Rogo closed a $50 million Series B in April 2025 at a $350 million post-money valuation. The round was led by Thrive Capital with participation from J.P. Morgan Growth Equity Partners and Tiger Global.

The company previously raised an $18 million Series A in October 2024 led by Khosla Ventures. Before that, Rogo secured seed funding in February 2024 led by AlleyCorp, with additional participation from Positive Sum Ventures.

In total, Rogo has raised $75 million across all funding rounds.

Rogo is an AI co-pilot that integrates into investment bankers' daily workflow through Excel, PowerPoint, Word, and their firm's data warehouse. The platform functions like a junior analyst that understands finance jargon, templates, and compliance requirements.

The core interface is a chat-first workspace where bankers enter plain-English prompts like "Build a five-slide overview of TMT carve-outs over $1 billion since 2022." Rogo plans the task, pulls relevant data, and returns a finished presentation deck with source footnotes.

Pre-built Quick Actions provide one-click workflows for common tasks including public company profiles, earnings comparisons, meeting prep memos, and deck proofreading. These are surfaced on the home screen to reduce reliance on prompt engineering.

The platform includes a spreadsheet agent that can read, explain, audit, and edit complex 40-tab valuation models. It answers questions like "Why is 2027 free cash flow negative?" and can refresh comparables from Capital IQ or roll models forward by quarters, with all output written back into Excel to maintain auditability.

Rogo pipes in both internal documents from deal rooms and pitch decks as well as licensed data feeds from LSEG fundamentals, PitchBook private market data, Quartr earnings transcripts, and international filings. The system automatically grounds answers in whichever sources the firm is entitled to access.

Rogo Pro uses a proprietary financial reasoning stack combining fine-tuned GPT-5, Gemini 2.5 Pro, and smaller reasoning models. Smaller models handle parsing and retrieval while GPT-5 is reserved for high-stakes financial analysis and reasoning tasks.

Rogo is a B2B SaaS platform for investment banking professionals sold via enterprise-grade subscriptions. The company sells directly to financial institutions through multi-year contracts that include compliance certifications and security requirements typical of the banking sector.

The platform is deployed as single-tenant instances to meet strict data security and regulatory requirements. This architecture supports pricing of around $3,300 per seat annually, above typical SaaS products and in line with specialized financial software.

Rogo's cost structure includes cloud infrastructure and data licensing fees paid to third-party providers like LSEG, PitchBook, and Quartr. Partnerships provide wholesale access to financial data feeds, which are packaged into the platform's AI-powered workflows.

The model benefits from high switching costs once integrated into daily banking workflows. Investment banks rely on Rogo for time-sensitive deal processes, creating recurring usage patterns that drive contract renewals and expansions across additional users within client organizations.

Revenue expansion occurs primarily through seat-based growth as more professionals within client firms adopt the platform. The company also generates additional revenue through paid features and access to specialized data sets for different types of financial analysis.

FactSet launched Mercury conversational search and Pitch Creator to auto-build pitchbooks inside Microsoft Office, cutting manual work by 80%. The company leverages proprietary StreetAccount and estimates data but faces challenges with slower iteration cycles and seat pricing above $30,000 annually.

S&P Capital IQ Pro added Document Intelligence and ChatIQ Gen-AI assistant with tight integration to Kensho models. The platform offers data breadth but struggles with UI complexity and multi-year contract requirements that limit flexibility.

Bloomberg powers AI earnings call summaries and document search inside Terminal through BloombergGPT. While Bloomberg has a large terminal install base, the walled-garden approach limits customization options compared to specialized solutions.

Mosaic focuses on Digital Deal Modeling and is expanding from private equity to investment banking through an Evercore partnership. The platform provides automated Excel models and verification with usage-based SaaS pricing, potentially commoditizing financial modeling workflows.

These specialist startups compete by unbundling specific analyst workflows like financial modeling, pitch deck production, and diligence processes. They offer faster deployment and lower costs compared to incumbent data vendors but lack the comprehensive data relationships of established players.

Large banks including JPMorgan, Goldman Sachs, and Citi are building proprietary LLM stacks to protect sensitive data and reduce vendor spending. This vertical integration creates competitive pressure as major institutions develop internal alternatives rather than relying on third-party solutions.

Rogo embedded OpenAI deep research agents in June 2025 that can browse, cite and summarize filings, call transcripts and web data. This enables bankers to run end-to-end diligence and create comprehensive earnings call presentations within the platform.

The August 2025 upgrade to GPT-5 materially improved multi-step valuation, precedent deal analysis, and slide generation accuracy. The upgrade enables Rogo to handle higher-value work including full fairness opinion models and confidential information memorandum drafting, expanding beyond analyst-level tasks to associate and VP-level output.

Partnerships with Crunchbase and PitchBook provide coverage of over 150,000 private companies and 120,000 funds. This enables new workflows for sponsor coverage, private placement advisory, and growth equity origination beyond traditional public market analysis.

Rogo's OpenAI collaboration explicitly extended platform access to private equity and hedge fund users, signaling expansion beyond investment banks. This targets approximately 100,000 professionals in global PE and hedge funds plus 30,000+ corporate development staff at Fortune 2000 companies.

The platform is used by middle-market and boutique firms including Moelis, Nomura and GTCR. These firms lack budgets for JPMorgan-style in-house LLM development, creating an addressable market for third-party AI solutions.

Buy-side adoption expands the addressable market as private equity firms, hedge funds, and corporate development teams face similar data analysis and presentation challenges as investment bankers.

Global investment banking fee pools rebounded to $117 billion in 2024, with 45% generated outside the Americas. Recent data shows fee growth returning in MENA at 24% while Asia represents approximately 35% of historical deal value despite current cyclical weakness.

Rogo's August 2025 LSEG partnership makes content instantly available to LSEG Workspace users worldwide, reducing friction for international client acquisition across EMEA and APAC markets.

The company can leverage its financial reasoning models and compliance frameworks to serve international banks facing similar workflow challenges, particularly in markets where firms cannot justify building proprietary AI capabilities.

Model dependency: Rogo's core value proposition depends on third-party AI models from OpenAI and Google, creating vulnerability if these providers change pricing, restrict access, or if competing banks develop superior in-house alternatives. Any deterioration in model performance or availability could materially affect customer satisfaction and retention.

Regulatory compliance: Financial services operate under tightening AI governance requirements around model explainability, data handling, and algorithmic bias. New regulations could require platform modifications or limit deployment in certain jurisdictions, particularly as regulators scrutinize AI decision-making in sensitive financial processes.

Incumbent retaliation: Major data providers such as Bloomberg, FactSet, and S&P Capital IQ have entrenched relationships with investment banks and could bundle competitive AI features at marginal cost to defend their high-margin seat licenses. Their existing data moats and procurement relationships create competitive advantages that could pressure Rogo's pricing and market access.