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Fintech platform development and financial software solutions

Build financial software that connects your users, data and systems

In a financial product, the rules are the product: who can approve what, which checks run before money moves, and what record is left for the auditor. We build fintech platforms, marketplaces and internal finance tools around those rules, with role-based permissions, audit trails and connections to payment providers, identity checks and data sources. When a product already exists, we can audit and fix it instead of starting over.

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  • Approvals, permissions and audit trails built in
  • Connections to payment, identity and data providers
  • Internal tools for finance and operations teams
  • Audits and fixes for existing fintech products

Why it works.

  • 01

    Write the rules down first

    Approval limits, roles, checks and exceptions decide the scope more than the screens do. We map them in week 1, so the build doesn’t discover them halfway.

    Clear product rules

  • 02

    Keep a record of every decision

    Who approved what, when and on what evidence. An audit trail is cheap to build at the start and expensive to add later.

    Audit trail

  • 03

    Connect, don’t rebuild

    Payments, identity checks (KYC), company data and e-signatures already have good providers. We connect them and build the part that makes your product different.

    Proven providers

  • 04

    Improve what already exists

    An existing product may need an audit, fixes and new features, not a rebuild. We start by reading the code and the data.

    Audit to build

How a request moves through the system.

A typical approval path once the system is built. The checks and their order are yours to define.

  1. A request comes in A payment, an application or a new vendor to onboard
  2. Identity and data checks KYC provider, company registry and credit data, called automatically
  3. Rules flag the risk Limits, thresholds and red flags you define, explained in plain words
  4. AI reads the documents Statements, contracts or proposals summarised, key fields pulled out for the reviewer
  5. A person decides Anything above a limit or flagged goes to an approver, with the evidence on one screen
  6. Logged with who and why The money moves or the record updates, and the decision is kept with its reasons
Rules decide, AI prepares, a person approves. We don’t let AI move money on its own.

What we’ve learned.

From the projects we’ve built in this area.

  • 01

    Decide what must be auditable before you design screens.

    Regulators, auditors and boards ask who decided, on what evidence and when. If the data model records that from day one, a report is a query. If it doesn’t, the report becomes a project.

  • 02

    Buy the regulated parts.

    Payments, card processing, identity checks and bank connections come from licensed providers such as Stripe or a KYC service. Building them yourself rarely makes sense and brings obligations of its own. Custom software should sit on top and run your process.

  • 03

    AI belongs next to the decision, not in it.

    AI is good at reading statements, contracts and vendor proposals, matching them to requirements and drafting a summary for the reviewer. The decision stays with rules and a person, especially when money moves or a customer is affected. Every AI suggestion should be logged with the final decision.

  • 04

    An audit often beats a rewrite.

    Products that feel broken often have a few root causes, such as slow queries, unclear permissions or missing tests. A focused audit finds them, and fixing them usually costs less than starting over. With Dilly Labs, we audited and fixed the existing platform, then kept adding features.

What we can build.

  • Platforms and marketplaces

    • Fintech platforms and B2B marketplaces
    • Onboarding with identity (KYC) and company checks
    • Client portals with statements and documents
    • Vendor and partner portals

  • Rules and control

    • Approval chains and limits by role
    • Audit trails of every change and decision
    • Role-based permissions and two-factor login
    • Exception queues for manual review

  • Integrations

    • Payments through Stripe and Stripe Connect
    • KYC providers, company registries and credit data
    • E-signatures and document generation
    • Accounting and ERP exports

  • AI and reporting

    • Document reading for statements, invoices and contracts
    • Requirement matching and draft recommendations for reviewers
    • Reports and dashboards for finance teams
    • Audits and fixes of existing fintech code

White-label, custom on licensed providers, or all in-house?

Three realistic ways to get a financial product to market. Most teams we talk to end up in the middle.

White-label platformCustom on licensed providersEverything built in-house
Time to a first version Weeks 6 weeks–3 months Many months
Your own product rules Partly Yes Yes
Payments and identity checks Included From providers Your responsibility
Audit trail you control Partly Yes Yes
Sets your product apart No Yes Yes
Ongoing cost Licence fees Provider fees and hosting A large in-house team
Licensed providers handle the regulated plumbing, and custom software handles the part customers actually choose you for. That is the sensible default for most teams.

Projects like this.

What we’ve built for clients in this field.

  • Fintech platform

    Dilly Labs

    Global fintech vendor platform · Global

    The problem

    The company needed to improve vendor records, procurement tools and the platform’s technical structure.

    What we built

    • Platform audit and remediation
    • Ongoing feature development
    • Vendor and workflow support inside the product
    • A record of each vendor decision and its reasons

    What changed: Platform issues addressed, with further features added to the existing product.

