Family Report Drafter
An LLM-powered drafting layer that produces quarterly family reports, capital-call notices, tax-footnote narrative, and ad-hoc communications — trained on the FO's historical document structure and preferred tone, with the CFO finalizing.
- Engagement
- 6–10 week build · ongoing operation
- Built for
- CFOs · Operations directors · Communications leads
Quarterly family reports are written from scratch every quarter — performance summary, allocation commentary, year-over-year context, family-member-relevant narrative. The CFO drafts the first version; staff revises; legal reviews; the principals get a polished document that took a person-week to produce.
What this is
The output layer of the suite — the place where the data flows through to the family. Three components:
- Tone-trained drafting. Fine-tuned on the FO's historical report corpus. Drafts read in the FO's voice, not in a generic LLM voice.
- Data-grounded number insertion. Numbers come from the canonical data layer via structured templating. The LLM never generates a financial figure.
- Per-recipient parameterization. Common report drafted once, framed per recipient (principals, family members, advisors) with appropriate detail and tone.
How it's built
Commercial-API LLM (Claude-class, GPT-class) with the FO's report corpus as a fine-tuning anchor, or on-prem Llama-class with the same approach. Structured templating layer (Jinja-class) for the data-insertion points. Per-recipient configuration as a declarative rule set. Output formats: PDF, Word, HTML — whatever the FO needs for downstream distribution.
What you get
- The fine-tuned drafting model deployed to your FO.
- Templates for the canonical report types (quarterly performance, annual summary, capital-call notice, tax-footnote narrative).
- Per-recipient parameterization configured to your family's preferences.
- The CFO review UI with markup-and-finalize workflow.
- Ongoing tone calibration as the report corpus grows.
Engagement is shape, not list.
Length and price are functions of the data and the destination. The shape below is the typical engagement.
- Length
- 6–10 week build · ongoing operation
- Lead
- Bogdan
- Cadence
- Async, weekly
- Bar
- Production
Scoped during the discovery call against the actual data and the operation it integrates with.
Principal engineer. Architecture and most code ships through one keyboard.
Written updates between, calls when the decision needs the room.
Async correctness, capacity under burst, observability at every boundary.
Products this composes with.
Same suite, or vertical-specialized versions in another.
- Same suite · Family Office Suite
Multi-Entity Consolidation Platform
A consolidation platform that ETLs from each entity's source-of-record system, normalizes to a unified chart of accounts, handles FX and intercompany eliminations, surfaces per-family-member and per-asset-type views, and enforces privacy partitions where the structure requires them.
- Same suite · Family Office Suite
Conversational Portfolio Assistant
An LLM-powered natural-language interface on top of the Multi-Entity Consolidation Platform — accepts questions in plain English, queries the underlying data, returns answers with the supporting numbers and audit links.
- Same suite · Family Office Suite
Liquidity & Cash Forecasting Engine
A liquidity forecasting model trained on the family's inflow and outflow patterns plus macro signals (Fed rates, sector benchmarks for investment distributions) — surfaces predicted shortfalls and excesses 60 days ahead with the driving factors documented.
What buyers ask about this one.
How does it preserve the FO's voice?
Fine-tuned on the FO's historical report corpus — typically two to three years of prior quarterly reports plus a curated set of preferred-tone examples. The drafts come out reading like the FO's previous reports because the model has learned the FO's voice. Where principals or family members have individual preferences (more conservative tone, specific phrasings to avoid), those are encoded as constraints.
What about per-family-member personalization?
The reports can be parameterized per recipient — different family members see different levels of detail, different commentary depth, different attached schedules. Drafted from a common data source with recipient-specific framing.
Does this hallucinate numbers?
Numbers come from the data layer (Multi-Entity Consolidation Platform or your equivalent), inserted via structured templating — not generated by the LLM. The LLM writes the prose around the numbers. Hallucinated numbers are not a failure mode of this architecture.
How much CFO time does it actually save?
Typical pattern: from a person-week of drafting to a few hours of review and revision. The CFO still owns the final document and the strategic framing; the engine handles the structure and the routine prose.
Pricing?
Scoped to report cadence, recipient count, and the breadth of document types covered. Discovery call covers all three.
If the deliverable matches the gap, the next step is one call.
We'll scope length and price against your data and the operation it integrates with. No retainer, no fishing.
Bogdan and team · async-first · OP—2026