Two AI-supported compliance tools
Bring efficiency to financial-crime case resolution and reporting.
EyesClear works alongside your existing providers to reduce effort and cost without forcing a platform replacement.
Turn every alert into a decision-ready case.
EyesClear uses the data you hold and rapidly accesses all relevant external data that you don’t have. Assesses both, identifies the risks and drafts the narrative. Your analysts review, decide and sign off.
Your data and the AI never leave your perimeter — on-prem or private cloud.
Public-record enquiries go out with a name only — never a customer file.
Five free searches on the entities that matter to you · results in minutes
MONITORING
EC-4471
HIGHDraftedSCREENING
EC-4470
MEDDraftedKYC REVIEW · Powered by Investigations
EC-4469
LOWAuto-closedONBOARDING · Powered by Investigations
EC-4468
HIGHDraftedAUDIT
EC-4467
MEDIn review
Evidence assembled · entities resolved · narrative drafted
Awaiting the analyst’s signature
The Platform — proven in live banking environments
- 9
- years in continuous production
- 7
- banking clients live
- 5+
- markets in production
- 10,000
- transactions per second
Two tools one decision
Two separate tools that can work together
EyesClear provides two separate AI-supported tools for financial-crime compliance. TheEyesClear Platform runs on-premise or in the bank's private cloud for its own data and workflows. TheEyesClear Investigations tool operates in the cloud for sourced public-record research. They can work together, but each is available and usable separately.
On-premise or private cloud
EyesClear Platform
Brings your transactions, customer records, alerts and KYC into one place, assesses them, and prepares each case for a decision. Detection, case management and reporting on a single data fabric.
It runs on your own infrastructure, alongside the AML and sanctions systems you already have.
Cloud-based · Separate tool · New
EyesClear Investigations
Screens a company or a person against the public records and reports every finding with its data source. No confidential data is released outside of the bank.
It runs on its own, and feeds whatever case system you already use. Free to try for financial institutions and their regulators.
Each stands on its own. Together they are uniquely powerful to close alerts.
Decisions compliance can sign
How it works
One queue. Three clear steps. A signature at the end.
Everything that needs a decision — a monitoring alert, a screening hit, a KYC review, an onboarding breach, an audit finding — lands in one queue. EyesClear prepares the case. Your analyst signs it. The decision then flows back into your systems without re-keying.
- 1
Rules-based collection
Transactions, customer records and internal data — and, through EyesClear Investigations, the public records on the counterparty you hold nothing about. Gathered by rules you set, so every step is repeatable and auditable.
- 2
AI analysis
The AI summarises and triages that evidence, maps the entity network and drafts the narrative. The risk is visible at a glance.
- 3
Human decision
Your analyst reviews, decides and signs. Approved actions — account holds, information requests, customer outreach — go back to your systems, every one logged.
Value created
Lower cost per case
The evidence is assembled and the narrative drafted before an analyst opens the case.
Faster regulatory response
A new typology runs across the full history overnight, and every AI output traces back to source.
Less undetected financial crime
Analyst time moves from assembling evidence to judging it, across more of the book.
Effort comes out of every case — whether EyesClear runs the operation or works alongside what you already have.
Why EyesClear is different
Two AI architectures, each used where it belongs
Every vendor has AI narratives now. The question is which AI, running where. One architecture for the whole problem forces a compromise: keep everything inside the bank and you give up the frontier; send everything out and you export the bank’s data. EyesClear declines both — frontier models work the public record, private on-premise AI works the bank’s own data, and the two meet in one case file that an analyst signs.
Frontier models on the public record
Best-in-class reasoning on the half of the case you do not hold.
EyesClear Investigations works the open record with frontier commercial models, and reports every finding with the quote and the source it came from. What leaves is the name being screened and the search terms derived from it — never a customer file — and no provider trains on those queries or on the reports.
Private AI on the bank’s own data
AI value without data-export risk.
The Platform and every inference it makes run on the bank’s own infrastructure — on-premise or private cloud, behind a private LLM gateway. No customer data and no model inference goes to an external cloud or a third-party vendor.
Two architectures, one case file
The analyst never has to think about which AI did the work.
