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AI M&A Platform Comparison 2026

Six AI M&A platforms compared — Rogo, Eilla AI, OffDeal, Hebbia, DealFlowAgent, and Amafi — rated on origination, APAC coverage, and execution support.

Six AI M&A platforms compared: Rogo, Eilla AI, OffDeal, Hebbia, DealFlowAgent, and Amafi. Use the table to pick your fit, then scroll for full platform breakdowns.


Quick Comparison

RogoEilla AIOffDealHebbiaDealFlowAgentAmafi
Origination✓ (US only)✓ (US focus)✓ (APAC)
Document generationPartial
Diligence / synthesis
APAC coverageLimitedLimitedLimited
Full deal workflowPartial
Advisor-facing
Self-serve platform✓ (early access)
Best deal rangeAnyAny$1M–$30MAnyAny$10M–$500M

Which Platform Is Right for You?

If you need research synthesis on public data: Rogo is the leading option for institutional research workflows.

If you need to accelerate document drafting in North America or Europe: Eilla AI has the strongest document generation capability.

If you need APAC origination or execution support: Amafi is the purpose-built option. Other platforms have meaningful data coverage gaps in Japan, Southeast Asia, and Australia.

If you need due diligence document processing at scale: Hebbia is the leading option for large document set synthesis.

If you need US lower-middle market deal flow: OffDeal or DealFlowAgent cover this segment.

“The question deal teams should ask is not ‘which platform is best’ but ‘which platform was built for the geography and stage I work in.’ Most platforms were designed around US public company data. That’s a structural gap for APAC practitioners — and it’s the gap Amafi was built to close.” — Daniel Bae, Founder & CEO, Amafi ($30B+ transaction experience)


What the Category Covers

The “AI M&A platform” label gets applied to four distinct product categories:

Research and analysis tools — AI that synthesises documents, filings, and research into structured outputs. Hebbia and parts of Rogo sit here.

Document generation tools — AI that drafts pitchbooks, CIMs, teasers, and management presentations from structured inputs. Eilla AI leads this category.

Origination and deal sourcing tools — AI that identifies acquisition targets, matches buyers, and surfaces off-market opportunities. OffDeal, Axial, and DealFlowAgent focus here.

End-to-end infrastructure — platforms that connect origination through execution: target identification → pitchbook → buyer research → outreach → diligence → close. Amafi is purpose-built in this direction for APAC.

Most evaluation errors come from comparing tools across categories. A document generation tool is not competing with a sourcing platform — they solve different problems.


Platform-by-Platform Summary

Rogo

What it does: AI research assistant built for investment banks and professional services. Synthesises filings, earnings transcripts, and market data into structured research outputs. Strong on the research synthesis side; less focused on document generation or origination.

Strengths: Institutional-grade accuracy on public company data, strong integration into research workflows, good at summarising complex documents. Rogo has genuine non-branded SEO traction — ranking for AI for investment banking and AI financial analyst — suggesting real search-intent alignment.

Limitations: Research-centric; does not generate pitchbooks or CIMs. No origination capability. Coverage is primarily public company data (filings, transcripts, press releases). Limited private company depth and limited APAC coverage.

Best for: Bulge bracket and mid-market bank research teams synthesising public information. Less useful for boutiques running origination or sell-side execution.


Eilla AI

What it does: AI document generation focused on investment banking deliverables — pitchbooks, CIMs, deal summaries. Generates structured output from template and data inputs.

Strengths: Strong at producing first-draft investment banking documents quickly. Reduces the time from mandate brief to initial deliverable. Useful for boutiques with limited analyst capacity.

Limitations: Primarily a document tool — no origination capability and limited integration with the broader deal workflow. Data coverage is North American and Western European; APAC private company intelligence is largely absent. The Eilla AI alternative question comes up frequently for APAC deal teams precisely because of this gap.

Best for: Boutique advisors in North America or Europe who need to accelerate document drafting. Not suited to APAC origination or cross-border execution work.


OffDeal

What it does: Off-market deal marketplace connecting buyers and sellers in the US lower-middle market. Uses AI to match buyer intent with seller listings, primarily in the $1M–$30M deal range.

Strengths: Dense lower-middle market deal flow in the US. AI-powered matching between listed sellers and categorised buyers. Platform-driven process without requiring a full banking mandate.

Limitations: Geography-limited to North America. Deal range ($1M–$30M) is below mid-market. Marketplace model means deal quality and exclusivity can vary. No advisory-workflow tooling — the platform matches parties, but does not support execution. See our OffDeal alternative analysis for a full breakdown.

