Legal & Compliance Document Summarizer
An LLM-and-extraction layer over the FO's legal document corpus — summarizes incoming documents, extracts and tracks key clauses, surfaces anomalies against precedent, generates working drafts for routine review.
- Engagement
- 6–10 week build · ongoing operation
- Built for
- FO General Counsel · Outside counsel · Controller
Trust documents, family-office contracts, foundation governance, real-property documents, employment agreements — the legal corpus accumulates faster than the GC has time to read it. Routine review (lease renewals, vendor contract anniversaries, trust-amendment cycles) sits in a backlog.
What this is
A review layer over the FO's legal document corpus — built for the GC who reads everything but only has time to read the things that matter. Three layers:
- Document ingestion and summarization. Per-document summary in the GC's preferred style (length, focus, format), generated as documents enter the corpus.
- Clause tracking and anomaly flagging. Key clauses (term, termination, indemnity, change-of-control, beneficiary entitlement, distribution waterfall) extracted and tracked. Anomalies against the FO's precedent surfaced.
- Working-draft generation. For routine review (lease renewal letters, beneficiary notifications, standard vendor renewals), the engine drafts the working version; the GC reviews and finalizes.
How it's built
Document AI for layout-aware extraction, embedding-based precedent matching against the FO's historical document base, LLM-based summarization with controlled output style. Where the FO requires on-prem deployment, the LLM layer runs on local hardware; otherwise commercial-API inference with no-training tiers.
What you get
- The summarization pipeline running against new documents.
- The clause-tracking dashboard for the GC.
- The anomaly-flagging system with precedent comparison.
- The working-draft generator for the routine document classes the GC identifies.
- A documented confidentiality architecture for the FO's compliance team.
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
K-1 Extraction & Validation Engine
A document-AI pipeline that ingests the K-1 corpus as it arrives, extracts all 200+ fields with confidence scores, maps to the FO's chart of accounts, flags inconsistencies against partnership returns, and posts to AtlasFive (or your fund-accounting system) with audit trail.
- 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.
What buyers ask about this one.
Does this replace outside counsel?
No. Outside counsel does the judgment work — drafting, negotiation, novel-issue research. This handles the volume work — reading the contract before counsel does so the GC can focus the engagement on the parts that matter, summarizing meeting notes so the GC remembers what was discussed, tracking clause expirations so renewal review doesn't sit in a backlog.
What's the scope of 'legal documents' here?
Trust agreements and amendments, partnership agreements (the LP-side documents), real-property lease and purchase documents, employment agreements (household staff and FO employees), vendor contracts above a materiality threshold, regulatory correspondence (state filings, beneficiary notifications). Configurable per FO.
How do you handle confidentiality given the sensitivity of FO legal documents?
Documents stay in the FO's environment. The LLM layer runs against your infrastructure (cloud, on-prem, hybrid — your call) with no external data sharing. Where we use commercial models (GPT-class, Claude-class), we use API tiers that exclude inference data from training. Documented in the engagement.
What does the anomaly flagging actually catch?
Three patterns. (1) Off-precedent terms — a new vendor contract that differs materially from the FO's standard. (2) Clause expirations and renewal dates that need attention. (3) Cross-document inconsistencies — when a trust amendment and a partnership agreement conflict on a beneficiary's entitlement, for example. The GC reviews the flag; the engine doesn't make the call.
Pricing?
Scoped to document corpus size and review cadence. Discovery call covers both.
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