Internal evidence and public evidence arrive in the same case, assessed together and traceable to source on both sides. Whichever side the work came from, one analyst reviews it and one signature closes it. The split is an engineering decision about where evidence lives, not something the compliance team has to operate.
Nine years in production, at the current frontier
Current AI, on a system banks already run.
Seven banking clients across five or more markets, nine years in continuous production — and the AI inside it is the current generation, not a narrative feature added to a legacy engine. When a better model arrives it is swapped in and re-run against a fixed set of test cases with known-correct outcomes, so a change in behaviour is detected rather than assumed. The maker-checker control around it does not change.
Risk mitigated, control retained, effort removed — because the AI is chosen for where the evidence sits, not for where it is easiest to run.
Why EyesClear is different
Problems and answers
Four problems. Four answers.
Financial-crime compliance is one of the largest cost centres in any bank, and the pressure lands on the same team every time. Four problems drive it, and one platform answers each.
The problem
Never enough people for the volume
Alert volumes grow with the book and with every new typology. Headcount does not. The team absorbs it by spending longer on each case or by looking at fewer of them — and the research that sits in no system at all gets done by hand, one search at a time.
The answer
More of the book, by the same team
The evidence is assembled and the narrative drafted before an analyst opens the case — inside the bank and outside it alike. The counterparty research someone would otherwise do by hand comes back as a sourced report. Those hours return as coverage: more of the book reviewed, by the same people.
The problem
Incomplete evidence
Raising an alert is the easy part. The cost sits downstream: investigators wait on slow queries, then hand-write each SAR narrative in two to four hours. And on an incoming payment you hold everything on your own customer and nothing on the party who sent the money.
The answer
Both sides, in one case file
The AI assembles, analyses and drafts — working with the data you hold and through EyesClear Investigations, the public records you do not have. The analyst decides and signs off.
The problem
Audit readiness is a scramble
An examiner asks how a case was decided eighteen months ago. The answer is spread across a case system, an email thread and somebody’s memory. The web research behind it leaves no trace at all — nobody recorded what was searched, and the page the analyst read may not say the same thing today.
The answer
A file that is already examiner-ready
Evidence, case history and decisions are held centrally, with full audit trails and instant retrieval for any period. Every AI output traces back to source, and every public-record finding carries the quote and the date it came from — so the outside evidence is as defensible as the inside evidence. Maker-checker records who requested each change and who approved it.
The problem
Managers have no line of sight
Headline numbers arrive monthly, in a spreadsheet, detached from the cases behind them. By the time a backlog or a drift in quality is visible, it has been true for weeks. And nobody can see whether two analysts researched the same counterparty to the same depth.
The answer
A control plane over the operation
Headline numbers drill down to the cases behind them, live. External research runs as a repeatable step rather than as one analyst’s search habits, so what gets checked is the same across the team. A remediation run across the affected history is one action away, through the same maker-checker queue.
That work spans multiple workstreams, usually spread across multiple systems, each with its own data, queues and reports. See how EyesClear consolidates them →
One platform owns the outcome, and one signature closes it.
Four problems, four answers
In practice
What the analyst and the manager actually do
Seven steps, from the moment alert is created up to the case conclusion — same platform, same data, same maker-checker control.
- 01
The consolidated queue
Alerts from every source system land in one place. One queue instead of five logins.
- 02
The case, fully assembled
Everything the analyst needs is on one screen — including, through EyesClear Investigations, what the public records say about the counterparty you hold nothing on. The case starts from evidence, not from a search.
- 03
Capture, designed by your team
Compliance designs what a case captures, and the form goes live without a vendor change request.
- 04
The maker-checker process
The AI drafts. The analyst reviews, edits and signs. Nothing closes without that signature.
- 05
Straight to the filing
The resolved case flows into the regulatory report, fields already populated.
- 06
Remediation
New supervisory input arrives, and the relevant historical cases are re-reviewed through the same queue.
- 07
The manager’s control plane
Headline numbers drill down to the cases behind them. A remediation run is one action away.
A lookback in days, not months — through the same maker-checker queue.
The Platform in practice
Try it on a name you already know
Investigations is free for financial institutions and their regulators — five screenings to start, nothing to integrate. Or book a demo and we will run the Platform on your own scenarios.