Rogo

What is Rogo?

Rogo is an AI platform purpose-built for finance professionals at investment banks, private equity firms, and asset managers. It consolidates a firm's proprietary data alongside external sources, including SEC filings, PitchBook, S&P Global, FactSet, and Preqin, to automate research, analysis, and financial workflows. Unlike general-purpose AI chatbots, Rogo was built by former bankers and investors who designed it specifically around the complexity of high-finance work. The platform produces institutional-grade outputs such as auditable Excel models, investment memos, diligence materials, and slide decks, and currently serves over 25,000 bankers and investors with more than 50,000 daily queries processed.

Key Features

• Finance-Specific LLMs and Agents: Fine-tuned large language models built exclusively for financial workflows, reducing hallucination rates from 34.1% to 3.9% and powering AI Tables for multi-step logic and comparative analysis.
• Document Search and Analysis: Scans internal and external documents, including SharePoint files, SEC filings, and proprietary data rooms, with support for multimodal text and visual data processing using retrieval augmented generation.
• Deep Research and Automation: Autonomous agents conduct company research, locate precedent transactions, and generate industry reports with web crawling, source attribution, and rationale documentation.
• Institutional Output Generation: Automatically builds slide decks, investment memos, competitive benchmarking reports, company profiles, and auditable Excel financial models.
• Data Integration: Connects directly to a firm's internal systems, including SharePoint and CRM platforms, as well as external financial data sources like FactSet, S&P Global, and Preqin.
• Rich Formatting and Export: Supports in-cell citations for spreadsheets, PDF exports, and copy-paste functionality that preserves formatting when moving content into PowerPoint, Word, or email.
• Cloud Infrastructure: Built on Google Cloud (Gemini 2.5 Flash and Pro via Vertex AI), AWS Bedrock, and uses Dataflow for data processing pipelines and Spanner for embedding and token retrieval.

Use Cases

• Investment Bankers and Analysts: Use Rogo to automate research, meeting preparation, and company profiling, saving 10 or more hours per week and redirecting that time toward client relationships and deal execution.
• Private Equity Firms: Generate investment memos and due diligence materials, integrate private data rooms, create question lists, and track client interactions, reducing processes that previously took days down to minutes.
• M&A Advisory Teams: Conduct precedent transaction research, competitive benchmarking, and valuation analysis with source-auditable responses and low hallucination rates, supporting over 100 core banker and investor use cases.
• Equity Research Professionals: Pull actionable insights from filings, transcripts, and presentations quickly, then produce presentation-ready materials. Baird Equity Research is a documented customer using Rogo to sharpen its research output.
• Hedge Funds and Asset Managers: Run real-time research queries, process large volumes of financial data, and generate institutional-quality analyses with citations, all within a secure enterprise deployment.

Strengths and Weaknesses

Strengths:

• Finance-specific design means the platform handles the nuance of high-finance workflows where general AI tools break down, backed by a team of former Lazard and J.P. Morgan bankers.
• Significant productivity gains reported by users, including 10 or more hours saved per week on tasks like meeting prep and company profiling, and a total of 500 years of full-time human work saved across the platform.
• High customizability with bespoke deployments tailored to each firm's systems, data sources, and workflows.
• Low hallucination rates relative to general models, with Gemini 2.5 Flash bringing the rate down to 3.9%, which matters for high-stakes financial outputs.
• Annual Recurring Revenue grew 27x since emerging from stealth, suggesting strong adoption among financial institutions.

Weaknesses:

• Steep learning curve during setup, with significant time required to integrate the platform with existing firm systems.
• Premium enterprise pricing with no free tier makes it inaccessible to smaller teams or individual practitioners.
• Scope is limited entirely to financial industries, so firms operating across non-financial sectors cannot apply it broadly.
• Browser-based workflow creates friction for some users who must leave Excel or other tools, upload data, query the platform, and manually copy results back, which introduces context switching.