  • Marketplace

    Cardino

    Marketplace workflow product · Europe

    The problem

    The team needed seller onboarding, dealer auctions and internal tools ready for launch.

    What we built

    • Seller onboarding
    • Dealer auction workflow
    • Operational tools for the marketplace

    What changed: Seller onboarding, dealer auctions and operations tools delivered for the marketplace.

How the first version comes together.

A typical timeline. We confirm yours after the project workshop.

  1. Day 1

    30-minute call

    Your product, your users and the rules that matter. You leave with what to build first and a rough price.

  2. Week 1

    Rules and risk workshop

    We map approvals, permissions, checks and the audit trail with your product and compliance people, then agree a fixed price.

  3. From week 2

    Build in 2-week stages

    A working demo every week, on test accounts from your payment and KYC providers.

  4. Launch

    Security checks, then live

    An access review, permission tests and, if you need one, an external penetration test before real money moves. You own the code, the repositories and the accounts.

  5. +3 months

    Free bug fixes

    Then optional monthly support as the product grows.

Our past projects took 6 weeks to 3 months to reach a first version. Approval by payment and KYC providers can take time, so we start it early.

Case studies.

Systems we’ve built that are close to this one.

  • Dilly Labs

    Fintech · San Francisco, CA

    A platform for choosing financial technology vendors

    Tools for financial institutions to compare vendors, collect proposals, and record their decisions

    Read the case study

  • Transfer International

    HR & Recruitment · Slovakia

    Candidate and employee management

    Workforce platform for temporary staffing, recruitment, compliance checks, and payroll administration

    Read the case study

  • Sprout

    Sports Management · Springboro, OH

    Making gym management easier

    Gym SaaS for class enrollment, parent self-checkout, and Stripe Connect billing

    Read the case study

Further reading.

  1. AI, GDPR and the EU AI Act: what a European company needs to know How GDPR applies when you use AI, what the EU AI Act requires and by when, and the practical steps most small and mid-sized companies need. Read the article
  2. Keeping AI agents safe: prompt injection, permissions and audit logs How AI agents that read emails, documents or web pages can be tricked, and the defences that work: least privilege, hard limits, approvals and logs. Read the article
  3. Human in the loop: where to keep people in AI processes Five ways to keep a person in an AI process, how to design a fast review screen, and how to move the line as you learn to trust the system. Read the article

Questions people ask.

Do you work with early-stage fintech teams?

Yes. We help define and build the first version, usually on top of licensed providers for payments and identity checks. Our past projects took 6 weeks to 3 months to reach a first version, so you can test the product with real users before investing more.

Can you improve an existing fintech product instead of starting over?

Yes. We start with an audit of the code, the data model and the permissions. We list what is risky and what is slow, and fix the most important issues first. That is how we worked with Dilly Labs before adding new features.

Do you take care of compliance?

We build the controls your compliance team asks for, such as audit trails, permissions, approval chains, data retention and reports. We don’t give legal advice or hold financial licences. Your compliance team or advisor decides what rules such as AML, PSD2 or DORA require, and we implement it.

Which providers can you connect?

If a provider has an API, we can usually connect it. On past projects we’ve used Stripe and Stripe Connect for payments, Sumsub and TrustID for identity checks, Finstat for Slovak company data and Eversign for e-signatures. We check your providers’ APIs before we quote.

How do you keep financial data secure?

We build with role-based access, two-factor login, encrypted connections, separate test and live environments and logs of who accessed what. Hosting can be in the EU or in your own cloud account. For higher-risk products we recommend an external penetration test before launch.

Can AI be used safely in a financial product?

Yes, for reading documents, matching requirements, drafting summaries and answering questions from your own data. Decisions that move money or affect a customer stay with rules and a person. We also limit what the AI can access and do, because documents can contain hidden instructions meant to mislead it.

What does it cost?

One process, such as an internal approval tool connected to 1–2 systems, costs €5–10k. A platform or portal with 10+ features and several integrations costs €10–30k, and larger platforms or replacements of older software start at €30k. We agree a fixed price after the project workshop, before any build starts.

Who owns the code and the accounts?

You do. At launch you get the code, the repositories and the accounts, including the ones with your payment and data providers. We fix bugs free of charge for 3 months, then you can choose monthly support or have your own team take over.

Planning a fintech product or rebuild?

Tell us about your product idea, or the system you already have. We’ll tell you what to build or fix first and what it would cost.

JurajCEO, QikBuild

You leave the call with

  • What we would build first
  • A rough price range
  • Whether custom software makes sense for you
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