Buy-side and sell-side analysts have quietly gotten access to Rogo (Goldman-adjacent), Hebbia Matrix (Point72, Centerview, D. E. Shaw), and Microsoft Copilot in Excel with Python. Every first-year IB analyst wants this stack. Every FP&A senior wonders when their turn comes. The content ecosystem is either vendor demos or "how to prompt ChatGPT for finance." Nothing on the actual workflow — LBO model auditing, CIM digestion, comps sourcing, IC memo drafting.
This hub is for the IB analyst or associate, PE associate, hedge fund analyst, corporate development lead, or FP&A senior who wants to use the modern AI finance stack the way top-decile analysts actually use it. It curates skills on auditing an LBO model in an hour instead of a night, digesting a 200-page CIM into an investment thesis, sourcing precedent transactions and public comps with Rogo, running a "read this and tell me what to think" pass over a data room with Hebbia Matrix, and drafting an IC memo that survives a Managing Director's red pen. Every skill is workflow-first and screenshot-verified.
Who this hub is for
IB analysts and associates (BB and boutique), PE associates, hedge fund analysts, corporate development leads, and FP&A senior analysts.
Rogo is optimized for banker workflows — precedent transactions, CIM analysis, IPO comps, sourcing. Hebbia Matrix is optimized for buy-side workflows — reading a data room, running the same question across 50 documents, building a comparative matrix. Sell-side and IB use Rogo more. Buy-side, PE, and hedge funds use Hebbia more. Big firms deploy both.
No — but it can compress a night of mechanical modeling into an hour. Copilot with Python in Excel is powerful for data cleanup, standard financial functions, and formula auditing. It is not yet reliable for building an LBO from scratch, adjusting a three-statement model for a new deal structure, or catching a subtle circular reference. Use it for grunt work, keep the senior thinking in a human head.
Two options. Option one: run the model through Copilot in Excel with data residency configured to your firm's tenant — nothing leaves your Microsoft environment. Option two: strip sensitive labels, feed anonymized sheets into Claude or ChatGPT for a "find every hardcoded number and flag inconsistencies with the assumptions tab" pass. Never paste a live deal name into consumer AI.
Upload to Claude Projects or a Rogo project. Ask for a structured summary: business overview, revenue drivers, unit economics, growth strategy, competitive positioning, financial highlights, key risks. Then ask targeted follow-ups — "walk me through customer concentration," "how does gross margin compare to public comps." You go from 200 pages to a working investment memo in about 90 minutes.
Rogo has this natively — enter the target company profile, get a ranked list of precedent transactions with EV/Revenue and EV/EBITDA multiples. For sanity-check, run the same query through Perplexity Enterprise with a source-preference for CapIQ, PitchBook, and press releases. Manually verify the top 5 in your subscription database (CapIQ or PitchBook) before putting them in a deck.
Increasingly, first-year IB analysts are evaluated on hours-saved per week and turnaround speed on standard deliverables. An analyst who can turn a live-deal CIM around in 12 hours instead of 36 gets staffed on better deals and gets a stronger promotion case. The 2026 promotion criterion is not "do you use AI" but "how much leverage do you get from AI in a live deal environment."