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Financial Services Data Platform for Auditable, AI-Ready Pipelines

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Replace separate systems with a unified architecture

Fragmented data stacks and unclear pipelines slow every decision downstream. We bring ingestion, observability, governance, and AI enablement into a shared architecture built for regulated financial environments.

A man using a multi-monitor setup to analyze integrated financial data dashboards for strategic decision-making and compliance

How an integrated data platform transforms your business

Faster decisions with trusted data

Teams rely on the same governed data instead of waiting for numbers to be reconciled across separate systems. Reporting and analysis become more timely, consistent, and useful.
More efficient compliance operations

Built-in governance, lineage, and traceability make supporting evidence easier to access. Audit preparation and regulatory reporting require less manual effort.
Greater capacity for higher-value work

A shared data foundation reduces discrepancies between systems and the time spent resolving them. Teams can focus on analysis, exception handling, and strategic decisions.
A stronger foundation for AI and growth

Well-governed, accessible data supports AI, advanced analytics, and new data products. New use cases can be introduced without rebuilding the underlying architecture each time.

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Pipeline and AI observability in one platform

Monitor data quality and model behavior from the same interface, so risk teams aren’t reconciling alerts from two separate systems when something breaks upstream.

Proactive anomaly detection

Issues surface before they reach downstream compliance or risk processes, giving your team time to act rather than explain.

Natural-language querying with built-in governance

Compliance officers and risk managers query production data directly, with auditability enforced at the query layer, no SQL required and no governance bypassed.

Compliance monitoring mapped to financial services frameworks

Coverage is structured around the regulatory obligations your teams already report against, so audit evidence is a byproduct of normal operations, not a separate workstream.

Secure cross-institutional data collaboration

Enrich models and analytics with external data without moving raw records across institutional boundaries, keeping data residency and privacy controls intact.

Defined engagement stages with clear handoffs

Scope, outputs, and review points are agreed before build begins, so your data engineering team knows exactly what ships at each phase and when.

What our clients say

“A solution co-developed with Neontri has reduced the number of queries directed to the central system, resulting in lower infrastructure costs and customer service time.”

Piotr Durakiewicz

Team leader – departament of electronic banking applications

“The IT specialists they provided possessed the necessary experience and required competencies. We recommend Neontri as a trustworthy and reliable business partner.”

Wojciech Moraczewski

Senior Manager

“Neontri’s execution and deep understanding of corporate processes made our project remarkably smooth. Their extensive enterprise experience delivered impressive results from solution to implementation.”

Patryk Dąbrowski

Head of Software Development

“Neontri stood out with their commitment, technical competence, and understanding of KIR’s business needs.”

Robert Trętowski

Vice president

A glowing digital circuit grid representing data ingestion and pipeline orchestration

Unified ingestion and pipeline orchestration

Batch and streaming data from customer, transaction, risk and product sources land in a single governed data layer, designed to meet financial services SLAs and data volumes.

Abstract digital charts and blurred financial lights illustrating low-latency data processing

Low-latency data access for banking, trading, and payments

Serverless access patterns deliver the response times that payments processing, live trading workflows and real-time risk monitoring require. No infrastructure provisioning between your data and the teams who need it.

A business team collaborating during a financial analytics discussion

Self-service analytics for financial roles

Bankers, traders, underwriters, risk managers and compliance teams query governed data and receive auditable answers without opening a ticket to engineering. Every query and result is logged for audit purposes

Abstract glowing wave patterns illustrating artificial intelligence and machine learning workloads within a secure perimeter

AI and ML workloads within a governed security perimeter

Model training, inference and agentic AI workflows run inside the same access controls and audit trail as the rest of your data, with policy guardrails keeping AI within institutional and regulatory boundaries.

Automated data quality policy enforcement

Quality rules are defined once and applied continuously across every pipeline and data asset, catching issues before they propagate downstream.

Interconnected purple and blue digital pipelines illustrating machine-learning-based proactive anomaly detection

Proactive anomaly detection in production pipelines

ML-based detection surfaces statistical outliers, schema changes and volume anomalies before they reach downstream processes, giving teams signal early enough to act.

Partnerships and certifications

Get a clear view of your data gaps before they cost you

Fragmented pipelines create risk long before anyone notices. Map your current data estate and see what a unified architecture would fix.

BOOK A 30-MIN CALL

How Neontri delivers production-ready data platforms

An abstract network of interconnected pink and blue data nodes

Discovery and priority mapping

Regulatory boundaries, current architecture, and technical priorities are mapped early, so success is defined before any work begins.

Data platform assessment

Pipelines, governance, observability, and data quality are examined to see where weaknesses create the greatest downstream risk or operational friction.

Impact-based prioritization

Not every issue needs attention at once. Priorities are set by business impact and implementation complexity, showing what should come first and why.

Development and delivery planning

The work is organized into defined streams with owners, milestones, and deliverables. Any changes are handled explicitly rather than being absorbed into the project along the way.

Post-launch support

Ongoing coverage is planned ahead of go-live. Pipeline health checks, thresholds, and advisory needs are agreed in advance so responsibilities remain clear after deployment.

Build your financial services data platform with Neontri

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Richard Geerligs

CCO, EUROPE

richard.geerligs@neontri.com