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DFT Solutions

Software development for banks

We developdigital twins, AML agents, ERP agents, AI applications, AI platformsfor banks.

DFT Solutions designs and implements digital twins of processes, AI agents for business units and internal applications, deploys them on the bank’s servers or in its private cloud, and supports them after launch.

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A bank building and its digital twin shown as a wireframe model
01What we do

Four lines of development

All solutions
  1. Digital twins
    • Digital twins
    • Release testing
    Details
  2. AI agents for business units
    • AML and anti-fraud
    • Analytics agents
    • Documents and knowledge
    • KPIs and operations
    • Projects, tasks and time tracking
    • ERP agents
    • CRM and relationship managers
    Details
  3. Control and audit
    • Model governance
    Details
  4. Platform inside the perimeter
    • Agent orchestration
    • Sovereign AI infrastructure
    • Custom applications with AI
    Details
02Expertise

Technologies and capabilities

DFT projects combine several of these capabilities depending on the bank’s task.

  1. 001

    Digital twins and simulation

    We model customers, the credit pipeline, transactions and the bank’s IT estate, and run scenarios and back-tests on historical data against those models.

    • Synthetic data
    • Back-testing
    • Process mining
    • Infrastructure as code
  2. 002

    AI agents and language models

    We develop agents that answer with a citation to the source, run plain-language queries against the DWH and work with documents, Jira, CRM and ERP.

    • Model Context Protocol
    • Vector search
    • Text-to-SQL
    • Document processing
    • Jira / CRM / ERP
  3. 003

    Risk models and AML analytics

    We build graph models of linked accounts, run challenger models in shadow mode and monitor model drift.

    • Graph analytics
    • Gini / AUC
    • Shadow scoring
    • Drift monitoring
  4. 004

    Private AI infrastructure

    We deploy open models on the bank’s GPUs for inference, fine-tuning and federated learning, in which raw data is not transferred between sites.

    • NVIDIA GPUs
    • vLLM
    • Hugging Face
    • NVIDIA FLARE
    • Air-gapped
  5. 005

    Release testing

    We test releases in a copy of the production environment: agents walk through customer journeys, and load and chaos tests find the breaking point.

    • Environment twin
    • Testing agents
    • Load testing
    • Chaos testing
  6. 006

    Enterprise applications

    We develop PM and ERP applications around the bank’s processes with built-in agents and integrate them through APIs without changing the core of existing systems.

    • ERP integration
    • Jira API
    • Approval workflows
    • AD / SSO
  7. 007

    Regulatory requirements

    We design solutions in line with the NBU Discussion Paper of 24.03.2026, NBU Resolution No. 65, DORA and the EU AI Act, including the audit trail, validation and exit plan.

    • NBU
    • DORA
    • EU AI Act
    • Audit trail
03How we work

Project stages

Work with a bank starts with a diagnostic session, followed by a pilot on one use case.

Learn more
  1. 01Diagnostic session
  2. 02Pilot
  3. 03Roll-out
  4. 04Support and scaling

How we account for NBU, EU AI Act and DORA requirements »

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pilot project.

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