See how AI agents can help real estate investors and aquisition teams automate underwriting, offer generation, outreach, and acquisition workflows at scale.
Real estate AI agents are execution systems powered by AI that do work for you. Finding leads, analyzing properties, sending offers, managing replies, and flagging promising leads that need human attention are all tasks that an AI agent get do for you.
Our AI Agent is built for aquisition work just like this. It automates core real estate workflows allowing teams to scale deals without having to scale head count. It's packaged execution that pulls on market listings, underwrites them, calculates ARV, rehab, and MAO, formulates the offer, sends the offer directly to the listing agent through text and/or email, manages responses, and continously follows up.
Pulls on market listing
Dottid AI underwrites the property and applies your buy box rules and thresholds.
It calculates ARV, rehab, and MAO from the underwriting output.
It drafts an offer from those numbers and the rule set your team uses.
It sends the offer to the listing agent.
It monitors inbound replies and watches for counteroffers or new terms.
It processes the response, flags exceptions, and routes promising leads for a rep to review.
04 Operator Use Case
An acquisition team is working a steady stream of residential investment deals and wants to move faster without adding another analyst and another inbox owner. They route each property into Dottid AI, set their buy box around price, rehab ceiling, and MAO thresholds, and let the system underwrite the file before anyone spends time drafting an offer.
If the numbers clear, the offer is generated and sent. If a listing agent comes back with a counteroffer inside the team’s tolerance band, Dottid AI can process it and keep it moving. If the reply breaks a threshold, changes terms, or needs judgment on exception handling, it lands in the review queue. The team still reviews the edge cases, but they are not spending the day on every property just to find the few that deserve attention.
Manual acquisition
Manual acquisition is limited by headcount and human capactiy. The number of cold callers or size of your underwriting team directly correlate to the number of offers sent and deals closed. Employee turnover and training is a never ending cycle.
Dottid AI workflow
With electricity and an internet connect there is no limit to the amount of offers made, responses managed, leads analyzed and deals closed. Now with over 1.9 million properties actively listed in the US and an AI agent to carry the workload aquisitions no longer starts with a lead list but with a real seller, ready to close.
More offers sent without adding one manual drafting step per property.
Faster acquisition throughput because underwriting, sending, and reply handling do not sit in separate queues.
Less inbox drag when responses, counteroffers, and exceptions are processed into a review queue instead of buried in email.
Cleaner review cycles because only threshold misses and unusual terms need human attention.
More volume handled without proportional headcount growth across underwriting and follow-up work.
It is the use of software and AI agents to move acquisition work across underwriting, offer generation, sending, response monitoring, and surfaced opportunities. The practical boundary is important: standard paths can be automated, but unusual terms, threshold misses, and judgment calls still route to human review.
Dottid AI can automate the standard acquisition path from intake through underwriting, ARV, rehab, and MAO calculation, offer drafting, offer sending, and response monitoring. Anything that falls outside your thresholds, such as a counteroffer that changes terms or a reply that needs exception handling, goes to the review queue instead of being closed out automatically.
It removes the repeated manual work that sits between a property arriving and an offer going out. One team can keep underwriting, drafting, sending, and reply triage moving at the same time because the system handles the standard path and only pushes exceptions to people for review.
Anything that breaks the team’s thresholds still needs human review. That includes unusual counteroffers, changed terms, underwriting edge cases, and deals that do not clear the buy box cleanly. The point is to review the exceptions, not every routine reply.
Choose AI agents when you want packaged execution now; choose API infrastructure when you need the logic embedded in your own stack. Agents fit teams that want underwriting, offer sending, and response handling to run out of the box, while API infrastructure fits teams and builders that want Dottid AI logic inside their own acquisition system and review flow.
Dottid AI
Run a property through Dottid AI by entering the address and testing the underwriting engine. That is the fastest way to see how the system applies your buy box, calculates the file, and decides what should move into review.
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