Your risk, product, and client systems each hold part of the picture. None of them holds the whole. LangOptima connects them into a single knowledge graph — so full counterparty exposure, regulatory traceability, and hidden subsidiary relationships become questions answered in seconds, not days.
A risk analyst asks what your full exposure is to a named counterparty — across all products, entities, geographies, and related parties. For many teams we have spoken with, the honest answer is: “Give me two days.”
Counterparty data lives in separate credit, trading, custody, and client master systems. Each has its own identifiers, refresh cycles, and governance.
Analysts pull extracts, reconcile IDs in Excel, and stitch together a view that is obsolete the moment it is published. Every regulatory request repeats the work.
The hidden subsidiary, the shared directorship, the indirect exposure through a collateral chain — all sit in the gaps between systems. No single query will find them.
LangOptima sits above your existing risk, product, and client systems — without replacing any of them. We structure the relationships they already contain into a semantic knowledge graph that understands that a parent company, its subsidiaries, its counterparties, and the products held between them are all connected — and lets you traverse that connection in a single query.
Credit, trading, custody, KYC, and client master systems unified at the semantic layer. Nothing moves. Nothing is replaced. Every system keeps doing its job.
Traverse from a counterparty to its parent, to its subsidiaries, to shared directorships, to products held, to collateral positions — and surface relationships your analysts did not know to look for.
Regulatory responses, risk committee prep, and ad-hoc exposure questions answered in seconds. The same query that took two days runs in under a minute.
Your risk analysts stop reconciling data and start asking the questions they were hired to answer. Every analyst becomes a team of analysts.
Representative scenarios for organizations with your profile — ask us what applies to yours.
A tier-2 bank reduced their regulatory data response time from 3 weeks to 4 hours by unifying counterparty, product, and exposure data into a knowledge graph. The same graph now powers day-to-day risk queries and ad-hoc board requests.
Generic machine translation failed on this client’s specialized knowledge base. Our knowledge-graph-mediated translation workflow — grounding translation in domain-specific glossaries and validated terminology — delivered accurate results where others could not.
However complex the data landscape underneath, the engagement itself stays simple.
We ingest the documents and data you already hold, straight from the systems you already run. Nothing is replaced — your teams keep working where they work today.
A scoped 8–12 week pilot structures your first decision context. Your domain experts contribute the knowledge; we do the engineering.
You start asking the questions — and every answer carries a citation back to the source, so you can check it yourself.
Start with a 30-minute conversation. We’ll listen to the specific counterparty, exposure, or reporting question that is burning the most time today — and show you how it would be answered on a knowledge graph.