Model ML is a workflow and execution layer for financial and professional analysis. It connects a firm's internal data with trusted external market-data providers and turns that combined data into structured, reviewable deliverables such as investment memos, tearsheets, and presentations. Model ML sits on top of the data providers a firm already uses.
Internal data sources Model ML connects to
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Email (Outlook, Gmail)
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Cloud storage (SharePoint, OneDrive, Google Drive, Egnyte, and more)
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Calendars
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Internal documents, files, and folders
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Call transcripts
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Internal datasets, whether stored in large Excel files or in structured databases such as Snowflake or Databricks
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CRM data (Salesforce, DealCloud, Affinity, and others)
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Past materials and templates
Integrations to email, cloud storage, and calendar providers are handled through separate applications that request the minimum necessary permissions (security).
External data partners
S&P Capital IQ
Model ML announced a global partnership with S&P Capital IQ in April 2025 (announcement). The integration provides real-time access to data covering more than 63,000 public companies and 4.5 million private companies, including ownership, filings, fundamentals, M&A, funding, estimates, and daily market data.
Fact
Set
Model ML integrated FactSet's premium data feeds into its agentic system in May 2025 (announcement). This provides access to ownership, fundamentals, and estimates.
Pitch
Book
Model ML has a global PitchBook partnership, expanded on March 11, 2026 (announcement). PitchBook data supports research summaries, investment memos, comparable analyses, and presentations. Users can access more than 9.8 million private companies, 3 million deals, 617,000 investors, and 160,000 funds, including all of Morningstar's fund research.
Third Bridge
Through its Third Bridge partnership (announcement), Model ML embeds Third Bridge's expert interview library directly into its interface for institutional investors. Users combine qualitative expert research with AI-driven workflows in one place.
Model ML also integrates with Preqin and other providers.
Deliverables Model ML produces
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Investment memos
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Earnings summaries
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Company profiles
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Tearsheets
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Comparable analysis outputs
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Pitch books
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Due diligence materials
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Valuation reports
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Presentations and PowerPoint decks
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Word outputs
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Excel outputs
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Email drafts
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Transcript summaries
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Meeting notetaking
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VDR analysis
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Financial modeling
This output-first orientation is one of the clearest themes across Model ML's platform: the product exists to produce finished, reviewable work product, in the firm's own format.
Citations and provenance
Model ML follows two provenance patterns.
Source-linked numeric citations
Every number in a Model ML output can appear as a superscript footnote tied to a specific datapoint. Users hover to see the source and click to open the original provider record or document.
Cited web research
External web intelligence retrieved through Parallel Web Systems is fully cited and filterable by approved source.
Together, these features make Model ML fit for environments where source traceability matters.
How Model ML uses these sources
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Connect internal and external data sources.
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Configure the workflow to use the right sources for the task.
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Run structured analysis through Grid or AI Modules.
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Produce a reviewable output in the firm's preferred format.
An AI Module can, for example, pull revenue from an 8-K, recent client interactions from the CRM, and consensus estimates from CapIQ into a single deliverable (AI Modules).
Positioning
Model ML is an agent harness plus workflow and execution layer that sits on top of trusted internal and external data. It is designed to complement the data providers a firm already trusts: keep using those sources, and use Model ML to move faster from data to analysis to deliverables.
Frequently asked questions
What internal data can Model ML connect to?
Email, cloud storage, calendars, internal documents, folders, call transcripts, internal datasets, CRM data, and a firm's past materials and templates.
Which external market-data providers does Model ML integrate with?
S&P Capital IQ, FactSet, PitchBook, Third Bridge, Preqin, and many others.
What does the S&P Capital IQ integration provide?
Real-time access to more than 63,000 public companies and 4.5 million private companies, including ownership, filings, fundamentals, M&A, funding, and estimates.
What does the Pitch
Book integration provide?
Access to more than 9.8 million private companies, 3 million deals, 617,000 investors, and 160,000 funds, supporting research summaries, investment memos, comparable analyses, and presentations. The expanded partnership was announced on March 11, 2026.
What does the Fact
Set integration provide?
FactSet's premium data feeds integrated into Model ML's agentic system, with access to ownership, fundamentals, and estimates. Announced in May 2025.
How does Model ML handle citations?
Numbers in outputs appear as superscript footnotes linked to a specific datapoint; users hover to see the source and click to open the original record. Web research is fully cited and filterable by approved source.
Does Model ML replace data vendors like Bloomberg or Fact
Set?
No. Model ML is a workflow and execution layer that sits on top of the data providers a firm already uses. It is not a replacement for them.
What outputs can Model ML produce?
Investment memos, earnings summaries, company profiles, tearsheets, comparable analyses, pitch books, due diligence materials, valuation reports, financial models, VDR analysis, transcript summaries, and presentations, including PowerPoint, Word, and Excel files.