledger reconciliation
Reconciliation becomes part of the system’s continuous operation rather than a separate process.
Transaction data flows across banking APIs, internal ledgers, and payment platforms, where records are automatically matched and aligned. We implement reconciliation logic that maintains consistent financial states across systems and provides full transaction traceability at any point in time.
Quantitative machine learning pipelines
Financial decision-making is supported by structured machine learning systems integrated into your workflows.
Market data, operational signals, and alternative datasets are processed through models designed for forecasting, pricing, and risk evaluation. We build these pipelines with clearly defined inputs, measurable outputs, and predictable behavior within your system architecture.
Integrated into your architecture
All capabilities are introduced as part of a coherent system design.
We define integration points, data flows, and execution boundaries so that each component operates within your infrastructure with full control and transparency. This allows advanced analytical capabilities to scale alongside your core systems without increasing operational complexity.
Industry-specific fintech solutions
Our custom fintech software development is tailored to different financial business models. Each system is designed to match how transactions are processed, how decisions are applied, and how operations are structured within your organization.
Banking software
Core banking systems, transaction engines, and API orchestration layers that unify financial operations across products, channels, and internal workflows.
Payment processing systems
Payment processing infrastructure that manages authorization, clearing, and settlement within a single execution layer, connected to global financial networks.
Trading & investment platforms
Trading platforms, portfolio systems, and analytics infrastructure that support real-time execution and continuous strategy evaluation.
Lending
Loan origination systems, credit decision engines, and risk evaluation models that structure and automate lending operations.
Corporate finance
Financial management systems, reconciliation engines, and reporting platforms that unify financial operations across the organization.
Insurance software
Underwriting platforms, claims processing systems, and policy management infrastructure that structure insurance workflows end-to-end.
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Security and compliance by architecture
Security and compliance are embedded directly into how your fintech system is designed and built. We engineer architectures where data access, transaction control, and system behavior are governed at every level.
AI-driven decision flows operate within defined data boundaries and access control rules. Each model follows the same governance structure as transaction systems, ensuring consistent behavior aligned with your security policies and regulatory requirements.
Role-based and data-level access control
Access to financial data is structured through role-based and attribute-based controls.
Every interaction with sensitive information is defined, traceable, and aligned with your internal policies and regulatory requirements.
PCI DSS, GDPR, SOC2 alignment
Your system is built to operate within established financial standards, including PCI DSS, GDPR, and SOC2.
Regulatory requirements are reflected in system architecture, data flows, and operational processes from the start.
PII redaction and controlled data pipelines
Sensitive data is handled through controlled processing pipelines, including data isolation, encryption, and selective redaction. This ensures that financial and personal data are consistently managed according to compliance expectations.
Zero-trust infrastructure
We design secure environments using zero-trust principles, where system components interact through verified and controlled channels. This creates a stable and governed execution environment for financial operations.
Integration with the financial ecosystem
We integrate your fintech system into the infrastructure your business already operates, ensuring consistent data flow, controlled execution, and predictable system behavior. Each integration is designed as part of the overall architecture, so every system communicates through clearly defined interfaces and operates within governed boundaries.
AI models and decision systems operate across integrated data flows, applying logic consistently as transactions move between internal systems, external providers, and financial networks.
- Core Banking Systems (Temenos, Finacle, FIS, Fiserv)
- Payment networks (SWIFT, SEPA, ACH)
- KYC and AML providers
- Trading and analytics platforms
- Internal enterprise systems (CRM, ERP, other internal tools)
Success stories of our Clients
The system has produced a significant competitive advantage in the industry thanks to SumatoSoft’s well-thought opinions.
They shouldered the burden of constantly updating a project management tool with a high level of detail and were committed to producing the best possible solution.
We tried another company that one of our partners had used but they didn’t work out. I feel that SumatoSoft does a better investigation of what we’re asking for. They tell us how they plan to do a task and ask if that works for us. We chose them because their method worked with us.
Rivalfox had the pleasure to work with SumatoSoft in building out core portions of our product, and the results really couldn’t have been better.
SumatoSoft provided us with engineering expertise, enthusiasm and great people that were focused on creating quality features quickly.
SumatoSoft is the firm to work with if you want to keep up to high standards. The professional workflows they stick to result in exceptional quality.
Important, they help you think with the business logic of your application and they don’t blindly follow what you are saying. Which is super important. Overall, great skills, good communication, and happy with the results so far.
We’d like to sincerely thank SumatoSoft for the work they’ve done on our maintenance system. At one point, our maintenance efforts became inefficient – long downtimes and rising repair costs became the norm.
