Trusted Agents for
Financial Services
Prometheux puts AI to work on your institution's own data and rules, where they already live: core banking, payments, trading, warehouses and files. Across front, middle and back office, from client growth to credit, fraud and reporting, teams, auditors and agents get the same answer every time, with the evidence behind it. People stay in control. No migration, no new store.
Proven in production
Plenty of Data.
Too Few Answers.
Every institution wants faster growth, tighter risk and lower cost from its data and AI. The data sits in silos across functions and decades of systems, and the logic that turns it into decisions sits in spreadsheets and people's heads.
Find Your Business
in the Menu
Familiar use cases across financial services, each running your own rules on data where it already lives. Start with one; the next reuses what it built.
Banking & Payments
Grow and protect retail and business banking, cards and payments.
Capital Markets & Wealth
Know positions, clients and exposure across desks, books and platforms.
Lending & Credit
Underwrite, price, monitor and explain credit consistently.
Finance & Operations
Close, report and run the back office with fewer manual steps.
The Questions Other
Tools Can't Answer
Payment Paths at Any Depth
Where did these funds go after the first hop, across which accounts and counterparties, and which accounts form connected groups? Recursive rules and graph algorithms run on the tables you already have, with no separate graph database.
One Client, Many Records
Which records across core banking, cards, CRM and leasing are the same client, and what is their total relationship? Every match cites its rule. See entity resolution.
Exposure That Propagates
If this counterparty defaults, which clients, facilities and portfolios are affected through guarantees and linked accounts, at any depth? Exposure is rolled up with recursion and aggregation.
Every Figure Traced to Its Row
Which source records, in which systems, produced this reported figure, and which control did it pass? See the Banca Sella case study.
Where the Return
Shows Up
The value comes from running the bank's own logic once, across every system, instead of rebuilding it by hand for each team, case and report. At Banca Sella a regulatory flow went from 5 hours to under a minute and the checks caught an anomaly of around €4bn. Another financial institution saves more than €9M a year, with critical reasoning tasks running over 250% faster.
Risk Seen Sooner
Rules run across every system on a schedule or when data changes, so exposures, breaches and suspicious links surface when the data does, not at month end.
Fewer, Better Alerts
Signals from several systems are combined before anything reaches an analyst, so each alert arrives with the reasons it fired and the evidence behind it.
Faster Reviews and KYC
Investigators and auditors start from the rule and source rows behind a result, instead of rebuilding the case across systems by hand.
Lower Running Cost
Logic written once serves every team and agent, runs on ordinary compute instead of repeated model calls, and needs no new data platform to load.
5 hours to under a minute at Banca Sella. €9M+ saved a year at a financial institution. The same rules, reused across every team.
One Rules Layer
Across the Institution
Typical financial-services platforms load your data into their own store and sell modules on top. Prometheux sits between your financial data and the people, tools and agents that act on it, and runs the rules where the data already lives.
Analytics
Dashboards, graph and BI
Integrations
Back into the databases behind core banking, CRM, finance and case tools
Agents
Assistants and agents, deterministic answers
Models
Define the ontology, read answers, and power analytics, integrations and agents
Your financial data
Core banking, payments, cards, CRM, ledger, risk and reporting data, connected in place. Nothing to migrate.
-
Financial Operations
- Customer eligibility, pricing, reconciliation, credit, controls and fraud signals on one set of rules
- Agents call deterministic rules over MCP and API, with the derivation behind every answer
- Results written back to the databases behind core banking, case management and reporting, on a schedule or when data changes
-
The Financial Rules Engine
- One model of clients, accounts, transactions and exposures across systems, instead of a copy per tool
- Recursion with aggregation and graph algorithms: payment paths at any depth, indicators rolled up per client
- Same input, same output, with lineage to the rules and source rows
-
Cloud Agnostic
- Run on your own servers, your cloud or Prometheux cloud, under your own controls
- Scale horizontally on clusters to every client and every transaction, with optional GPU acceleration
- 1-click deployment anywhere: EKS, AKS, GKE, Databricks Clusters, Snowpark Containers
-
Financial-Data Agnostic
- Read and write core banking, payments, ledger, CRM, risk and reporting data in any database, format and schema
- Connect warehouses, mainframe extracts, files and APIs across clouds and on-premises
- No new data store to migrate into and keep in sync
Same Layers.
Better Built.
Map a typical financial-services data or decision platform to Prometheux and the difference is where the work happens: in place, in rules you own, with an answer you can check.
5 Hours to
Under a Minute
Banca Sella runs Prometheux rules directly on its own databases. A regulatory flow that took 5 hours now runs in under a minute, and the checks caught an anomaly of around €4bn. The credit risk team uses the same engine to explain rating changes from each client's full history: in the words of its Head of Credit Risk, a system that can "process all the client's historical variables, and provide an intelligent, understandable explanation". Read the case study.
Owned by You
Product, policy and control logic lives in rules your team can read, review and version, not inside a vendor's modules.
Deterministic and Explained
The same data gives the same result, with the rules and source rows behind it, ready for audit, model risk review or a supervisor's question.
Built for Bank Scale
A financial institution measured a speed-up of over 250% on critical reasoning tasks over graphs with billions of edges. See high-performance engine.
On Your Infrastructure
Run on your own servers with Docker or Kubernetes, in your cloud, or inside Snowflake and Databricks. See on-premises.
Write a control once. Run it on every client, every day. Answer the supervisor with the rule and the row.
One Flow.
Then the Next.
Connect in Place
Point Prometheux at the systems behind one flow: core banking, payments, CRM, ledger or reporting. The data is processed where it lives; nothing is copied.
Codify the Knowledge
Your analysts, our forward deployed engineers and the AI assistant turn spreadsheets, policies and expertise into readable rules in days, not months.
Run One Use Case
A customer eligibility check, reconciliation, regulatory control or credit explanation, on live data, for teams and agents alike.
Expand Flow by Flow
Each new use case reuses the rules and connections already in place, so the next team starts further ahead.
Questions,
Answered
Is this another data platform we have to load?
No. Prometheux reads core banking, payments, risk and reporting data where it already lives, across databases, warehouses, mainframe extracts and files, and runs the rules there. There's nothing new to migrate or keep in sync.
We already have financial-crime and KYC tools. Why add Prometheux?
Keep them. Specialist tools are strong inside their function. Prometheux runs the bank's own logic across systems and functions, reads from those tools and the data you license, and writes results back to the databases behind the case and reporting systems your teams already use.
Can it run inside our own infrastructure?
Yes. Install it on your own servers with Docker or Kubernetes, in your private cloud, or inside Snowflake and Databricks, under your existing access controls. Prometheux is SOC 2 Type II certified.
How do auditors and model risk teams review it?
Rules are plain, versioned text your team can read. Every result links to the rules that fired and the source rows they used, and the same input always gives the same output, so a result can be replayed and checked.
What does it cost?
It depends on your data and use cases, so we measure it on yours rather than quote a generic figure. Most banks start with one flow, prove the value, then add use cases on the same rules and connections, which is where the cost per use case falls.
Related Capabilities
Bring One Flow
That Must Hold Up.
An eligibility check, reconciliation, regulatory control or credit explanation on your own data. Our forward deployed engineers will run it with you, in place, on your infrastructure.
