Secure Data Orchestration Platforms.
Pipelines, lineage, and governance for sensitive data. Built for organisations where every movement of data is a compliance event.
Overview
Data orchestration is the connective tissue between systems of record, analytical stores, and downstream consumers.
XVICA builds the orchestration layer for organisations where every movement of data carries compliance weight: regulated financial groups, government, healthcare, and large enterprise estates. The work covers ingestion, transformation, lineage, quality, governance, and delivery, deployed on customer-owned warehouses and lakes so compute decisions and cost control stay where they belong.
Data has become a regulated input, no longer a byproduct.
Regulators increasingly treat data architecture as a control concern in its own right. BCBS 239 requires risk data aggregation and reporting to be timely, accurate, complete, and adaptable. SR 11-7 and SS1/23 put model inputs under scrutiny. UK GDPR Article 30 requires a current record of every processing activity. DORA requires demonstrable resilience of data dependencies. In healthcare, the NHS Data Security and Protection Toolkit and equivalent sectoral regimes impose the same standard.
The organisations that meet these obligations well have one thing in common: they treat data movement as engineered infrastructure (specified, versioned, tested, and observable) rather than a set of unattended scripts. Getting this right compresses examination effort, reduces incident blast radius, and removes a category of finding that rarely closes quickly.
What we build
The orchestration platform is deployed as a single system or as named components integrated into existing estates.
Ingestion and transformation
Batch, streaming, and change-data-capture pipelines with declarative transformation and versioned SQL or DataFrame logic.
Lineage and catalogue
Column-level lineage from source to consumer, paired with a governed catalogue that powers impact analysis and regulatory requests.
Privacy and tokenisation
Field-level tagging, tokenisation, pseudonymisation, and role-scoped masking with HSM-backed key management.
Quality and reconciliation
Declarative quality rules, automated reconciliation with upstream sources, and break workflows tied to the catalogue.
Warehouse-portable compute
Deployed on Snowflake, Databricks, BigQuery, Redshift, and Azure Synapse without lock-in; workload placement driven by policy.
Governance and access
Policy-as-code access controls, approval workflows for schema change, and entitlement review scoped to data products.
How we build data platforms
We build data platforms the way institutions build transaction platforms: specified, versioned, monitored, and independently auditable. Every pipeline is a product with an owner, a service level, and a documented chain of evidence.
Domain and contract design
Data domains are mapped to business owners; schemas become published contracts with deprecation policy. Downstream consumers depend on contracts, not incidental structure.
Engineered pipelines
Transformations are declarative, versioned, and tested. Every run emits structured lineage and quality telemetry captured in the catalogue.
Governance by default
Classification, access policy, and retention are specified alongside the pipeline. Sensitive fields are protected from ingestion forward, not retrofitted.
Operated under SLA
Data products are monitored against freshness, completeness, and quality SLOs. Incidents trigger documented response, not unattended retries.
Technical standards
Column-level lineage
Queryable from regulation to source system, not just at pipeline granularity.
Immutable event log
Every ingestion and transformation run is recorded and replayable.
Policy-as-code access
Access decisions expressed as version-controlled policy, not ticket-driven.
OpenLineage emission
Standards-based lineage for portability and tool interoperability.
SOC 2 and ISO 27001 aligned
Controls mapped to frameworks from specification, evidenced continuously.
FIPS 140-2 key material
HSM-backed encryption keys with documented rotation and recovery.
Where organisations deploy this
Three representative deployments. Scope varies by regulation, volume, and data sensitivity.
BCBS 239-aligned risk platform
A globally significant bank consolidated risk and finance data onto a governed orchestration layer with column-level lineage, automated reconciliation to source systems, and signed examination packs produced on demand. Month-end close time halved; examiner queries resolved the same day.
Federated healthcare data platform
A healthcare provider network built a FHIR-aligned orchestration layer across trust boundaries with patient-linked tokenisation, DCB0129/0160 clinical safety evidence, and audited data access. Research requests move through a governed pipeline rather than case-by-case exports.
Cross-cloud operational data
An industrial group unified operational data across AWS and Azure estates without consolidating to a single warehouse. Workload placement is policy-driven; lineage is continuous across regions; access is scoped to data products rather than underlying storage.
Operational discipline
Observability by default
Freshness, quality, and lineage signals in every pipeline.
Sensitive data protected
Tokenised at ingest, masked at consumption, keyed in the HSM.
Regulator-ready evidence
Lineage and controls produced on demand, signed at export.
Reversible change
Schema change, access policy, and pipeline logic are versioned and revertible.
Where regulated data lives
Financial Institutions
Risk, finance, and regulatory data platforms with full lineage for BCBS 239 and SR 11-7.
Read onEnterprise
Operational and analytical data platforms across multi-cloud and legacy estates.
Read onPublic Sector
Cross-agency data sharing under statutory gateways and data protection legislation.
Read onHealthcare
Clinical, research, and population-health data with FHIR-aligned interoperability.
Read onData orchestration platforms
The questions that come up most often during briefings.
What is data orchestration infrastructure, and who needs it?
It is the layer that moves, transforms, and governs data between systems of record, analytical stores, and downstream consumers. Organisations with cross-system compliance obligations, complex data lineage requirements, or sensitive data residency constraints benefit most.
How do you handle data lineage and provenance?
Every transformation emits structured lineage metadata captured in an immutable catalogue. Lineage is queryable from source column to downstream report, supporting both regulatory requests (SR 11-7, BCBS 239, GDPR Article 30) and internal incident investigation.
Do you build on top of existing warehouses and lakes?
Yes. We deploy on customer-owned Snowflake, Databricks, BigQuery, Redshift, and Azure Synapse estates. The orchestration layer is designed to be portable across compute backends so workload and cost decisions stay with the customer.
How are PII and regulated data protected in pipelines?
Sensitive fields are tagged at ingestion, tokenised or encrypted in flight, and masked per role at the consumption boundary. Key management runs through HSM-backed KMS with documented rotation and quorum-controlled recovery.
What level of governance controls do you include?
Policy-as-code access controls, approval workflows for schema changes, lineage-based impact analysis, and automated quality checks with alerting. Controls map to SOC 2, ISO 27001, and sectoral regimes as required.
Related reading: regulatory & compliance engines, integration fabrics, and financial institutions.
Governed data movement, engineered as infrastructure.
Request a confidential briefing to discuss your data orchestration requirements and regulatory obligations.
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