Agentic AI that monitors,
reconciles, understands and
remediates — end to end.

One platform, seven modules. The full reconciliation and data-quality lifecycle, from break detection to resolution, at the speed of AI. With traceability built in.
Elevating reporting quality through automation, not headcount.

From Detection to Resolution.

Traditional QA platforms detect what's wrong and hand the fix back to you. Gentek runs the full lifecycle: detect and reconcile deeper, then resolve and re-report the correction autonomously.
Adopt the whole platform, or start where the pain is.

Module 01 · AI + ML automated data mapping

Integrate

AI + ML mapping. Integrate fast, integrate right — from day one.

Schema mapping · AI-suggested

75–100%50–75%

Source schema

trade_date

cpty_lei

notional_amt

venue_mic

Destination

ReportingTimestamp

Counterparty1

Notional

TradingVenue

AI + ML mapping engine learns your source data and proposes the right field mappings automatically: a modern alternative to months of manual spec work.

Fast on day one: stand up a working integration in a fraction of the usual time, then keep adapting as sources and rules change.

Correct by design: models flag ambiguities and edge cases for review, so mappings are accurate, not just quick.

Sits alongside your existing infrastructure — no rip-and-replace — and ingests native formats (CSV, XML, ISO 20022, Parquet, FpML).

Module 02 · Regulatory context, as code

Understand

Every decision fully traceable to the regulation.

Horizon scan · regulatory change

6 changes detectedNext hard date · T‑81d

202620272028

EU · ESMA

UK · FCA

US · CFTC/SEC

APAC · ASIC/HKMA

Hard dateConsultationDirectional

A curated regulatory knowledge base: the documentation, citations and context that ground every consequential decision.

Continuous horizon scanning keeps the knowledge layer current as rules evolve.

Two audiences, one layer: it serves the AI agents and the Reg Ops/Compliance/First-line teams alike.

Made explicit, citable and queryable not hidden inside the platform.

Module 03 · INETLLIGENT DATA QUALITY ASSURANCE

Detect

More than field level testing. Data Quality that defends itself.

Assurance & compliance engine

Inputs

SubmissionsEndpoints reportsReference data

Detect

Field, record & report-level checks

NL-authored rulesDQEF indicatorsTraceable to source & lawAnomaly detection

Signals

Pre / post quality assuranceEarly-warningLogical validations

Runs pre and post-submission, catching issues before they reach the regulator and surfacing early-warning signals after.

An AI-defined, flexible validation framework that adapts as regulations and data evolve, not a brittle, hard-coded engine you wait on a vendor to update.

Coverage across completeness, validity, consistency and logical coherence, at field, trade and cross-field level, plus DQEF supervisory indicators most platforms don't reach.

Every check is explainable and traceable to its regulatory source, so flexibility never costs you auditability.

Don't just test against a fixed rulebook, create validation rules in plain Natural Language (NL), and AI turns each one into an executable validator. No coding, no vendor change requests.

Module 04 · PAIR & MATCH, SOURCE TO ENDPOINT

Reconcile

AI driven Pairing, Matching and Reconcilition engine. with the automated corresponding remediations

Reconciliation · source ↔ TR/ARM

94.6%Recon rate

695Open breaks

12,163Reconciled

Source100%

Eligible78%

Submitted76%

Paired70%

Reconciled66%

Pair-side reconciliation against counterparty positions where it applies with breaks surfaced at the population level, not just within your own books.

Hybrid by design: deterministic logic clears the 80–90% case; AI fuzzy matching handles the long tail others leave as unmatched exceptions.

Every match decision is transparent, configurable and auditable.

Consolidated daily reconciliation between source data and every Trade Repository and ARM you report to.

Module 05 · AGENTIC EXCEPTION RESOLUTION WITH HITL

Resolve

Where everyone else stops.
Exceptions identified, understood, root-caused, fixed and communicated. Autonomously. In seconds.

Autonomous exception resolution

Exception · UTI mismatch · TXN-8842Autonomous

Triaged & classifiedClassification agent
96%
Root cause identifiedDiagnosis agent
mapping rule
Correction proposedResolution agent
ready
Human sign-offHuman-in-the-loop
checkpoint
Re-submitted to TR / ARMResolution agent
resolved

Every step explained & logged to the audit trail

A network of agentic workflows that resolves exceptions autonomously.