Pricing

Rogo does not publish fixed pricing tiers and has no free tier or public trial available without direct sales engagement. Pricing is custom and based on factors such as number of users, data processing volume, customization requirements, and integration complexity.

• Custom Enterprise Plan: Contact sales at [email protected], pricing tailored to the organization's specific needs and scale.
• AWS Marketplace Option: A 12-month shared tenancy contract is available at $10,000,000, which entitles users to a specified quantity of use. Additional AWS infrastructure costs may apply, and access expires upon non-renewal.

Firms can also access Rogo through Azure Marketplace. The starting point for any engagement is a demo request through rogo.ai.

FAQ

What does the company Rogo do?

Rogo provides an AI platform built specifically for finance professionals at investment banks, private equity firms, and asset managers. It automates research, analysis, and document generation tasks by unifying a firm's internal data with external financial data sources.

What is Rogo used for?

Rogo is used to automate financial workflows including building investment memos, generating slide decks, conducting company research, performing due diligence, and producing competitive benchmarking reports. Analysts also use it for meeting preparation, company profiling, and precedent transaction research.

Who is the CEO of Rogo?

Rogo was co-founded by Gabriel Stengel, John Willett, and Tumas Rackaitis. The dossier does not specify which founder holds the CEO title at present.

Where is Rogo headquartered?

Rogo's headquarters location is not publicly listed in the available research data.

How many people use Rogo?

Rogo reports over 25,000 bankers and investors using the platform, with more than 50,000 daily queries processed.

Is Rogo free to use?

No. Rogo has no free tier and no publicly available trial without going through the sales team. Pricing is custom enterprise and requires direct contact with Rogo's sales team.

How much does Rogo cost?

Rogo uses custom enterprise pricing based on each organization's needs. One option listed on AWS Marketplace is a 12-month shared tenancy contract at $10,000,000. For all other arrangements, pricing requires contacting Rogo directly.

What financial data sources does Rogo integrate with?

Rogo connects to a range of external financial data platforms including SEC filings, PitchBook, S&P Global, FactSet, and Preqin. It also integrates with internal firm systems such as SharePoint and CRM tools.

How does Rogo reduce hallucinations in AI outputs?

Rogo uses fine-tuned models and routes tasks to the most appropriate AI for each job. Using Gemini 2.5 Flash, the platform reports reducing hallucination rates from 34.1% to 3.9%, which is a meaningful improvement for professionals relying on accurate financial data.

Who are Rogo's customers?

Rogo's customers include leading financial institutions such as Truist Securities, Nomura, Lucerne Capital, and Baird Equity Research. The platform targets investment banks, private equity firms, hedge funds, and asset managers.

Is Rogo suitable for small teams or individuals?

Rogo's premium pricing and enterprise deployment model make it most appropriate for large financial institutions and established firms. Small teams or individual practitioners are unlikely to meet the cost and integration requirements.

What outputs does Rogo produce?

Rogo generates auditable Excel financial models, investment memos, PowerPoint slide decks, diligence materials, company profiles, and competitive benchmarking reports. Outputs are designed to meet institutional quality standards.

How does Rogo compare to general AI chatbots for finance work?

General AI chatbots are not trained on the specific workflows, terminology, or data sources used in high-finance environments. Rogo is built with finance-specific models, integrates directly with financial data platforms, and produces outputs formatted for institutional use, which is where general tools tend to fall short.

What are the main limitations of Rogo?

The platform is limited to financial industry use cases, has a steep setup and learning curve, carries premium pricing that excludes smaller firms, and currently requires some manual copy-pasting between browser-based workflows and tools like Excel.

How does Rogo handle security?

Rogo offers custom, bespoke deployments with enterprise-grade security and maintains a Security Advisory Board. Each firm's deployment is configured separately, keeping proprietary data within the firm's own environment. Further details are available on Rogo's security page at rogo.ai/security.