Asset management, wealth, advisory, research, investment operations, risk, compliance, and distribution leaders

Investments data + AI transformation

Investment firms need faster insight and more personalized service without compromising fiduciary judgment, suitability, controls, or the traceability of investment decisions. Infinitive connects the systems you already run to trusted data and AI so teams can improve outcomes without separating innovation from governance.

Discuss Investments priorities Explore use cases

Speak the language of the business

Start from the operating model—not the model.

AUMHouseholdingSuitabilityResearchPortfolio riskPerformance attributionAdvisor productivityClient reportingTrade surveillance

We use the language, measures, controls, and workflows your teams already operate, then connect them to modern data and AI capabilities.

Trusted Enterprise AI

Five capabilities. One business outcome.

Every use case can draw from the same Infinitive capability model: Data Foundations to enable AI; Analytics + Decision Support powered by AI; Governance + Risk to trust AI; Agents + Automation driven by AI; and Adoption + Workforce Enablement to realize value.

01Data FoundationsTo enable AI 02Analytics + Decision SupportPowered by AI 03Governance + RiskTo trust your AI 04Agents + AutomationDriven by AI 05Adoption + WorkforceTo realize the value of AI

Customer / constituent journey

Use AI where it improves the experience and the economics.

AI becomes more valuable when the same governed data and decision logic follows the journey instead of being rebuilt channel by channel.

Prospect

Identify investor needs, segments, and advisor opportunities using governed household and market context.

Open / onboard

Accelerate account opening, KYC, suitability, document review, and transfer workflows.

Advise

Prepare portfolio and client context, scenario analysis, and explainable advisor prompts.

Invest

Support research, idea generation, portfolio analytics, and risk monitoring with governed data and provenance.

Report

Generate consistent performance narratives, commentary, and client-ready explanations grounded in approved data.

Retain / grow

Detect service friction, liquidity events, household opportunities, and retention risk for advisor review.

Employee journey

Give people better context, not another disconnected tool.

Infinitive redesigns the workflow so AI prepares evidence, finds patterns, and removes low-value effort while people stay accountable for judgment, exceptions, empathy, and business tradeoffs.

Advisor

Starts meetings with a trusted client brief, portfolio context, approved research, and next-best discussion topics.

Research analyst

Uses AI to synthesize filings, transcripts, internal research, and market data with citations and source provenance.

Portfolio / risk team

Monitors exposures, concentration, drift, scenario results, and exceptions with consistent definitions.

Compliance / operations

Reviews suitability, communications, surveillance, and operational exceptions with traceable evidence.

In-depth use cases

Where data, Databricks, and AI can change the work.

These are not generic AI demos. Each use case starts with a recognizable operating problem, the data required to solve it, the role of AI, the human decision point, and the measures that determine whether value is real.

Use case 01

Advisor intelligence and household next-best action

Advisors often assemble client context manually across CRM, portfolio, planning, interaction, product, and household systems.

Trusted data on Databricks

Create a governed household and relationship layer combining accounts, holdings, goals, risk profile, service history, consent, and life-event signals.

AI at work

Generate meeting briefs, identify gaps or opportunities, summarize interactions, and propose explainable follow-ups consistent with firm policy.

How Infinitive helps

Design the household data model, Databricks semantic layer, advisor experience, workflow integration, and adoption model.

Human accountability

Advisors retain suitability, fiduciary, disclosure, and relationship judgment.

Measures to improveAdvisor preparation timeHousehold penetrationClient engagementFollow-up completionRetention

Use case 02

Investment research copilot with governed provenance

Research teams spend significant time gathering filings, transcripts, market data, internal notes, and prior theses before analysis begins.

Trusted data on Databricks

Bring structured market data and unstructured research content into governed, permission-aware Databricks data products and vector indexes.

AI at work

Retrieve source-grounded evidence, compare companies or periods, summarize changes, draft research outlines, and identify questions that require analyst investigation.

How Infinitive helps

Implement ingestion, document intelligence, retrieval, entitlements, evaluation, and research workflows that preserve source traceability.

Human accountability

Analysts own thesis formation, valuation assumptions, recommendations, and publication.

