AI
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Focus area

AI for financial services.
Secure. Scalable. Practical.

Artificial intelligence, minus the hype.

Products, services, systems and consulting for organisations that want to deploy AI securely, scalably and with real business relevance.

We help financial service providers use AI strategically – from the first idea to a solution running in day-to-day operations.

Why AI in finance calls for particular expertise

Deploying AI in financial services takes more than technical innovation. What matters are regulatory requirements, robust data flows, decisions that can be traced, and a solution that fits into existing processes.

Hand on heart

Have you also wondered what AI actually is – and whether you really need it?

AI is a scientific discipline, not a product. What you buy is never “the AI”, but software that comes out of it: it reads, sorts, compares and spots anomalies – the legwork that steals valuable time from your teams. The software gets that work done in minutes rather than hours. Four misconceptions first:

And whether you need it comes down to a single question: do your people spend more time searching, retyping and looking things up than on applying their professional expertise?

Answers in full in the FAQ

Services

Products, services, systems and consulting – four ways into AI that pays off in day-to-day operations.

01

AI products

We build AI-based products for concrete use cases in finance – from assistive features to intelligent workflows. The aim is to take load off internal teams and improve the customer experience.

02

AI services

We support you with services around design, implementation, training and the ongoing development of your AI applications – accompanying you from the first idea to production operation.

03

AI systems

We design and integrate AI systems that fit into existing processes, data sources and platforms. The result: solutions that do not work in isolation, but add real value day to day.

04

AI consulting

We advise financial companies on strategy, use case definition, technology selection, governance and scaling. That way AI does not remain an experiment, but becomes a dependable part of your value creation.

Areas of application

Our solutions are used wherever statutory review obligations and financial security requirements have to be digitalised.

The Syngeon AI Principle

Four steps to a working solution.

  1. Analysing your requirements

    We identify the relevant use cases, requirements and potential.

  2. Domain expertise and technology from one source

    Together with our partner we develop a workable AI strategy for your company – one with the greatest benefit and realistic feasibility.

  3. Implementation

    We integrate and test the solution.

  4. Rollout and optimisation

    We support introduction, adoption and further development in live operation.

What sets us apart

We do not think of AI in isolation as a technology project, but as a strategic lever for financial companies. In doing so we combine domain knowledge, technical delivery and a clear understanding of trust, security and scalability.

Our aim is a solution that adds up professionally and holds up organisationally.

Solutions

Our products are in use wherever enquiries, knowledge, documents, AI governance and audits come together.

Conversational AI C-Talker

An AI assistant on your website that advises visitors in real time and resolves recurring enquiries before they reach your team.

  • C-Talker answers around the clock
  • More than 120 languages
  • Hands complex cases over with context
Request a demo

Agent-based knowledge search Knowledge Base

Searches internal procedures, regulatory circulars and key information documents agent-based and answers directly – including the exact place it found the answer.

  • Ask instead of search
  • Answers cite their source
  • The knowledge base stays current
Request a demo

Document processing ETL Pipeline

Reads bank statements, onboarding evidence and contracts automatically and loads the relevant data into your target systems, validated.

  • Document type is recognised
  • Fields are read out automatically
  • Straight into the target system
Request a demo

AI governance / EU AI Act enodAI

The central place where AI systems are inventoried, classified by risk, monitored and documented.

  • An inventory of the AI in use
  • Risk levels under the AI Act
  • Audit-ready evidence
Request a demo

Internal audit Revisions-Cockpit

Takes the time-consuming groundwork off your audit function, from ICT testing under DORA to the audit of the annual accounts – every piece of evidence pre-qualified and sourced.

  • Full testing instead of sampling
  • Upload each document once
  • Every decision reasoned
Request a demo

Conversational AI C-Talker

From now on, your website answers for itself.

C-Talker chat window: a question about transferring a securities portfolio in German and one about the required identity documents in English, each answered directly.
Example conversation

The same questions, every day, over and over – terms and conditions, verification procedures, the status of a portfolio transfer. C-Talker answers them straight away and in the visitor's language, connected to your systems and with a complete log. Your team keeps the cases that genuinely need attention.

  • Noticeably less workload Standard enquiries run automatically. Your team handles the complex cases.
  • Around the clock, 120+ languages C-Talker answers immediately, at night and at weekends, in your visitors' language – with no waiting, no form to fill in, no phone queue.
  • Intent, not keywords Evaluates what is meant, not what was typed – no decision tree, no menu.
  • Sees it through Guides visitors through application journeys and onboarding and triggers the necessary transactions in CRM, core banking and policy administration systems instead of only returning text.
  • Clean handover When it gets complex, C-Talker hands over to your team – with the full conversation.
  • Under your name Appears in your design and your tone of voice, not as somebody else's product.
  • Auditable and compliant Every conversation logged without gaps, operated in EU data centres with a DPA under Art. 28 GDPR, built around the transparency and documentation duties of the EU AI Act and GDPR.
  • German company with SLA Contractually assured availability and a counterpart under German law.
  • 120+ languages
  • Around the clock
  • Your design
  • EU data centres
  • Audit trail
  • SLA

Agent-based knowledge search Knowledge Base

Ask your question. In plain language.

