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CIMs, Models, Emails - All Manual. All Slow.
Whether you’re scanning for new targets or managing live deal flow, most M&A teams are stuck in PDFs and Excel. Analysts waste hours summarizing CIMs, cleaning models, and searching inboxes for relevant buyers. The longer it takes, the more opportunity slips away.
Where M&A Workflows Break Down
CIMs and financial models arrive in inconsistent formats and require manual review
Analysts summarize deals in Word docs and spreadsheets, with no reusability
Buyer tracking happens in email threads or isolated CRMs
Search and triage for relevant past comps or deals is slow and incomplete
Our Solution
We built an AI-powered deal processing engine that ingests all inbound materials — CIMs, models, buyer lists, and emails — and turns them into structured deal intelligence.
Solution Components:
CIM Parser – Extracts key company details, financials, business model, and positioning from PDFs
Model Summary Engine – Parses Excel models and surfaces key KPIs and assumptions
Buyer Matching Agent – Links inbound deals to historical buyers based on vertical, size, and thesis
Triage Dashboard – Prioritizes live opportunities based on fit, risk, and historical precedent
Output Delivery – Structured summaries, dashboards, and deal tracking datasets ready for use in reporting, pitch prep, or CRM sync
Common Use Cases
Auto-extract KPIs and summaries from CIMs
Tag and index inbound deals to resurface buyer lists and past engagements
Accelerate buyer matching by linking new deals to historical closed/lost data
Enable MDs to see daily updates and prioritized triage without relying on analyst prep
Business Outcomes
Cut deal triage time from 3 hours to under 20 minutes
Increase responsiveness to bankers, founders, and sponsors
Improve buyer matching accuracy and speed with past deal context
Centralize deal memory across teams without relying on tribal knowledge