Measures to improveResearch cycle timeSource coverageAnalyst reuseCitation completenessTime to insight

Use case 03

Portfolio, risk, and exposure surveillance

Portfolio teams need a current view of exposure, concentration, factor risk, liquidity, benchmark drift, and exception conditions across portfolios.

Trusted data on Databricks

Unify positions, transactions, reference data, benchmarks, risk factors, pricing, mandates, and limit rules in governed data products.

AI at work

Detect unusual changes, explain drivers, summarize exceptions, and surface relevant market or portfolio context for review.

How Infinitive helps

Modernize data pipelines, implement analytics and alerting, define semantic metrics, and integrate review workflows.

Human accountability

Portfolio managers and risk officers retain trade, rebalance, override, and escalation authority.

Measures to improveException detection timeRisk review efficiencyData reconciliationLimit breach responseDecision consistency

Use case 04

Client reporting and commentary automation

Performance and client-service teams repeatedly assemble data, commentary, attribution, and disclosures across accounts and channels.

Trusted data on Databricks

Standardize performance, holdings, attribution, benchmark, fee, and client-segment data with governed definitions.

AI at work

Draft account commentary, summarize performance drivers, explain changes in plain language, and tailor approved content to client context.

How Infinitive helps

Connect reporting data, implement controlled generation, create approval workflows, and measure cycle-time improvement.

Human accountability

Client teams approve narrative, disclosures, and material investment communication.

Measures to improveReporting cycle timeManual reworkNarrative consistencyApproval timeClient-service capacity

Use case 05

Suitability and communications review

Compliance teams review large volumes of recommendations, communications, product usage, and documentation for suitability and policy adherence.

Trusted data on Databricks

Connect client profiles, product attributes, recommendations, communications, policy, and supervisory history.

AI at work

Prioritize potentially inconsistent cases, retrieve applicable policy, summarize evidence, and draft review notes.

How Infinitive helps

Implement governed retrieval, rules and model monitoring, case prioritization, audit trails, and reviewer workflows.

Human accountability

Supervisors and compliance officers make final determinations and remediation decisions.

Measures to improveReview throughputException detectionEvidence retrieval timeSupervisory consistencyAudit readiness

Use case 06

Investment operations reconciliation and exception management

Operations teams manage breaks across trade, position, cash, corporate-action, and settlement systems with repeated investigation work.

Trusted data on Databricks

Centralize normalized operational events, reconciliations, counterparty data, exception history, and reference data in the lakehouse.

AI at work

Classify breaks, group similar causes, summarize history, suggest resolution steps, and identify upstream data-quality patterns.

How Infinitive helps

Modernize reconciliation data flows, configure exception analytics, integrate operational systems, and build a closed-loop improvement backlog.

Human accountability

Operations staff approve adjustments, accounting changes, and external communications.

Measures to improveBreak agingManual investigation timeRepeat exceptionsSettlement riskOperational capacity

How Infinitive engages

Land with a focused need. Expand through demonstrated value.

Clients can enter at any stage. We do not require a multi-year transformation before value is visible; we connect the right capabilities to the immediate problem and scale only where the evidence supports it.

01Activate

Define a priority problem, establish trusted data, and demonstrate value through a focused engagement or POC.

02Productionize

Make the capability secure, reliable, governed, measurable, and useful in everyday operations.

03Scale

Extend proven value across teams, workflows, data domains, and business areas—only where evidence supports it.

Why Infinitive

Trust is part of the architecture and the operating model.

Infinitive combines data and AI delivery with governance, risk, transformation, and adoption so the same team can address the technical path and the organizational conditions that determine whether AI actually works in practice.

Build on enterprise reality

Connect core systems, controls, teams, and existing investments rather than designing a disconnected AI island.

Govern at design time

Data access, lineage, security, policy, auditability, cost, and human decision rights are defined before production.

Prove value before scale

Use a focused entry point with business measures so the next decision is based on evidence—not enthusiasm.

Keep people accountable

AI can automate preparation and pattern finding; people remain at judgment, exception, empathy, and accountability.

Investments next step

Choose one workflow where better data and AI could change the outcome.

Bring the business owner, data/platform lead, and operating or risk leader. Infinitive will help frame the use case, required data, governance needs, human decision points, and the right Activate, Productionize, or Scale path.

Request a working session Why Infinitive