Specialised agents work each break and reason from the regulation, like a senior analyst, not pattern-matching.

Agents, plugged into your reg stack, trace the exact root cause in your own data. No guesswork.

High-confidence breaks resolve end-to-end in seconds. Anything ambiguous goes to a human, with a confidence score.

Agents get smarter with every break. Already ~85% of the industry's exception types.

Module 06 · BACK REPORTING

Correct

Cancel what was wrong. Re-report what is right.

Back-reporting · CANC / NEWT queue

Exception	Action	IRIS	Status
EX-9921 · Duplicate	CANC	99%	Ready
EX-9922 · Wrong UPI	CANC+NEWT	96%	Ready
EX-9924 · LEI mis-key	CANC+NEWT	99%	Approved
EX-9925 · Below threshold	CANC	94%	Ready

Back-reporting automation for all four MiFID II/MiFIR flows — CANC and NEWT generated from gold-source data.

Smart Correction collapses multiple errors on a transaction into the right sequence of actions.

E&O thresholds monitored and NCA notification handled where required.

Audit pack assembled automatically — automated where safe, governed where it matters.

Module 07 · AI-Enabled people for bau & remediations

Operate

A managed service, force-multiplued by agents AI, not people instead of platform.

Operations · BAU & remediation

PractitionersEx Tier-1 Reg OpsEx TR / ARM operatorsEx Big 4 RegTech

×

Agentic platformDetect agentsReconcile agentsResolve agents

Embedded in your team. BAU runs & remediation surges — more done than humans or agents alone.

Where others offer an outsourced team running their tool, our practitioners run the agentic platform with you — expert humans plus AI, getting more done than either alone.

Not generic staff augmentation: deep regulatory expertise, former Tier-1 bank Reg Ops, former TR/ARM operators, former Big 4 RegTech.

For the moments that call for more than a platform: reconciliation surges around EMIR REFIT phasing, urgent regulator requests, back-reporting cut-overs.

Fix today's issues and prevent tomorrow's without the classic consulting trap of leaving a documentation pile behind.

Why we are different.

Most platforms detect the problem and hand it back. We are built — people, AI and a proprietary framework — to take regulated operations all the way to resolved.

the pedigree

Practitioner depth

We have built Data, AI and Enterprise solutions powering the largest institutions across some of the most regulated industries.

AI-native

Built-in AI, not bolt-on

AI sits at the core of the platform, not retro-fitted around a legacy engine. It's how we map, validate and adapt at speed.

The framework

AI-driven resolution

A proprietary agentic framework that decides at scale, taking exceptions from raised to resolved under human control. The part everyone else leaves to people.

Plug transaction reporting
into your AI assistant.

Our MCP connectors bring Gentek's reporting tools into the agentic harness your teams already use to check reference data and navigate cross-field validation across regulatory regimes, right inside the assistant.

Claude

OpenAI / ChatGPT

Microsoft Copilot

Cursor

+ any MCP-compatible client

Explore the Gentek MCP Server

Gentek MCP · connected

Is this LEI eligible under EMIR & MiFIR?

› reference_data.lookup(LEI)

LEI · activeEMIR + MiFIR in scope

Validate notional vs. price across both regimes.

› cross_field.validate(EMIR, MiFIR)

EMIR · Notional > 0Pass

MiFIR · Price × QtyReview

ISDA selected Gentek to build
the DRR Traceability Tool.

A milestone for open, auditable digital regulatory reporting providing end-to-end visibility from regulatory text to live reporting code.

01

Trace the origin

Link every DRR coding decision back to the underlying regulatory requirement with full historical context from the first version.

02

Track the changes

Understand what changed, when it changed, and why, including the working-group decisions that drove each update.

03

Manage the impact

Forward-looking change management lets firms assess the effect of regulatory amendments before they are applied.

Traceability is a foundational requirement for scalable, trusted digital regulatory reporting. Gentek AI demonstrated strong alignment with ISDA's vision for an open, auditable and AI-driven traceability framework that links regulatory text, working-group decisions and DRR code in a transparent and sustainable fashion.

David Shone

Senior Director, Data & Digital Solutions — ISDA

"

From data to decision, at the speed of AI.

See the reconciliation and data-quality lifecycle run against your own reporting.

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Agentic AI that monitors, reconciles, understands and remediates — end to end.