Dottid AI

Real Estate AI API

See how our real estate AI API helps serious real estate investors automate underwriting, tailor offers to preset buy boxes,and powers acquisition workflows at scale.

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Dottid AI

Real estate acquisition automation

Our Real estate AI API is execution infrastructure for acquisition teams. It allows an agent to underwrite properties and applies buy box rules so offers can be generated at scale all without human input.

Dottid AI gives you two ways to run acquisition work. Use real estate AI agents when you want packaged execution now: the system underwrites, estimates ARV, rehab, and MAO, generates offers, sends them, watches inbound responses, processes replies, and pushes exceptions into a review queue. It also allows you to plug in our real estate underwriting API when you want that same underwriting and offer logic embedded in your own acquisition stack, with your own intake, rules, and review flow controlling where the logic runs. It allows users to build their own agents and use our API to power the offer logic.

The choice matters operationally. Teams with active deal flow and no time to build usually start with agents. Teams that already have internal systems, portfolio tools, or PropTech products use the API when they need Dottid AI logic to sit inside their own underwriting queue, offer workflow, or response triage layer.

Route a property into the intake queue.

Run underwriting on the address and property data.

Apply buy box rules, thresholds, and exception checks.

Calculate ARV, rehab, and MAO.

Generate an offer from the underwriting output.

Send the offer to the listing agent.

Monitor inbound replies and counteroffers.

Process responses, flag misses, and route unusual terms to human review.

Surface viable opportunities into the review queue.

04 Operator Use Case

Real Investor Use Case

An acquisition team runs every inbound property through Dottid AI before a human touches it. Their buy box might allow small residential investment properties only when the ARV, rehab range, and MAO fall inside preset thresholds. Anything that clears those rules gets underwritten, an offer gets drafted, and the offer goes out to the listing agent the same day. If a counteroffer comes back inside the normal range, the system can process it and move it to the next review step. If the terms drift outside the box, the deal goes to a person. The team is not reviewing every property by hand; they are reviewing the exceptions and the opportunities that make it through the threshold gate.

Manual acquisition

Work stacks up after analysis.

Manual acquisition breaks when the same team has to underwrite every property, draft every offer, send every offer, then watch inboxes for replies and chase follow up on top of that. Under volume, those tasks stack fast. A slower underwriting queue delays offer drafting. Offer drafting delays sending. Sending delays reply monitoring. Reply monitoring delays counteroffer review. Then missed replies and manual follow up create more drag.

Dottid AI workflow

The standard path keeps moving.

Faster analysis alone does not fix that. A team can score deals quickly and still lose execution time if offers are not drafted, sent, tracked, and triaged without human handoffs. The bottleneck is the full acquisition path, not just the spreadsheet.

Send more offers without adding the same amount of underwriting and follow up staff.

Keep reply handling out of the main inbox and into a defined review queue.

Cut the lag between intake, underwriting, offer drafting, and offer delivery.

Review fewer dead ends and spend more time on deals that clear thresholds.

Handle more acquisition volume without turning every new property into another manual work item.

What is real estate acquisition automation?

It is software that moves acquisition work from intake through underwriting, offer generation, offer sending, and reply handling without requiring a person to touch every step. The practical boundary is still important: routine properties and standard terms can run through the system, but unusual terms and threshold misses should move into human review before anything is finalized.

What parts of the acquisition workflow can Dottid AI automate?

Dottid AI can automate the standard acquisition path: underwrite the property, estimate ARV, rehab, and MAO, generate the offer, send it, watch for inbound replies, and process normal responses. When a reply includes a counteroffer, a term outside the buy box, or an exception that fails your thresholds, it routes to a person instead of forcing an automated decision.

How does Dottid AI help teams send more offers without adding headcount?

It removes the per-property work that usually eats acquisition time: repeated underwriting, manual offer drafting, sending each offer by hand, and checking inboxes for responses. That matters when deal volume rises, because one operator can keep moving properties through the queue while the system handles the repeat work and pushes only the exceptions back for review.

What still needs human review in an automated acquisition workflow?

Anything outside the normal playbook should still be reviewed by a person. That includes deals that miss thresholds, counteroffers with unusual terms, pricing that does not fit the buy box, or replies that need escalation. The system should clear the standard path and leave the edge cases in the review queue.

What is the difference between AI agents and API infrastructure?

Choose AI agents when you want packaged execution now. Choose API infrastructure when you need the underwriting, offer, and response logic embedded inside your own stack. Agents fit teams that want to start moving offers and replies quickly; API fits teams that already have internal workflows and want Dottid AI logic to run inside them instead of around them.

Dottid AI

Try the AI underwriter

Run a property through Dottid AI and see how the underwriting engine handles the address, thresholds, and offer logic before you build around it. Start by entering a property address.

Try the AI underwriter

Built for

Acquisition teams
Real estate investors
PropTech workflows