SearchFundAI

Inspiration

Search fund investors often struggle to identify promising small and medium-sized businesses to acquire or invest in. Unless someone is connected to a large venture partner network with access to proprietary deal flow and extensive databases, discovering quality companies is extremely time-consuming and inefficient. Many investors rely on fragmented public records, spreadsheets, cold outreach, and manual research to evaluate opportunities.

We wanted to build a platform that democratizes access to acquisition opportunities by helping search funders quickly discover, evaluate, and track companies using publicly available data and AI-powered analysis.

What it does

Search Fund AI is an intelligent sourcing and evaluation platform designed for search fund investors and acquisition entrepreneurs.

The platform automatically scans and aggregates public business records, financial filings, and company information from sources such as SEC EDGAR and other government databases. Using AI-driven analysis, the system evaluates companies across multiple dimensions including:

• Business longevity and stability
• Company size and growth indicators
• Industry attractiveness
• Financial health signals
• Acquisition fit for search fund investors

Each company receives a match score that helps investors prioritize the most promising opportunities.

Beyond discovery, Search Fund AI also acts as a lightweight deal pipeline and CRM system. Once a company is added to the user’s pipeline, investors can:

• Track outreach progress
• Log communication notes
• Schedule follow-ups
• Organize acquisition targets
• Monitor ongoing conversations and diligence steps

This creates a centralized workflow for sourcing and managing acquisition opportunities from discovery to outreach.

How we built it

We built Search Fund AI using a combination of public datasets, web scraping, AI classification models, and workflow management tools.

Our backend gathers company information from publicly available government sources such as SEC EDGAR filings and business registration databases. We then process and normalize the data to extract relevant company attributes.

To improve discovery, we trained AI models to classify companies by industry and business category. This allows users to filter opportunities based on investment preferences, acquisition criteria, and sector focus.

The platform also includes a pipeline management interface where users can manage target companies, store communication updates, and maintain acquisition workflows in one place.

Challenges we ran into

One of the biggest challenges was data accessibility and compliance. Many platforms that contain valuable business communication and contact information — such as LinkedIn or Salesforce-based directories — have strict terms of service that prohibit automated scraping.

To ensure compliance and avoid violating platform policies, we limited our automated data collection to public and legally accessible records. As a temporary workaround, users are currently prompted to manually input contact information when adding companies to their pipeline.

Another challenge was cleaning and standardizing fragmented public company data. Business records often vary in formatting, completeness, and accuracy, which required significant preprocessing and normalization before our AI models could analyze them effectively.

Accomplishments that we're proud of

• Built an end-to-end AI-powered acquisition sourcing platform
• Successfully integrated public business datasets into a searchable pipeline
• Developed an AI classification system for industry-based company matching
• Created a workflow system tailored specifically for search fund investors
• Designed a scalable foundation for future integrations and automated outreach tools

What we learned

Through building Search Fund AI, we learned how difficult and fragmented acquisition sourcing can be for independent investors. We also gained experience working with large public datasets, AI-driven classification systems, compliance considerations around scraping, and CRM-style workflow design.

Most importantly, we learned how AI can simplify traditionally manual investment research workflows and help smaller investors compete with larger firms that have proprietary deal sourcing advantages.

What's next for Search Fund AI

In the future, we plan to:

• Integrate verified business contact providers
• Add financial forecasting and valuation analysis
• Build AI-generated acquisition summaries and risk reports
• Support automated outreach workflows
• Expand beyond SEC filings into private business databases and alternative data sources
• Create collaboration features for investment teams and venture partners

Our long-term vision is to become the operating system for search fund acquisition sourcing and deal management.

Built With

• claude
• sqlite