See how real estate acquisitions automation platform helps serious real estate investors automate underwriting, offer generation, outreach, and acquisition workflows at scale.
Dottid AI underwrites properties, applies buy box rules, drafts offers, sends them, monitors replies, and surfaces the deals that still deserve human review. It is not just underwriting software, and it is not just analysis software that helps investors look at deals faster.
Dottid AI comes in two modes. Use pre built AI agents when you want packaged acquisition execution: run a property through underwriting, calculate ARV, rehab, and MAO, generate the offer, send it to the listing agent, then keep tracking the inbox for replies and counteroffers. Use the API when you need that same underwriting and offer logic embedded inside your own stack, so your team, operators, or PropTech product can apply the rules inside existing workflows.
The choice is operational. If you want Dottid AI to handle the standard acquisition path now, use the agents. If you want to wire underwriting and response logic into your own system, use the API. For teams already standardizing deal intake and response handling, the relevant layer is the offer workflow that sits between underwriting and final review.
Enter the property or send intake data into Dottid AI.
Underwrite the deal and calculate ARV, rehab, and MAO against your buy box rules.
Check thresholds and flag anything that misses your limits or needs review.
Generate the offer based on the underwriting output.
Send the offer to the listing agent.
Monitor inbound replies, counteroffers, and response timing.
Process the response and route exceptions to a human.
Surface the opportunities that still fit the box and push them into the review queue.
04 Operator Use Case
An acquisition team is screening a steady flow of listings and wants every address underwritten the same way. They set ARV, rehab, and MAO thresholds, then let Dottid AI draft offers and send them on the deals that clear the box. If a property lands near the margin, misses a threshold, or comes back with unusual terms, it gets held for human review instead of moving automatically. If a listing agent sends a counteroffer, the team reviews the response, checks it against the buy box, and decides whether to escalate, revise, or pass. The goal is not to remove the acquisition team from the loop. The goal is to keep them focused on the properties and replies that actually need judgment.
Manual acquisition
Manual acquisition breaks when every property creates the same stack of work: underwrite the deal, draft the offer, send it, follow up, watch the inbox, and sort through replies. One delay is manageable. Fifty properties at once are not.
Dottid AI workflow
The bottleneck is not just analysis speed. Faster underwriting still leaves someone to apply the buy box, draft the offer, send it to the listing agent, monitor inbound responses, triage counteroffers, and decide which exceptions need review. That work compounds with volume. As deal flow rises, teams spend more time moving files between spreadsheets, inboxes, and follow-up threads than reviewing actual opportunities.
Run more acquisitions through the same team without adding a person for every new batch of listings.
Keep offers moving while replies and counteroffers are still fresh.
Get faster review on deals that miss thresholds, instead of burying them in the queue.
Push more qualified opportunities to the front of the line without slowing down the standard path.
Reduce the manual load around underwriting, offer drafting, and response triage.
Dottid AI can automate the standard acquisition path, but exceptions, unusual terms, and threshold misses still route to human review. That means the system can underwrite, apply your buy box rules, draft and send offers, monitor replies, and process routine responses, while a reviewer handles the edge cases that need judgment.
No. Underwriting is only the entry point. The operational value is that the same system can carry the deal forward into offer drafting, sending, reply monitoring, and response triage, so your team is not reworking the file by hand after analysis is done.
Choose the AI agents when you want packaged execution now and your team wants to run properties through a defined acquisition path without building the logic yourself. Choose the API when you need Dottid AI embedded in your own stack so your team can call the underwriting and offer rules from an internal tool or product. That choice matters because agents move faster to live execution, while API use requires implementation work but gives you control over where the logic runs.
Human review stays on the deals that miss a threshold, carry unusual terms, or come back with a counteroffer that does not fit the rule set. Those items do not disappear into automation; they get routed to a review queue so an acquisition lead can decide whether to revise, escalate, or pass.
No. Faster analysis helps, but the bottleneck is the stack of manual work after underwriting: drafting the offer, sending it, following up, checking replies, and deciding what to do with exceptions. If those steps still live in inboxes and spreadsheets, volume still breaks the team.
Dottid AI
Run a property address through Dottid AI and see the underwriting engine produce the next acquisition step.
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