Banking & Capital Markets

The data layer that runsbanking operations

Your core banking system is not the problem. The problem is that nothing downstream of it agrees — five warehouses, three definitions of a customer, and a regulator who wants lineage you cannot produce. We fix the layer in between.

200+
Migrations delivered
Zero data loss tolerance
12 wks
Typical Teradata exit
Not 24 months
35%
Average cloud cost reduction
Measured post-migration
On-prem
Deployment available
Data never leaves your perimeter
The architecture

One objective in.Your whole estate, moving.

The governed layer sits at the centre of your operations. It reads every signal across Core banking systems, KYC identity data, Transaction streams and the rest of your estate, and closes every loop back to your business and regulatory goals.

Core bankingsystems
KYC identitydata
Transactionstreams
Fraudsignals
Loan originationdata
Regulatory changefeeds
Risk creditmodels
Live

Banking Governed Data Layer

IntelliBooks · Platform agnostic · Your cloud · On-prem capable

Ingestion & CDC
Change data capture from core, cards and channels into the lakehouse
Governed models
One conformed customer, product and ledger — dbt-tested, versioned
Agent registry
28 MCP servers, activated per process with per-user OAuth
Orchestration
Airflow and dbt with retries, backfills and deterministic fallbacks
Lineage & control
Column-level lineage in Neo4j, evidencing every regulatory figure
Human in the loop
Writes, spend and destructive actions route to a named approver
Snowflake · Databricks · Redshift · BigQuery · Synapse · Iceberg — and the core you already run
Any warehouse · Any cloud · Any orchestrator · Bring or build agents
Customeronboarding
Creditdecisions
Fraudalerts
Compliancereports
Riskassessments
Regulatorysubmissions
Audittrails
What does your organisation actually need?

The right question changes the answer.

Most banking teams have modernised in pockets. We start with why those pockets never joined up, and what it takes to run the whole estate on one governed layer.

Customer data is created in the core, in cards, in onboarding and in the CRM — systems never designed to agree. How long does it take to answer one simple question about one customer?


One conformed customer, product and ledger model, with the reconciliation logic written out and signed off by your team rather than buried in a pipeline. The answer stops depending on which system was queried.

Regulatory reporting draws on dozens of upstream sources. If a single figure were challenged, how confidently could it be traced back to source?


Lineage is captured as pipelines run, not reconstructed afterwards, so every reported figure has a queryable path back to its source system. The audit response becomes a query rather than a project.

Most banks still carry workloads on a warehouse that predates the cloud strategy. What does leaving it in place through another renewal cycle actually cost?


Agents survey the estate before anyone commits budget — every table, view and procedure mapped, dependencies graphed, each object scored for conversion difficulty. You get a costed picture of the real exit, not an estimate.

When reporting runs overnight, the business decides on yesterday's position. Where is that lag quietly costing you?


Batch logic is translated to streaming rather than rebuilt, and both run in parallel until outputs reconcile. Cutover happens on evidence, with rollback available throughout.

From objective to outcome

This is how the work actually runs.

01

Your systems stay. We fix the layer between them.

Your core banking platform, your card and payment rails, your KYC registry, your AML system, your reporting stack. Connect what you have. Nothing migrates off its system of record. We are not a core replacement.

Zero rip-and-replace
02

State the business outcome. We return the plan.

Not a project brief. An outcome. "Onboard a customer in hours, not three weeks." "Monitor AML continuously across every tier-1 account." "Cut warehouse spend by a third without losing a report." We read the live estate and return a ranked plan by risk, dependency and regulatory exposure.

Outcome-first scoping
03

The right agents activate, inside limits you set.

Customer matching, KYC data refresh, transaction enrichment, fraud signal correlation, credit data assembly, regulatory aggregation. Autonomy is set per process: assistive for credit-adjacent work, delegated for KYC refresh, autonomous for reconciliation.

Staged autonomy, earned not assumed
04

Customers get onboarded. Reports reconcile. Auditors get answers.

Every action carries the query it ran and the identity it ran as, and every reported figure traces to its source. Explainable at the moment it happened, to your team, your auditor or your regulator.

Explainable at execution
Coverage

We map to how you already run.

Tell us which of these hurts most and we start there — not with a platform rollout.

Onboarding & KYC

Identity and screening data unified so verification runs on current records, not overnight extracts.

AML & sanctions

Transaction and counterparty signals joined into one monitoring layer with alert lineage intact.

Fraud operations

Behavioural, device and transaction signals correlated to suppress false positives with evidence.

Credit & underwriting

Income, asset and bureau data conformed so credit decisions are reproducible and explainable.

Loan origination

Handoffs across the credit lifecycle instrumented, so where applications stall becomes visible.

Loan servicing

Modifications, hardship and collections data modelled for policy-consistent servicing.

Regulatory reporting

Basel III/IV and BCBS 239 assembled from primary data with provenance attached.

Compliance monitoring

Continuous checks against policy rather than quarterly sampling exercises.

Treasury & liquidity

Position and cash-flow data consolidated into a daily decision view.

Risk aggregation

Market, credit and counterparty exposures rolled up with drill-down to source.

Reconciliation

Breaks and exceptions surfaced with root cause rather than as a nightly report.

Customer 360

One conformed customer across retail, SMB, wealth and cards — finally agreed.

The question you are already asking

Your data. Your platform. Your call.

It runs in your cloud

Deployed inside your own account and VPC, or fully on-premises where residency requires it. Your data does not leave your perimeter, and no proprietary information trains anyone's model.

Governed at every step

Every agent action is logged with its query and its identity. Per-user OAuth means an agent inherits the permissions of whoever it acts for — never a shared service account.

You keep what we build

The models, pipelines, lineage and agent definitions are yours. No proprietary runtime holds them hostage. If you end the engagement, the platform keeps working.

Any platform, any model

Snowflake, Databricks, Redshift, BigQuery, Synapse or open Iceberg. Model routing is yours to configure. We are a consultancy, not a platform vendor with a lock-in incentive.

Basel III / IVReporting delivered
BCBS 239Lineage evidenced
ISO 27001Aligned
SOC 2Aligned
GDPRReady architecture
On-premisesDeploy option
Works with your stack
SnowflakeDatabricksAWS RedshiftGoogle BigQueryAzure SynapseApache IcebergdbtApache AirflowApache KafkaNeo4jTrinoHL7 / FHIR

If you are thinking it, it is answered here.

No. The core stays exactly where it is. We work on the data layer downstream of it — the warehouses, marts, pipelines and reporting that currently disagree with each other. Nothing we do requires touching the system of record.
Yes. The full stack deploys inside your own infrastructure, which is normally what makes core banking data work possible at all. Nothing is sent to a third-party service during the migration.
Row-level and aggregate validation on every object, run automatically and reported per object. Source and target run in parallel until they reconcile, and rollback stays available at every wave rather than only at the end.
It gets converted and validated object by object. QUALIFY becomes window functions, SAMPLE becomes TABLESAMPLE, temporal tables become SCD Type 2, MULTISET and SET tables are handled explicitly. Every conversion produces a diff report for review.
Both, deliberately split. Agents handle volume: schema mapping, dialect conversion, validation, reconciliation across thousands of objects. Certified engineers own architecture, conflict resolution and sign-off. Anyone claiming agents do all of it has not migrated a bank.
A two-to-four week assessment that audits the current estate, defines the target architecture and produces a costed roadmap. You own the output whether or not you continue with us.

Set the objective. We will scope it honestly.

Bring us the estate as it actually is, deadlines included. Two to four weeks later you have a costed roadmap you own — whether or not you continue with us.