Financial services AI

AI for Financial Services

Arvya implements cited, approval-gated AI workflows for financial services teams. Deployment, delegated permissions, retention, system access, and audit boundaries are confirmed for each engagement.

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AI for financial services has to respect data boundaries before it can be useful. Arvya deploys inside the customer's own cloud tenant (Microsoft Azure native today, Google Cloud supported per deployment) using delegated permissions, never storing raw email bodies or documents, and keeping an audit log on everything. On that foundation it builds one verified memory from the firm's own activity and ships workflows with citations, human approval before writeback, and read-back receipts proving each write landed.

// who this is for

Financial services teams with sensitive workflows, fragmented data, and strict approval requirements.

Technology and operations leaders who have passed on AI tools over security and need in-tenant architecture.

Firms that need AI connected to Microsoft 365, the CRM, documents, and relationship context, without moving data into a vendor's cloud.

The problem

  • Horizontal AI tools rarely meet the permission, audit, and data-residency bar financial services teams have to clear.
  • Firm knowledge lives in disconnected systems (CRM, data room, trackers, notetaker), each sold separately, none reconciled.
  • AI pilots fail when they do not fit the team's actual tools, fields, review paths, and data boundaries.

What Arvya does

  • Configures the agreed deployment and delegated permissions, with retention and processing boundaries documented before live use.
  • Builds verified, cited memory across companies, people, funds, deals, meetings, and documents, with every fact keeping its source.
  • Ships approval-first workflows: staged CRM updates, briefs, digests, and drift corrections, each write followed by a read-back receipt and logged to an append-only audit trail.

// how it works

01

Identify the business workflow, system owners, data sources, and trust requirements.

02

Connect the systems the firm already owns (CRM, Microsoft 365, data rooms, notetaker), configured per deployment, no rip-and-replace.

03

Deploy the first workflow inside existing tools, verify against a measured baseline, then expand where users already see value.

// works with

Microsoft 365OutlookTeamsSalesforceDealCloudAffinitySharePointOneDriveresearch toolscustom systems

Frequently asked questions

What should financial services firms look for in an AI implementation partner?

Four things: in-tenant deployment so data never leaves the firm's cloud, source citations on every claim so output can be verified, human approval before anything is written to a system of record, and an audit trail on every action. A partner that cannot show a write landing (the record read back after the update) is asking for trust it has not earned.

Can Arvya support custom financial services workflows?

Yes. The platform is one verified memory with workflows as views over it, and each deployment is configured to the firm's stack: its CRM, its notetaker, its data room, its cloud (Azure native, Google Cloud per deployment). Custom schemas, approval queues, and output formats are part of the implementation, not an add-on.

One live mandate

See the transaction become a live operating system.