We've expanded Deliverables AI to process much larger data rooms. This update lets investment banking and private equity teams work with thousands of documents simultaneously.
Why We Built This
As more large firms and buy-side teams use our platform, we've seen their data rooms grow. What started as a few dozen documents has become hundreds of files plus external research materials.
Users told us they needed to analyze their entire data rooms without sacrificing the quality of insights.
Technical Challenges
Large document sets create real technical problems, especially with financial materials.
Financial documents like SEC filings, annual reports, and transaction ledgers contain complex information with numbers, tables, and specialized terminology. Standard processing methods struggle at scale:
- Context Gets Lost: Breaking documents into small pieces can separate related information. A statement about "3% revenue growth" might get disconnected from which company or time period it references.
- Tables and Structures Break: Financial reports have varied layouts that resist simple processing. Tables split incorrectly lose their meaning, and figures get separated from their explanations.
- Finding Relevant Information: As document collections grow to thousands of files, search accuracy often declines, making relevance harder to determine.
How It Works
The updated system processes substantially larger data rooms while keeping information in context.
Here's what it does:
- Better Indexing: We index thousands of documents without losing their structure.
- Context Preservation: Instead of creating disconnected fragments, we keep the context around key information.
- Better Search Results: When you search across thousands of documents, the system finds information relevant to your specific question.
- Complete Documents: We use complete documents when they contain important information rather than showing isolated fragments.
Under the hood, we use a hybrid approach called "adaptive context stuffing" that manages how documents feed into the AI engine.
Technical Approach
We combine several techniques to improve results:
Metadata Processing
Document segments include information about their source and context. This keeps parts of documents connected and ensures financial figures stay linked to their explanations.
Multiple Search Methods
The system uses both semantic understanding (the meaning behind your question) and keyword matching to find both concepts and specific terms. This matters for financial documents where exact terminology and numbers count.
Result Ranking
After finding potentially relevant information, an additional analysis step ranks results by importance to your question.
Flexible Context
Rather than using one fixed approach, the system adapts to each question and document set, bringing in the right context for accurate answers.
Real-World Uses
The larger document capacity works for both sell-side and buy-side teams:
Sell-Side Transaction Preparation
Process hundreds of documents from different departments to quickly find growth drivers, operational strengths, and potential issues. This helps develop stronger equity stories with supporting evidence from across the organization.
Buy-Side Due Diligence
Analyze large data rooms to find inconsistencies across financial statements, contracts, and management presentations. Spot connections between documents that manual review might miss.
Complex Carve-Out Transactions
Whether buying or selling, identify dependencies and transition requirements across numerous contracts and operational documents. Find overlapping obligations and critical transition items buried in the documentation.
Quality and Scale
In talking with investment bankers and PE professionals, we consistently hear that accurate, complete information matters more than small speed improvements.
Research on financial document processing confirms this – when searching thousands of documents, important information can get buried or fragmented.
While the system handles much larger document sets, it still works much faster than manual review.
Try It Yourself
If you've been limited by tools that only handle a subset of your documents, try running an entire data room through Deliverables AI.