AI for finance work that survives review.
For M&A, corporate finance, private equity, and capital-markets teams already testing frontier tools. ogram foundation turns that usage into an integrated operating layer.
One required field. We respond through a controlled channel.
Claude and Codex, made operational.
Frontier platforms are already in the hands of serious professionals. ogram foundation turns that informal use into a configured operating perimeter.
Claude
Structured use for long documents, client material, diligence packs, correspondence, and professional memoranda.
Codex
Firm-specific automations, data preparation, workflow tools, and controlled access to internal systems.
The finance workflows where drift is expensive.
The diagnostic maps repeated analytical work, source systems, and review points before frontier platforms are placed into the daily stack.
Investment memos
Source-grounded deal narratives, risks, comparables, and committee-ready summaries.
Comps analysis
Controlled synthesis around peer sets, precedent transactions, and valuation notes.
Diligence reports
Cross-source issue tracking, evidence summaries, and recoverable workstreams.
Model commentary
Explanatory notes around assumptions, sensitivities, and output changes.
Pitch material
Drafting support for decks, market pages, company profiles, and appendices.
Placed next to the finance stack.
The integration names categories first. Exact market-data and data-room connections are confirmed only when credentials, contracts, and permissions allow.
Spreadsheet estate
Excel / Sheets models, templates, assumptions, and operating extracts.
Presentation layer
PowerPoint-style materials, committee decks, pitch books, and reporting packs.
Market data
Bloomberg / LSEG / CapIQ / PitchBook-style sources where authorised.
Data rooms
Diligence documents, Q&A exports, management presentations, and source folders.
Internal lake
Firm datasets, approved extracts, and controlled analytical workspaces.
The legal and technical perimeter comes first.
The campaign promise is not generic adoption. It is adoption under a defensible operating model: DPA, retention policy, residency, auditability, and source boundaries mapped before scale.
DPA path
The data-processing position is clarified before production use, with firm obligations reflected in the engagement.
ZDR policy
Zero-retention requirements are mapped at platform and workflow level before sensitive work is introduced.
Model portability
Claude and Codex are integrated without making the firm dependent on a single provider or closed workflow.
Start with a finance AI diagnostic.
A structured map of workflows, data surfaces, and privacy obligations before Claude or Codex is embedded.
Request diagnostic
One required field. We respond through a controlled channel.