Vespera

Local-first AI due diligence.

Review a dataroom without sending confidential documents to a third-party AI provider.

pip install vespera
vespera review ./dataroom

Vespera scans the documents in a local folder — contracts, board minutes, NDAs — and produces a structured due diligence report with evidence-backed findings, each linked to its source document and page. All analysis runs on your machine via Ollama. Document contents never leave your network.

What it does

Vespera performs the first-pass review of a document collection for M&A, VC, and PE due diligence:

• Recursively discovers PDF, DOCX, TXT, and Markdown documents
• Extracts text and analyses it with a local LLM
• Produces structured findings across categories including change-of-control clauses, termination rights, assignment restrictions, exclusivity, IP ownership, material liabilities, missing signatures, and cross-document inconsistencies
• Writes a Markdown report and a machine-readable JSON evidence file

Vespera

Reviewing ./dataroom

Documents found: 6
Documents processed: 6

Findings:
- Change-of-control clauses: 1
- Termination rights: 3
- Missing signatures: 1
- IP ownership / assignment: 2

Report: vespera-output/report.md
Evidence: vespera-output/findings.json

All document analysis was performed locally.

Every finding carries its category, severity, a short verbatim evidence excerpt, a confidence score, and the source file and page.

Privacy model

• No cloud calls for analysis. Inference runs on a local Ollama server (localhost by default).
• No telemetry, no accounts, no database. Vespera reads your documents and writes two output files. That's it.
• The only network activity you'll ever need is ollama pull to download a model once.

Quick start

1. Install Ollama and pull a model:

   ollama pull qwen3:8b
   

2. Install Vespera (Python 3.12+):

   pip install vespera
   

3. Review a dataroom:

   vespera review ./dataroom
   

Try it on the included synthetic example:

git clone https://github.com/VesperaSystems/vespera
cd vespera
vespera review ./examples/sample-dataroom

Commands

vespera review PATH [--model qwen3:8b] [--output vespera-output] [--host http://localhost:11434]
vespera models      # show default + locally installed Ollama models
vespera --version

Supported document types

Scanned image-only documents are not analysed in this version (no OCR).

Limitations

Vespera is automated document triage. It is not legal, financial, or investment advice, and it does not replace review by qualified professionals. Local language models can miss issues and misread context; findings must be verified against the source documents. Vespera is designed to tell a human professional where to look first — not to make decisions.

Roadmap

• OCR for scanned documents
• More document formats (XLSX, EML, PPTX)
• Additional local model providers (llama.cpp, MLX)
• Configurable finding categories and custom review checklists
• Multi-language document support

Development

git clone https://github.com/VesperaSystems/vespera
cd vespera
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pytest

The LLM is behind a tiny provider interface (vespera/llm/base.py), so tests inject a fake provider and never require Ollama.

License

Apache-2.0