Rogo
by Rogo Technologies
Agentic AI platform for investment banks, private equity and investors that produces auditable models, memos and decks
Rogo is an AI platform built specifically for investment banks, private equity firms and public-markets investors that automates financial research and deal work. Its Felix agent produces Excel models, comps, CIMs, memos and slide decks grounded in institutional data, removing hours of junior-banker grunt work while keeping outputs auditable.
Rogo is a New York-based AI company building a finance-native agentic platform for investment banking, private markets and public markets. It was founded by former bankers including CEO Gabriel Stengel, a former Lazard analyst, alongside John Willett and Tumas Rackaitis. The platform offers a chat-style research interface plus Felix, an agent that users reach either directly in the app or by email, delegating work the way they would to a colleague: shelling and refreshing pitch decks, building financial models and comparable-company analyses, drafting memos and meeting materials, and running deal screening, CIM generation, buyer outreach and data-room diligence. Outputs are grounded in a firm's internal systems (SharePoint, CRM) and licensed market data such as FactSet, S&P Capital IQ and LSEG, with audit trails and access controls designed around the Chinese walls and MNPI rules banks operate under. Rogo also acquired Offset, whose AI updates financial models with new information. The company raised a $75 million Series C led by Sequoia in January 2026 and a $160 million Series D led by Kleiner Perkins in April 2026, taking total funding past $300 million at a reported $2 billion valuation; investors also include Thrive Capital, Khosla Ventures and J.P. Morgan. Rogo reported 35,000 users at 250+ institutions at the Series D and now cites 50,000+ bankers and investors at 350+ institutions; named customers include Rothschild & Co, Jefferies, Lazard, Moelis, Nomura, Truist Securities and Baird. Sacra estimates ARR at $53 million in August 2026. It competes with Hebbia and incumbents' own AI such as FactSet and Bloomberg.
The COO, head of innovation or CTO at an investment bank, M&A advisory or PE firm with sizeable deal teams, who needs AI that produces bank-grade, auditable deliverables within compliance walls.
Junior-banker work — comps, models, CIMs, memos and deck refreshes — delegated to an agent that cites institutional data sources, freeing deal teams for client work.
At a Glance
- Category
- Industry & Government
- Pricing
- Subscription, Contact for pricing
- Target Market
- Investment Banks, Private Equity Firms, Asset Managers, CTOs, COOs
- Deployment
- Cloud-first
- Headquarters
- New York, NY, United States
- Customers
- 350+ institutions, 50,000+ users (per Rogo, 2026)
Key Features
- ✓Felix agent
Delegate multi-step deliverables like decks, models and memos by chat or email; Felix iterates on the work like a junior colleague.
- ✓Financial modelling and comps
Builds Excel financial models and comparable-company analyses and updates supporting materials, cutting hours from routine analyst work.
- ✓Deal workflow automation
Covers deal screening, CIM generation, buyer outreach and data-room diligence end to end, accelerating sell-side and buy-side processes.
- ✓Institutional data grounding
Draws on internal SharePoint and CRM content plus licensed market data such as FactSet, so outputs are sourced rather than invented.
- ✓Auditable outputs and controls
Audit trails and access controls are built for MNPI and Chinese-wall requirements, which is what lets regulated banks adopt it.
- ✓Compliance certifications
Rogo states SOC 2 and ISO 27001 certification plus GDPR, CCPA and EU AI Act compliance, easing vendor-risk review at banks.
Capabilities
Use Cases
- •Pitch deck refresh
A coverage team emails Felix to refresh market data and comps in an existing pitch book, receiving an updated draft deck to review.
- •Sell-side CIM drafting
Bankers generate a first-draft confidential information memorandum from company materials and market data, compressing days of drafting into hours.
- •PE target screening
Private equity associates screen potential targets against investment criteria and receive sourced summaries, speeding up pipeline triage for deal teams.
- •Data-room diligence
Deal teams have Felix review data-room documents and surface key risks and figures, so senior reviewers focus on judgement rather than extraction.
- •Investment memo preparation
Investors draft memos outlining returns and risks grounded in filings and research, producing consistent committee materials faster.
Ideal For
Best For
- ✓Investment banks and M&A advisory firms automating comps, CIMs and pitch-deck refreshes
- ✓Private equity deal teams screening targets and running data-room diligence
- ✓Coverage bankers who want to delegate research and model updates by email
- ✓Institutions that need source-cited, auditable AI output inside information barriers
- ✓Firms already licensing FactSet, Capital IQ or LSEG data that want AI grounded in it
Not Ideal For
- ✗Small boutiques and individual investors — there is no self-serve tier and seat economics are enterprise-scale
- ✗Hedge funds or asset managers wanting broad cross-asset research, where independent reviewers see Hebbia as a better fit
- ✗Accounting, finance-close or BI dashboard use cases, which Rogo is not built for
- ✗Teams expecting instant rollout — deployments involve weeks of integration, permissions and data-entitlement work
Deployment
Market & Ratings
350+ institutions, 50,000+ users (per Rogo, 2026)
Market Analysis
Pros
- ✓Finance-native workflows that match how banking deal teams actually work
- ✓Marquee customer base including Rothschild, Lazard, Jefferies, Moelis and Nomura
- ✓Outputs grounded in licensed institutional data with audit trails
- ✓Heavily funded ($300M+, reported $2B valuation), reducing vendor-viability risk
Cons
- ✗Opaque, quote-based pricing with no self-serve tier or public trial
- ✗Deal-side focus makes it a weaker fit for asset managers, hedge funds and lending
- ✗Implementation takes weeks of integration, permissions and data-entitlement work
- ✗Depends on third-party model providers and faces incumbents like FactSet and Bloomberg bundling their own AI
Pricing
Enterprise (pilot, team or firm-wide)
Contact for pricing
- ✓Felix agent
- ✓Research and modelling workflows
- ✓Institutional data integrations
- ✓Custom deployment with forward-deployed support
Rogo publishes no list pricing; contracts are quote-based, multi-year and priced per seat. Sacra estimates roughly $3,300 per seat per year for investment-banking users, and some data feeds require the customer's own third-party licences on top.
Security & Compliance
Sources
This page was written from 9 sources, 6 on domains other than rogo.com.
- 1.rogo.com — rogo.comvendor
- 2.rogo.com — felixvendor
- 3.rogo.com — companyvendor
- 4.prnewswire.com — rogo raises 160m series d to scale the agentic platform for
- 5.siliconangle.com — rogo raises 160m speed financial analysis ai agents
- 6.fintech.global — rogo raises 75m series c to scale ai finance platform
- 7.sacra.com — rogo
- 8.aiagentsquare.com — rogo ai
- 9.jefferies.com — gabriel stengel on building the ai platform for investment b
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