Working with SumatoSoft has been an outstanding experience. Their team is not only highly skilled but also incredibly responsive, collaborative, and committed to delivering quality results. I can’t recommend them enough! Thank you team SumatoSoft for bringing my vision to life.
SumatoSoft is flexible, efficient, and extremely good at planning and being proactive. They have also been very proactive in their approach throughout the project, seeking to understand the needs and the reasons behind them before launching into development, which has been helpful for maintaining direction and consistency, especially because the end client is regularly generating new ideas for added features.
Awards & Recognitions
Frequently asked questions
How do you prevent Generative AI from “hallucinating” when giving automated financial or investment advice?
We engineer Deterministic AI Guardrails. Our systems never allow an LLM to generate financial figures or investment advice from its base training weights. The AI is strictly limited to extracting numbers directly from your verified internal databases or Bloomberg/Reuters APIs. Furthermore, an automated “LLM-as-a-judge” parses every output to verify mathematical accuracy before the user sees it.
How do you handle the latency requirements for high-frequency trading (HFT) or real-time payment processing when using Machine Learning?
You cannot query a cloud-based ML model during a sub-millisecond transaction. We implement Edge-Inference and In-Memory Caching (using technologies like Redis Enterprise or Aerospike). We train the fraud/pricing models offline, compile them into highly optimized C++ or Rust binaries, and deploy them directly alongside the transaction matching engine to ensure inference occurs in under 5 milliseconds.
How do you ensure AI integration complies with strict banking regulations like PCI-DSS and SOC2?
We implement Compliance-as-Code. Our architecture utilizes Zero-Trust network micro-segmentation. The AI models are hosted in completely isolated VPCs without internet access. Before any financial data is processed by the AI, it passes through an automated PII/PAN (Primary Account Number) redaction layer, ensuring your core compliance certifications are never compromised.
How do we extract data for Machine Learning from our legacy AS/400 or COBOL mainframe without causing system degradation?
You cannot query a legacy mainframe directly with heavy ML workloads. We engineer Change Data Capture (CDC) Pipelines. We read the transactional database logs directly (without querying the database itself) and stream those state changes in real-time via Apache Kafka into a modern cloud Data Lakehouse. Your AI models train on this synchronized cloud data, putting exactly zero compute stress on your critical mainframe.
How do you handle multi-tenant data architecture for a B2B FinTech SaaS without violating SOC2 or GDPR?
We engineer Siloed Multi-Tenancy with Row-Level Security (RLS). While the application compute layer is shared for cost-efficiency, the database layer utilizes strict logical isolation. Every tenant’s data is encrypted with their own unique, rotating Customer-Managed Key (CMK), ensuring that a breach or misconfiguration in one tenant’s environment physically cannot expose another bank’s data.
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Why Clients trust SumatoSoft with fintech development
We design and deliver fintech solutions where transaction infrastructure and AI operate as one controlled architecture.
Proven delivery
- 350+ custom software systems delivered
- 14+ years in software engineering
- 98% Client satisfaction
- Clients across 25+ countries
System-level execution
- High-throughput transaction platforms with embedded decision logic
- AI-driven KYC/AML and fraud detection integrated into transaction flows
- Financial data platforms combining real-time processing with machine learning models
- Quantitative ML systems supporting risk evaluation and financial decision-making
Controlled AI systems
- Controlled AI pipelines operating within defined data boundaries
- Model outputs aligned with business rules and system logic
- AI integrated into operational workflows, not isolated components
- Consistent performance across changing data and transaction conditions
Measured performance
- Stable transaction processing under load
- Predictable AI-driven outputs
- Consistent data across integrated systems
- Reliable system behavior at scale
What never changes in our services
While cooperation models adapt to your needs, the principles behind delivery remain consistent.
Risk-controlled delivery
We define scope, timelines, and cost structure upfront. Each stage is validated against clear criteria, so execution remains predictable and aligned with business goals.
When needed, we validate assumptions through focused pilot stages before scaling.
Full transparency
You always see the current state of the system and delivery progress.
We work with shared metrics, structured reporting, and clear documentation, so decisions are made with full visibility.
Built-in compliance
Compliance is embedded into system architecture from the start.
We design solutions aligned with financial regulations and internal governance standards, including PCI DSS, SOC2, GDPR, and industry-specific requirements.
Security by design
Security is implemented across infrastructure, data, and access layers.
We apply encryption, access control, and monitoring practices that support stable, secure operation at scale.
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