The problem

Fragmented investor records

Fragmented investor data

Investor profiles are often spread across CRM records, third-party data sources, commitments, fundraising history, and internal interaction notes.

Messy and incomplete records

Messy and incomplete records

Even with market data providers, investor profiles can contain gaps, stale fields, duplicate records, or conflicting information across source.

Investor prioritization models

Hard to prioritize action

Manual cleanup and enrichment slow down fundraising workflows, while teams struggle to identify the right investors for the right products.

What our system does

Merge

AI-assisted matching across CRM, third-party, and internal sources.

Enrich

ML models classify, complete, and improve investor records.

Score

Investor/product fit models help prioritize the right LPs for each fund or strategy.

Explain

AI-generated summaries, next actions, relationship insights, and decision support.

Software plus support, not another tool to manage

Each engagement combines our deployed tools with a defined block of hands-on support and data consulting hours. Those hours can be used to implement and tune the platform, clean or analyze data, design pipelines, build reports, support integrations, or help with broader data challenges around your ecosystem.

Why not just hire internally or use your CRM vendor?

Hiring gives you people, but not the tools. CRM vendors give you software, but usually not hands-on data cleanup, AI tuning, enrichment, and private-markets implementation. AltF2 combines both: deployed tools plus senior data/AI support.

Connect fragmented investor records

AI-assisted entity resolution across CRM, third-party, and internal data.

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Improve investor data quality

ML-powered investor enrichment and data quality pipelines.

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Prioritize better-fit investors

Investor/product fit scoring through APIs, CRM widgets, or reports.

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Give teams useful relationship context

LLM-generated investor summaries, next actions, and relationship context.

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Use support hours where they matter

A fixed block of hands-on hours can be used for platform tuning, data cleanup, pipeline design, reporting, analysis, implementation help, or broader data consulting.

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Embed into your existing ecosystem

Delivered through ETLs, APIs, CRM extensions, reports, workflows, pipeline design, and consultation.

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Start with a focused data readiness sprint

A practical first pass on your investor data, designed to expose quality gaps, show what enrichment can improve, and define the integration path.

Request a Data Readiness Sprint

First data quality report

Enrichment sample showcase

Light data cleanup

Integration roadmap for your ecosystem

Mike Goodwin

AltF2 has been a strong partner in helping us take complex data challenges and turn them into practical, business-ready solutions. They’ve contributed to improving the structure and usability of our data and have provided helpful senior-level technical guidance across our data and AI work. The team is responsive, easy to work with, and collaborates well alongside our internal data team.

Mike Goodwin

CIO, Ridgepost Capital

Want to see where AI and data tooling actually fit in your business?