01
AML investigations
From alert to defensible case file in one workspace.
Open
Alert → related entities → transaction history → evidence → supervisor review.
Financial Intelligence Operating System
Turn fragmented financial data into coordinated action.
Solomon connects institutional systems into a live financial ontology and gives teams a private AI layer to investigate, explain, and act.
- Private AI
- Auditable
- On-prem or VPC
- Real-time context
Synthetic data. Illustration of the Solomon ontology — not a real institution.
Private AIOntologyInvestigationsOn-prem or VPCAuditableReal-time contextHuman approvalData lineagePrivate AIOntologyInvestigationsOn-prem or VPCAuditableReal-time contextHuman approvalData lineage
Featured
See all02
Entity intelligence
One answer to “who are we actually dealing with?”
Open
Search → resolved entity → relationships, documents, and history with provenance.
03
Customer 360
Every product, account, and interaction in one governed view.
Open
Customer → accounts and wallets → devices and channels → open items.
04
Transaction monitoring
Context-rich review instead of queue-clearing.
Open
Signal → counterparties → pattern across accounts → disposition with rationale.
05
Compliance operations
Screening, review, and reporting with a complete trail.
Open
Watchlist hit → identity check → decision → auditable report.
06
Financial crime investigations
Networks surfaced, not just individual accounts.
Open
Seed entity → graph expansion → chain of relationships → coordinated case.
07
Management intelligence
Questions answered from governed data, with citations.
Open
Question → private AI → cited answer → exportable summary.
08
Workflow automation
Repetitive operational steps executed under policy.
Open
Trigger → proposed action → human approval → recorded execution.
Our software
- A live model of customers, accounts, companies, wallets, devices, and transactions — with relationships that carry provenance.Deterministic resolution merges records only on hard identifiers; everything less certain becomes a reviewable proposal./0.1Ontology
- An AI layer that answers inside your perimeter, cites its sources, and respects each user’s permissions.Every claim links to the record behind it. No citation, no answer./0.2Private AI
- Signals become structured investigations with evidence, timelines, and supervisor review.Alert triage, relationship tracing, and case files that stand up to audit./0.3Investigations
- Findings turn into assigned tasks, approvals, and reports — recorded end to end.Every consequential action carries who, when, and on what authority./0.4Workflows
- On-premises, private cloud, or your VPC. Customer data does not leave the deployment.Same images, same migrations, different configuration — from pilot to production./0.5Deployment
How Solomon works
Connect Model Reason Act
- 01Connect
- 02Model
- 03Reason
- 04Act
The institutional problem
Your institution does not have a data problem. It has a decision gap.
Every system below already holds part of the answer. The gap is between them: an analyst opens seven tools, re-keys the same identifiers, and reconstructs context by hand before a single decision can be made.
- Core Banking
- CRM
- KYC
- Transaction Monitoring
- Case Management
- Data Warehouse
- Internal Workflows
Solomon · Live ontology
Resolved · Governed · Cited
CustomerAccountCompanyWalletDeviceTransactionAlertCase
Solomon reads from these systems and resolves them into one live ontology — so the context an investigation needs already exists before anyone asks for it.
How Solomon works
One operating layer, four moves.
01
Connect
Connect existing institutional systems without replacing core infrastructure.
02
Model
Transform fragmented records into a live ontology of financial entities, relationships, events, and actions.
03
Reason
Give authorized teams a private AI layer that understands institutional context, permissions, and data lineage.
04
Act
Turn findings into investigations, workflows, decisions, reports, and auditable operational actions.
How Solomon works
One operating layer, four moves.
01
Connect
Connect existing institutional systems without replacing core infrastructure.
02
Model
Transform fragmented records into a live ontology of financial entities, relationships, events, and actions.
03
Reason
Give authorized teams a private AI layer that understands institutional context, permissions, and data lineage.
04
Act
Turn findings into investigations, workflows, decisions, reports, and auditable operational actions.
An investigation, from signal to case.
This is a working fragment of the Solomon workspace running on synthetic data. Select entities, run the private AI query, and open a case — the way an analyst would.
Loading workspace…
Deployment & integration
Runs where your regulator expects it to.
Solomon deploys inside your perimeter and connects to existing systems through read-only, outbound-only integrations. Nothing connects in.
Your data center, your identity provider, your encryption keys, your backup policy.
- Air-gap friendly
- Your KMS and HSM
- Your observability stack
API & event integration
Batch files, database reads, REST, and event streams — read-only by default.
Role-based access
Permissions enforced server-side by the service that owns the data.
Audit logs
Append-only record of every consequential action and every AI tool call.
Data lineage
Every attribute records which source produced it and when it arrived.
Model governance
Which models run, on what data, with which tools — configured and logged.
Human approval
Consequential decisions require a person. The AI proposes; people dispose.
Designed for institutions that answer to regulators.
Solomon is built on the assumption that it will be examined — by your security team, your auditors, and your supervisor.
/01
Private deployment
Runs inside your perimeter. Customer data does not leave the deployment.
/02
Least-privilege access
Every permission decision is made server-side by the service that owns the data.
/03
Explainable outputs
AI answers cite the records they rest on. No citation, no answer.
/04
Auditability
Append-only audit of consequential actions, AI tool calls, and exports.
/05
Human approval
The AI cannot close a case, block an account, or export data on its own.
/06
Data lineage
Each attribute records its source, arrival time, and confidence.
/07
Model governance
Models, tools, and data scope are configured, versioned, and logged.
/08
Action governance
Operational actions run under policy, with approvals recorded end to end.
We publish what we can prove.
Solomon is an early-stage platform working with design partners. We do not publish customer names, testimonials, or performance numbers we cannot verify — on this page or anywhere else.
Pilot measure
Time from alert to completed investigation
Pilot measure
Systems consulted per case, before and after
Pilot measure
Share of AI answers accepted with citations intact
Pilot measure
Audit findings on access control and lineage
A pilot runs on synthetic or masked data first, inside your perimeter, with success criteria agreed in writing before it starts.
Connect your systems, model your operational reality, and give every authorized team the context required to act.