AI agents / Research
Research that runs every day without tying up the team
US real estate research and outreach
Two AI agents collect grants, investor, and land opportunities on a daily schedule. Results converge into an Airtable pipeline, where Claude scores each opportunity against fund criteria. Qualified opportunities move into outreach preparation and a human review step before one daily approval briefing goes out. Opportunities below the scoring threshold are archived automatically.
The operational problem
The team needed structured research across grants, investors, and land opportunities without receiving a stream of disconnected alerts.
How the system handles it
Two AI agents collect and structure opportunities, Claude scores them against the fund criteria, and the workflow prepares outreach for human approval.
ENGINEERING DECISIONS
Logic & boundary design
Unstructured data processing, context extraction, and reasoning.
Deterministic conditions, status routing, and strict validation.
Final approval triggers, manual overrides, and audit checkpoints.
API fallbacks, database connectors, and custom Python integrations.
SYSTEM OUTCOME
The team receives one approval briefing with the opportunities worth reviewing.
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