Relationship intelligence for legal & professional services.

Aggregates public-domain signals about target companies and the people who work at them — then synthesizes them into personalized briefings and outreach hooks.

In active development · pre-revenue

What it does

DD CRM ingests roughly a dozen public-data streams per target company, classifies and routes signals via large-language-model passes, and assembles a current, source-cited dossier on each company and contact in your relationship graph.

Built for lawyers, business-development professionals, recruiters, and anyone whose work depends on relationship intelligence at depth rather than surface-level CRM hygiene.

Sources currently integrated

SEC EDGAR (10-K / 10-Q / 8-K / proxy) CourtListener USPTO patents Congressional testimony USAJobs + ATS postings USA Spending federal contracts Federal Register GitHub OSS commits Listen Notes podcasts Wappalyzer / engineering blogs LinkedIn graph (manual import)

Architecture

Data layer

SQLite primary store, Neo4j graph projection for relationship queries, S3 for large-content cache.

LLM stack

Anthropic Claude Sonnet for synthesis, Google Gemini Flash for high-volume classification, faster-whisper for podcast transcription.

Compute

EC2 g6.xlarge spot for Whisper inference across multiple AWS regions; SQS for distributed work coordination.

UI

Flask dashboard with per-contact and per-company views; planned web UI for productized release.

Status

DD CRM is in active development by Jake Nelson, a JD candidate at the University of Maryland Carey School of Law transferring to Georgetown Law. The platform is currently used internally for company research and professional networking.

Productization for individual practitioners (lawyers, BD, talent) is on the near-term roadmap. Public availability and pricing will be announced here.