Knowledge graph for finance
Financial Services Knowledge Graph
Arvya builds verified, cited knowledge graphs for financial firms: per-deal memory today, connected into firm-wide cross-deal memory, with every fact keeping its source.
Book a Working SessionA financial services knowledge graph connects the people, companies, funds, relationships, meetings, documents, and CRM records a firm depends on, with every fact keeping its source. Arvya builds these graphs as Deal Brains: one verified memory per deal, assembled from the email, calls, and documents the firm already generates. Connected Deal Brains become the Company Brain (firm-wide, cross-deal memory of who talked to whom, which buyers passed and why, and every process ever run), in development.
// who this is for
Financial firms whose institutional memory lives across email, CRM, documents, meetings, and partner memory.
Teams that need AI to understand firm-specific entities and relationships before it can be useful.
Technology and operations leaders building the data layer for AI workflows.
The problem
- Documents and CRM records are not enough; the relationships between people, firms, funds, meetings, and decisions carry the meaning.
- Generic retrieval misses firm context and produces answers without a source trail anyone can check.
- Workflow automation is risky unless the underlying graph knows permissions, ownership, and where each fact came from.
What Arvya does
- Builds cited graphs from the activity the firm already generates (the gold in its email, calls, and documents), with every fact traceable to its source.
- Uses the graph as the single memory under every workflow: briefs, CRM writeback, trackers, drift monitoring, weekly updates.
- Is building MCP access on top of the graph, so Claude and Microsoft Copilot can answer from firm memory (permissioned, cited, audit-logged), in development.
// how it works
Define the firm ontology: people, firms, funds, deals, companies, sources, meetings, documents, and workflows.
Connect approved source systems and preserve citations on every extracted fact.
Use the graph to power answers, briefs, staged updates, and, as Deal Brains connect, firm-wide cross-deal memory.
// works with
Frequently asked questions
Why does a financial firm need a knowledge graph for AI?
Because the meaning of a note, email, call, or CRM field depends on relationships between people, firms, funds, deals, owners, and time. A graph makes that context reusable, and a graph where every fact keeps its source makes it verifiable, which is the difference between AI a deal firm can act on and AI it has to double-check.
How is Arvya's Deal Brain related to a knowledge graph?
The Deal Brain is Arvya's applied knowledge graph for one deal: a verified memory where every fact cites the email, call, or document it came from. Connected Deal Brains form the Company Brain, the firm-wide graph across all deals and relationships, in development. Both feed the same workflows: cited answers, staged updates, human approved writes.
// related
Deal Brain →
The Deal Brain is Arvya's verified memory for each live deal (every fact cited to its source) and the foundation of the Company Brain, the firm-wide cross-deal memory in development.
AI Implementation for Financial Firms →
Arvya helps financial firms implement AI inside real workflows: one verified deal memory, cited outputs, human approved writeback with receipts, deployed in the firm's own cloud tenant.
FDE AI Implementation →
Arvya brings a founder-led, field-engineering motion to financial firms: workflow discovery, integration with the stack the firm already owns, verified memory buildout, and deployment in the firm's own tenant.
CRM Trust Workflow for Deal Teams →
Arvya makes DealCloud, Salesforce, and the CRM your firm already owns trustworthy again: bulk enrichment from SEC filings and firm websites, evidence backed updates a human approves, and a read-back receipt on every write.
One live mandate