The Knowledge Base answers a question about the deadline for filing a suspicious activity report and cites the internal procedure, page and section it came from.
Answer with its source

The knowledge is there – just not where you need it. Instead of clicking through PDFs, you ask the question in plain language: the AI picks the fitting source from the stored corpus itself and backs the answer with its origin.

  • Ask instead of search Ordinary language, no keywords, no filters, no search syntax.
  • Agent-based access The AI decides per question which source fits and searches the stored corpus deliberately.
  • Answers cite their source Every answer names document, page and section – verifiable, not merely plausible.
  • Everything in one place Internal procedures, regulatory circulars, key information documents and supervisory requirements searchable side by side.
  • Current, without upkeep The Knowledge Base absorbs new and amended documents into its index automatically.
  • For team and customers Usable internally by staff – or as the knowledge source behind C-Talker in customer contact, instead of maintaining content twice.
  • Auditable and operated in the EU Every request and every answer logged without gaps. EU data centres, DPA under Art. 28 GDPR – your documents stay in your hands.
  • Agent-based
  • Source per answer
  • Internal & customer-facing
  • Audit trail
  • EU data centres

Document processing ETL Pipeline

Read documents, understand them, process them automatically.

Processing list of the ETL Pipeline: a bank statement, a commercial register extract, annual accounts and a contract, each with type, status and the extracted fields.
Processing at a glance

Incoming documents are recognised automatically, the relevant data is read out and transferred into your system – validated, traceable and without manual entry. A dedicated, trainable extraction model works per document type; handover to core banking, accounting or your own systems runs via REST API.

  • No retyping What the document says ends up in the system without anyone copying it across.
  • A model per document type The document type is recognised automatically up front and the matching extraction model chosen for it. The models are configurable and trainable rather than one rigid schema – contracts, annual accounts and your own forms can be set up with your own fields.
  • Statements and vouchers Booking date, amount, payment reference, counter account and transaction reference are captured.
  • Onboarding evidence Commercial register extracts, shareholder lists and identity document data are taken over.
  • Validated, not guessed Extracted values are compared against your master data and checked for plausibility.
  • Doubtful cases to people Anything unclear goes to your team for review instead of being posted wrongly in silence.
  • Straight into the target system Core banking and accounting directly, e.pliance modules natively, your own systems via REST API.
  • Callable by AI agents classify_document, extract_fields, validate_extraction, train_document_type and load_to_system are available as MCP tools.
  • Throughput and evidence Optimised OCR and parallel processing, extraction within seconds, scales to high volumes. Separated tenants, encrypted storage, role-based access – and every extraction and handover fully documented.
  • Bank statements
  • KYC evidence
  • Contracts
  • Custom forms
  • REST API
  • MCP tools
  • Multi-tenant

AI governance / EU AI Act enodAI

The framework for running AI lawfully.

enodAI dashboard showing metrics on the AI agents in use and entry points for risk management, data governance and compliance.
Dashboard view

enodAI answers the questions that come up in every audit: which AI are we actually running, which risk level does it fall into, and where is the evidence for that? The inventory is compiled automatically, the risk scoring follows the requirements of the AI Act, and the classified systems stay under continuous monitoring.

  • An overview of your own AI A register of every AI system in use instead of scattered individual knowledge – compiled automatically, along with the models and components embedded in them.
  • A clear classification Every system lands in one of the four common risk levels of the AI Act, with a reasoned result. The scoring follows the requirements of the regulation and classifies along Annex III and the transparency and CE requirements.
  • Recommended actions Each risk level states what to do – from prohibition checks to transparency duties.
  • Evidence on demand The documents for an audit are already there rather than assembled beforehand.
  • Technical documentation Risk management plan, data provenance and technical records in an auditable form.
  • Transparency & explainability User notices, AI labelling and explainability reports as a duty met, not as rework.
  • Continuous monitoring Watches for bias, robustness and regulatory drift, with alerts.
  • Data governance & reporting CE conformity, data governance plus reporting and integration into existing processes.
  • Phased introduction Designed around the staggered AI Act deadlines running to 2028.
  • Four risk levels
  • Annex III
  • Risk scoring
  • Monitoring
  • Audit-ready
  • Deadlines to 2028

Internal audit Revisions-Cockpit

Still preparing your audits by hand?

