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AI Lease & Contract Intelligence for Property Managers is a local web application that converts rental agreements into structured, searchable data. Users upload PDF or TXT leases, and the system extracts tenant, property, rent, security deposit, lease dates, notice periods and renewal terms, clearly marking any missing or uncertain details rather than inventing values.
The platform includes a RAG-based contract assistant that answers questions with cited source passages, using a local Ollama model when available and keyword retrieval as a fallback. Automated review flags surface unclear clauses and missing information for human verification, while an expiry tracker and live dashboard help managers stay ahead of renewals and expirations.
Built with Python, Flask and SQLite, it runs entirely on the user’s machine with no paid APIs or subscriptions, keeping sensitive documents private.
I noticed the system flags missing lease fields instead of guessing values, which should cut down on manual verification headaches.
That was intentional. A confidently wrong value in a lease is riskier than a blank, so missing fields are flagged and uncertain ones are marked Verify, with the source text shown. It makes review faster and more focused.”
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I ran a session with my team on how to build a team of AI agents, and how to treat them so they actually deliver.
What we've seen running this setup on client work:
→ Agents running 24/7
→ 3B+ tokens in 6 days
→ A 2-week milestone done in 3 days
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Treat agents like teammates, not software.
Give them a clear goal, the right context and tools they're comfortable with.
Tell them the goal, never the solution.
Let the agents propose the options. You make the call.
Talk to one agent, not ten.
A central PM agent takes the goal and coordinates the rest.
Solve today's problem.
Don't build the perfect agent on day one. Start small and let the team grow with the work.
Don't be the bottleneck.
Review at milestones, not every task.
For clients, this changes the pace. My job is understanding the problem and making the decisions. The agents handle the execution.
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Building something and want to move faster with an AI-first team? Let's talk.