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AI and financial services
AI systems for your financial services operations.|
Systems we run for financial services teams
Investment research and analysis
New names, filings, transcripts, and internal research are scattered across terminals, inboxes, and old memos. We pull the relevant evidence together, draft pre-earnings briefs, compare results against expectations, and update the house model before the analyst starts from a blank page. Every output is routed for review with the firm's prior thinking attached.
Research & retrieve
Draft & compare
Update & review
Investment thesis monitoring
An investment thesis is written at entry and rarely checked against what happens next. We turn each thesis into explicit assumptions, monitor filings, transcripts, revisions, and news against them, and flag the evidence when the case starts to drift. PMs get an early warning and a sourced bear case before the next investment committee.
Capture thesis
Monitor drift
Alert & review
Deal document production
Producing teasers, IMs, CIMs, and recurring deal updates means pulling numbers from models, CRM records, data rooms, and prior materials, then checking every page before it goes out. We assemble first drafts in the firm's format, keep figures and footnotes consistent, and route the material for banker review. Deal teams spend less time on document production and more time on positioning and client work.
Gather deal data
Build materials
Review & refine
Your systems can run on a dedicated Algebra platform or inside the tools your team already uses.