Initial qualification of a submitted annual report: relevance, completeness, currency and consistency, each with a verbatim quote and page reference from the document.
Evidence with its source

An audit starts with searching today: which test questions from DORA, MaRisk and your own audit plan apply to this institution, which evidence is still missing, who supplies it. The Revisions-Cockpit tailors the audit scope to your institution, a connected evidence portal collects the documents and checks them on arrival – every qualification with its source, every decision with its trail. Your audit function decides.

  • Audit scope per institution Existing test catalogues are matched against the institution profile and each test point checked for applicability. Every exclusion stays reasoned, visible and open to override.
  • Full testing instead of sampling Where the testing procedure allows it, the entire available dataset is evaluated – every access right against the leavers list, say, instead of ten samples.
  • Each document only once Within an audit the same piece of evidence is obtained once and mapped to every test point that requires it.
  • Qualified on arrival Incoming evidence is checked for relevance, completeness, currency and consistency with what is already on file. Every result names the document, the page and the verbatim quote – verifiable rather than merely plausible.
  • Reconciliation across documents Documents are compared against one another, including where names are spelt differently and the match runs over a unique identifier. Contradictions surface that stay invisible in any single file.
  • Policy, regulation, process as lived Policies such as the ICT security policy are tested against the requirements of DORA and MaRisk and against your own process documents – with article and reference for every result. A gap also covers a contradiction between two internal documents and a requirement left without a measurable criterion.
  • Deadlines and cycles recalculated What the policy prescribes in time is computed against the evidence: a missed recertification cycle surfaces even where no document flags it as a breach.
  • A pre-assessment per test point Every test point comes with a pre-filled working paper: the evidence used, the central observation, a verdict on design and operating effectiveness, a proposed rating and remediation – split into immediate and structural. Every observation states how solid it is; where evidence is missing, it is named rather than papered over.
  • Sensitive evidence stays on site Documents the institution may not release digitally can be reviewed in a documented on-site inspection.
  • You keep the decision Every suggestion is reasoned and can be overridden with one click: accept, discard or set aside for your own review. Deadlines and escalation are set by the auditor, the audit opinion stays with your audit function – and every upload, every qualification and every discarded assessment is logged and traceable in the audit report.
  • Full testing
  • One upload, all test points
  • Source per result
  • DORA & MaRisk
  • Human in the loop
  • Audit trail

Platform & trust

All AI products presented here run on the Enterprise Intelligence Platform by e.pliance AG. This results in the following characteristics.

  • Complete audit trail Every request and response fully logged
  • AI Act & GDPR The platform is built around their transparency and documentation duties
  • Information security Information security management system modelled on ISO 27001
  • Operated in EU data centres DPA under Art. 28 GDPR
  • German public company as contracting party With agreed SLA
  • Multi-tenant capable Separate data storage per tenant

FAQ

Will AI replace our staff?

No. Our approach is scaling rather than cutting headcount: your teams deliver more quality and more business with the same people, because AI takes over the routine work. Decisions on substance stay with people (human in the loop), which for high-risk applications under Art. 14 of the AI Act is mandatory anyway.

How do we keep control over what the AI does?

Every solution works with a complete audit trail: each processing step is traceable and auditable. That makes full reviews possible instead of spot checks, and your business unit retains decision-making authority.

What does the EU AI Act mean for us on top of DORA and existing regulation?

The EU AI Act adds AI-specific obligations to existing requirements such as DORA – on risk classification, transparency and human oversight, among others. We assess which obligations apply to your particular use cases and how to meet them pragmatically.

How transparent are the costs of deploying AI?

We calculate effort and benefit before the project starts, including the ongoing usage costs of the AI models involved. That way you know before deciding what running a solution costs and what savings are realistic.

How do you make sure AI solutions work in regulated environments?

We pay attention to clean data flows, a traceable architecture, governance and an implementation geared to the requirements of regulated financial companies.

Who are your AI services aimed at?

Our services are aimed at banks, insurers, asset managers, fintechs and other financial service providers that want to deploy AI strategically and securely.

Do you only advise, or do you also implement?

We accompany you from consulting through design to technical implementation and integration. That way you gain both strategic clarity and a production-ready result.

Which AI use cases are particularly relevant in finance?

The most frequent requests concern customer service automation, document processing, knowledge assistance, analytical support and internal process optimisation.

Do you also develop bespoke AI products?

Yes. We develop tailor-made AI products and systems geared to your business processes, your system landscape and your objectives.

How does a project with you start?

It usually begins with an initial conversation in which we clarify objectives, requirements and possible use cases. Building on that, we recommend a sensible approach for analysis and implementation.

Contact

Are you ready for AI with substance? Let us find out together which AI potential genuinely makes sense in your financial company.

Make AI your competitive advantage.

e.g. which documents come in, what volume, which target system the data should reach

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