Best for: SME acquisitions in the US lower-middle market. Not a fit for APAC deal teams, mid-market boutiques running structured processes, or advisory firms needing execution infrastructure.


Hebbia

What it does: AI document analysis and synthesis platform. Reads, classifies, and synthesises large document sets — data rooms, regulatory filings, research reports. Uses multi-modal AI to handle complex unstructured inputs.

Strengths: Exceptional at synthesising large document volumes. Favoured by larger PE firms and law firms for due diligence and research workflows. Handles complex, multi-document queries well.

Limitations: Analysis and synthesis tool — not an origination platform, not a document generator in the pitchbook sense. High price point and enterprise-focused commercial model. Limited use for boutique M&A advisors or deal teams that need origination support.

Best for: Large PE funds and institutional investors needing to process data rooms, filings, and research at scale. Not a primary tool for boutique advisory origination or execution.


DealFlowAgent

What it does: AI-powered deal sourcing and outreach automation. Automates buyer and seller identification, outreach sequencing, and response tracking across deal pipelines.

Strengths: Outreach automation and deal pipeline management. Useful for teams running high-volume origination campaigns. Some AI-native workflow design.

Limitations: Primarily US-focused. Limited APAC private company coverage. Document generation is not a core capability. The Axial alternatives analysis covers the broader deal sourcing landscape DealFlowAgent operates in.

Best for: Deal teams in North America running high-volume outreach campaigns. Limited applicability for APAC cross-border mandates.


Amafi

What it does: A confidential, AI-driven M&A matching marketplace for APAC — privately matching business owners (sellers) with qualified investors, with a free AI deal toolkit (model, CIM, teaser, AI-native data room) and licensed advisory execution through Lyndon Advisory. The marketplace is live on early access.

Strengths: Purpose-built for APAC. Three-sided marketplace serving sellers, PE firms, and advisors. Full deal cycle coverage — AI-matched origination through to execution support — rather than solving a single workflow problem. Primary-source intelligence across APAC corporate registries, licensing databases, and market signals provides data depth in markets like Japan, Southeast Asia, India, and Australia where US-centric platforms have thin coverage. Free to join for sellers and investors; monetized through success fees on closed deals, not subscriptions.

Current stage: Early access — marketplace live for sellers and investors; register investor criteria or start a confidential sale.

Best for: Business owners exploring a confidential sale in APAC, PE firms and acquirers seeking AI-matched off-market deal flow, and boutique M&A advisors needing execution support infrastructure.


The APAC Data Gap

The single most consistent limitation across US-built AI M&A platforms is private company coverage in Asia Pacific.

Japan has tens of thousands of family-owned businesses with no English-language public filings. Southeast Asian SMEs exist primarily in national company registries, not global databases. Indian private companies are registered across state-level ROC systems. Australian private companies file through ASIC but require local data parsing.

A 2024 PwC analysis of cross-border M&A found that information asymmetry — buyers not finding the right targets, sellers not reaching the right buyers — is the single largest source of deal failure in APAC mid-market transactions. AI platforms that don’t solve the data problem don’t solve the deal problem.

Amafi’s approach builds on primary-source intelligence across the APAC market — corporate registries, licensing records, funding databases, and bilateral trade data — creating the research foundation for meaningful AI-augmented origination in markets where US-centric tools have structural blind spots.


What’s Coming in the Category

The AI M&A workflow category is moving fast. Key trends for 2026:

  • End-to-end integration: Single platforms connecting origination through close will outperform point solutions that require data transfer between tools.
  • APAC expansion: US platforms will attempt to expand coverage; purpose-built regional infrastructure will maintain a data quality advantage for 2-3 years.
  • Advisor-embedded tooling: The winning platforms will sit inside advisor workflows, not alongside them.
  • Outcome-aligned pricing: Success-fee or revenue-share models will supplement subscription pricing as platforms take on more of the origination risk.

For deal professionals evaluating AI M&A platforms in 2026, the starting question should be geography: where do you work, and does the platform’s data actually cover it?


Amafi is infrastructure for M&A — origination, execution support, and AI-augmented workflow for deal professionals across APAC. Work with us as a partner or join the platform waitlist.


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Daniel Bae

About the author

Daniel Bae

Founder & CEO, Amafi

Daniel is an investment banker with 15+ years of experience in M&A, having advised on deals worth over US$30 billion. His career spans Citi, Moelis, Nomura, and ANZ across London, Hong Kong, and Sydney. He holds a combined Commerce/Law degree from the University of New South Wales. Daniel founded Amafi to solve the pain points in M&A, enabling bankers to focus on what matters most — delivering trusted advice to clients.