Deal Origination in the Age of AI Agents A Playbook for Boutique M and A Firms

Summary

For boutique M&A and private equity firms, deal sourcing has traditionally been a manual, resource-intensive process. Analysts spend countless hours scouring platforms like LinkedIn, Crunchbase, and Google Sheets to compile lists aligned with their investment theses. By the time these lists are finalized, the most promising companies are often already in competitors' pipelines.

However, this landscape is rapidly evolving. A new generation of AI agents is transforming how lean firms approach deal origination. These agents go beyond simple data retrieval—they interpret natural language prompts (e.g., "find vertical SaaS startups in LATAM with <$10M revenue and no VC backing") and execute end-to-end workflows to identify relevant companies in real time.

Key Capabilities of AI Agents:

• Automated Web Crawling: Agents can scour the web for niche companies before they appear on mainstream lists.
• Fuzzy Criteria Scoring: They evaluate targets against nuanced, qualitative criteria.
• Data Enrichment: Public data is used to enhance target profiles.
• Structured Outputs: Results are delivered as organized, actionable lists.

Platforms like Extruct are democratizing access to these tools, enabling boutique firms, family offices, and corporate strategy teams to build dynamic, custom company landscapes tied directly to their investment logic.

Real-World Applications:

• Discovering niche robotics companies ahead of competitors.
• Identifying founder-led brands in emerging sectors like alternative wellness.
• Mapping fragmented industries (e.g., metal 3D printing) with precision.

For concrete examples, Extruct’s Data Room showcases AI-generated lists across vertical SaaS and industrial tech.

Strategic Differentiation:

The adoption of AI agents isn’t just about speed—it’s about differentiation. Firms leveraging these tools can uncover companies that align with unique theses long before they raise Series A funding or gain media attention. In a field where information asymmetry is critical, AI agents are emerging as a competitive edge.

Future Prospects:

AI agents can be fine-tuned using a firm’s past deal history, proprietary frameworks, and qualitative preferences, transforming sourcing from reactive to proactive. Imagine inputting an internal memo and receiving a pipeline of matching targets the same day—this is now becoming an operational reality.