Financial Operations Intelligence

gaigenticOS

An AI operating system for financial institutions

An on-premises AI platform that reads a bank's own databases and regulatory environment, then continuously surfaces what's going well, what's going badly, and where to improve — every finding cited and auditable.

gaigenticOS
Morning briefing

Chief Risk Officer

Headline read-out

Capital and liquidity hold, but the AML alert backlog is now critical and CET1 is drifting toward buffer. Two items need a decision today.

Engine live brain v4.2.1 mapping v1747 findings · 1,204 concepts
What's going badly
AML alert backlog
CRITICAL
312 open+18%

Queue breaching SLA; investigator capacity exceeded for 6 days.

fct_aml_alertsEBA6AMLD
CET1 ratio drift
HIGH
13.8%0.4pp

Approaching internal buffer; RWA inflation on the corporate book.

Basel IIIfct_capitalEBA
What's going well
LCR within bounds
LOW
142%stable

High-quality liquid assets comfortably above the 100% floor.

Basel IIIfct_liquidity
NPL ratio improving
LOW
3.1%0.3pp

Cured exposures outpacing new defaults two quarters running.

fct_loansEBA
Where we can improve
Model validation lag
MEDIUM
4 overdue+1

IRB recalibration backlog risks the annual-review window.

SR 11-7fct_models
11
Reasoning Agents
1B+
Rows Profiled
On-Prem
Single-Tenant Deploy
The problem

Financial institutions can't extract insight from their own data without long, expensive consulting projects — and the industry has no product that reads a bank's data in its own context without a requirements phase.

Who it's for

Chief Risk Officers, CFOs, Heads of Compliance, and boards at mid-to-large financial institutions across the EU, UK, and Middle East, plus their audit and regulatory teams.

The full picture

Most banks are stuck in 6–18 month implementation projects that produce requirement docs and slide decks but no working system — meanwhile the answers already sit in their data. gaigenticOS deploys single-tenant inside the institution, automatically discovers which lines of business it runs by profiling database schemas at billion-row scale, and maps them to a deep regulatory knowledge base anchored on FIBO, Basel, and EU/UK/ME standards. A continuous five-stage pipeline turns live data into role-specific intelligence briefings for the CRO, CFO, and Head of Compliance. Every finding links back to the exact rows, regulatory passages, and ontology concepts behind it, and every internal decision emits to an append-only, hash-chained audit ledger that auditors can replay byte-for-byte.

How it works

From input to audit trail.

1

Install

One-command on-premises install — pick your model backend and air-gap mode.

2

Discover

Connects to the bank database, introspects schemas, and proposes metric-to-table mappings for review.

3

Analyze

A continuous pipeline resolves metrics, runs detections, and streams findings to role briefings.

4

Act

Operators drill to evidence, add panels in plain English, and export — every action audited.

Capabilities

What it does.

Schema Auto-Discovery

Introspects bank databases at billion-row scale and recognizes business lines without manual mapping.

Role-Based Briefings

Generates a morning intelligence briefing per role — CRO, CFO, Compliance — grouped by severity.

Citation-Grounded

Every finding links back to source data rows, regulatory passages, and mapped ontology concepts.

Continuous Analysis

A five-stage pipeline streams new findings in real time against thresholds and anomaly detection.

Knowledge Constellation

Maps live signals to FIBO, Basel, and ECB/EBA standards in an interactive, drill-down graph.

Audit & Replay

An append-only, hash-chained ledger lets auditors replay any decision byte-for-byte.

See gaigenticOS in action

Built for chief risk officers. Book a walkthrough with our team.