Technical delivery across trading and risk systems.
Engineering for the platforms and integrations that trading operations depend on every day.
Openlink Endur
Full implementation and operations support for Endur (Trading & Risk) — from product modelling through to production-ready stabilisation.
Endur Engineering in detail →- — Trade and risk workflows, master data, product and deal modelling
- — Extensions: AVS/JVS development, reports, services, performance analysis
- — Upgrade and release readiness: impact analysis, regression, cutover, hypercare
- — Operations: incident analysis, batch monitoring, stabilisation and runbooks
Triple A Portfolio Management
Portfolio management, analytics and valuation — engineering and integration for end-to-end data flows between Triple A and surrounding systems.
- — Portfolio structures, instruments, curves and valuation logic
- — Analytics and valuation processes: configuration, error analysis, reconciliation
- — Data quality: validation, plausibility checks and exception processes
- — Integration to market data, reference data and reporting systems
Integrations & Data Flows
Interface engineering from design to operational handover — production-ready, with error handling and full documentation.
Integrations in detail →- — API design (REST/SOAP), messaging (Kafka, MQ, AMQP), batch/file pipelines
- — ETL/ELT pipelines for settlement, risk data and market data
- — Error handling, retry logic, idempotency and auditability
- — End-to-end monitoring, alerting and operational handover with runbooks
Cloud & Modernisation
Cloud connectivity and modernisation for ETRM environments — pragmatic, without rip-and-replace dogmatism, with attention to operational costs and security.
- — Hybrid integration: on-premise ETRM with cloud infrastructure (Azure, AWS)
- — Landing zones, network baselines and security configuration
- — CI/CD for integration and data pipelines
- — Cost and runtime transparency for batch/compute workloads
Data & Architecture
Data quality, architecture advisory and interface logic for ETRM environments — grounded in production system reality, not theoretical target states.
- — Data quality concepts: validation, plausibility checks, exception processes
- — Mapping and transformation for complex ETRM data structures
- — Target architecture reviews: current-state analysis, weaknesses, modernisation paths
- — Reporting interfaces: data extraction, aggregation, consistency checks
Typical engagement scenarios
Kiacon is typically brought in when a concrete trigger requires specialist depth.
Upgrade and release
Upcoming Endur upgrade with accumulated custom code — no clear impact overview, insufficient test coverage for the release window.
Unstable operational processes
EOD, batch or integration chains that fail intermittently or become labour-intensive after releases — without a clear error structure.
Data and valuation processes
Triple A valuations, curves or data flows that are not technically or functionally traceable and generate manual correction loops.
Integration reality vs. requirements
Interfaces that work formally but are not robust enough for new requirements, system changes or reliable production operations.
New products and markets
New trading segments, products or booking logic that cannot be cleanly represented in the existing ETRM configuration.
Missing end-to-end ownership
Processes that span system, team and data boundaries without anyone overseeing and owning the complete chain.
AI Integration
We integrate AI components selectively into ETRM processes — where a measurable operational contribution is realistic. No hype, no broad promises, no AI for AI's sake.
Anomaly Detection in Settlement
Automatic detection of unusual deviations in trades, positions and settlement data — before they flow into downstream systems.
Data Quality for Market Data
AI-assisted plausibility checks on curves and price series, before they enter valuation models and risk systems.
Intelligent Operational Monitoring
Automatic analysis of batch logs and system events — critical patterns identified early, before they become incidents.
Guardrails, data boundaries, logging and prompt/response controls are part of every AI integration — not optional extras.
Frequently Asked Questions
Do you offer architecture-only reviews?
Do you implement, or only advise?
How do you work alongside internal teams?
Do you support vendor and release management?
Do you handle data migrations?
What deliverables are typical?
Discuss a project.
kontakt@kiacon.de — we respond to concrete enquiries.