INDUSTRIES / FINANCIAL SERVICES
AI for Financial Services
We build production AI for financial-services and pursuit teams where an unsourced number gets the tool pulled from the meeting — client intelligence, briefs, and risk flags shipped with document-level attribution, entitlement-aware retrieval, and a human reviewer before anything ships.
Use cases: Instant client & pursuit briefs; Research synthesis; Risk flagging; Filing & 10-K analysis; Talk-track generation; Business-user prompt tuning.
Compliance and constraints handled: Source attribution, Entitlement-aware retrieval, Recordkeeping & audit trails, Model risk management, Human-in-the-loop, Client-owned deployment.
How do you keep AI outputs sourced and auditable in financial services? Every claim and risk flag is attributed back to the source document a reviewer can open, and every model call is logged with its prompt, response, and model version. Attribution back to source was the feature that earned partner trust in the field — unsourced claims got the tool pulled from meetings, so we build attribution in from the start.
How do you handle SEC and FINRA recordkeeping requirements? Systems are designed for the immutable, reconstructable audit trail that SEC 17a-4 and FINRA 4511 recordkeeping expectations demand: every interaction logged, every model call traceable, and retention controls specified before implementation. The goal is a record a regulator or auditor can reconstruct, not a black box.
Does this work with our existing data permissions? Yes. Retrieval is entitlement-aware — row-level security honors the permissions you already have across CRM, filings, and internal systems, so the model never surfaces a record a given user is not entitled to see. We integrate with existing identity and access controls rather than working around them.
How long until a financial-services workflow is in production? A focused workflow ships fast when it lives where the team already works. A first version typically reaches one team within weeks, with global rollout following as feedback drives iteration — one engagement reached 89,000 staff-hours saved monthly across global teams within a three-month rollout.
Does this replace our analysts or pursuit teams? No. It removes the 8–12 hours of manual intelligence-gathering per brief so teams pursue more opportunities with consistent quality. A reviewer still signs off on every output, and putting prompt tuning in business-user hands made the system a team asset rather than an IT project.
Which financial-services workflows are the best fit for AI? Workflows with scattered source data, a hard attribution requirement, and expert reviewers: instant client and pursuit briefs, research synthesis, risk flagging, filing and 10-K analysis, talk-track generation, and business-user-tuned prompt systems.
This public industry shell gives crawlers and answer engines the canonical industry focus, use cases, compliance posture, and FAQs before the React app renders the full interactive page.