Reapit AI integration: what estate agents can actually build today

Reapit is the most widely used CRM for high-volume UK estate agents, and the question most Reapit users are raising right now is the same: what can AI actually do on top of what we already have? Reapit AI integration is not a single product you install. It is a set of possible connections between your live property data and an AI agent that can act on it. This post covers what those connections look like, what they can and cannot do, and how to think about scoping a build that adds real capacity without breaking the workflow your team has spent years refining.

What Reapit already gives you, and where it stops

Reapit AgencyCloud holds a significant amount of data: contacts, properties, offers, diary entries, communications, pipeline stages. The platform has introduced some AI-assisted features in recent releases, mainly around communication drafting and reporting. These are useful starting points, but they have a defined ceiling.

The built-in features are designed for the broadest possible user base. They cannot be trained on your agency's voice, they do not learn from the specific patterns of your pipeline, and they have no mechanism to act autonomously on a trigger. An email drafting tool inside the CRM still requires a negotiator to open the record, initiate the draft, review it and send it. It removes some of the writing effort. It does not remove the bottleneck.

The gap most Reapit agencies find is at the workflow level. The CRM holds the information. What is needed is an agent that reads that information, decides what action is appropriate, takes the action, and logs the result, all triggered by an event rather than a person manually starting the process. Reapit's Foundations API marketplace is what makes this possible. It exposes the data and event hooks a third-party agent needs to operate alongside AgencyCloud without requiring you to move CRM or rebuild anything from scratch.

What a Reapit AI integration actually does

The core architecture for any AI agent running on top of Reapit follows the same pattern: trigger, read context, reason, take action, log.

The trigger is an event in AgencyCloud. A new enquiry lands. An offer is submitted. A property status changes. A diary entry is created. A defined number of working days passes without a status update from a solicitor or lender. The agent reads the relevant records from the Foundations API, combines them with any relevant email or message history, and decides what to do.

The action depends on the job the agent is built for.

For lead qualification, the trigger is an inbound enquiry from Rightmove or Zoopla. The agent reads the property record in Reapit, constructs a qualified response in your agency's voice, sends it within seconds, and writes the exchange back into the contact record in AgencyCloud. The negotiator opens Reapit and finds the conversation already logged, with buying position and timescales captured from the buyer's replies.

For sales progression, the trigger is a time window. If a solicitor has not replied within a defined number of working days, the agent reads the conveyancing chain record in Reapit, drafts a chaser, and delivers it to the negotiator's drafts folder for approval or, where auto-send has been explicitly configured, sends it and logs the result. Chain risk flags surface through Slack or a simple dashboard rather than as buried CRM notes that require a negotiator to go looking.

For vendor updates, the trigger is a schedule combined with pipeline events. A vendor's weekly update is generated from the current state of their record in Reapit: what has happened since the last message, what is pending, what the next step is. It lands in the negotiator's email drafts with one click to approve and send.

The key point is that none of this requires you to leave Reapit. The data lives in AgencyCloud. The agent reads it there, acts, and writes back. From the negotiator's perspective the CRM is the same. The difference is in what appears in it and when.

What it looks like for a Reapit agency

Take an independent running forty active instructions. They receive around twenty portal enquiries per week across Rightmove and Zoopla. Three negotiators handle progression, vendor contact and enquiry response alongside valuations and viewings.

Before a Reapit AI integration, Monday mornings begin with a backlog of weekend enquiries in the shared inbox and a stack of solicitor chasers to write. Vendor calls arrive from mid-morning from clients who have not had any contact over the weekend.

After the integration, the pattern is different.

Weekend enquiries are answered within seconds as they arrive. Each response is written from the live Reapit property record, accurate to the current listing status. Buyers who confirm availability and buying position are offered viewing slots pulled from Geo Diary. The appointments land in AgencyCloud before the office opens on Monday.

Solicitor chasers that crossed the five-working-day mark over the weekend are drafted and waiting in the negotiator's email drafts folder for review. Three vendor updates went out on Friday afternoon, each drawing on the current pipeline note in Reapit, naming what happened that week and setting an expectation for the next.

The negotiators start Monday looking at a CRM that has already moved while they were away from the office, not a backlog that accumulated while they were.

Compliance and integration reality

Running an AI agent connected to a live Reapit system has clear obligations that need to be designed in from the start.

UK GDPR. The Foundations API connects to contact and transaction records that contain personal data. Any agent reading or writing to those records needs a documented lawful basis, a data processing agreement with the AI provider, and data residency in the UK or EU. Sortd uses UK and EU infrastructure by default. No client data from your Reapit system is processed on US servers.

AML. Identity verification and source of funds decisions remain with your team and are documented in AgencyCloud as they would be now. The AI does not make AML determinations. It can surface prompts and flag missing steps, but the conclusion is always a person's responsibility.

TPO. The Property Ombudsman's code requires that clients are dealt with accurately and honestly. Every message template and agent behaviour is agreed with your team before it touches a live record. The agent is tested against real Reapit data from your pipeline before anything reaches a vendor, buyer or solicitor. The Negotiator and Property Industry Eye both carry regular coverage of TPO guidance and enforcement patterns across the sector.

On integration specifics: Sortd uses Reapit's Foundations API for data access and event subscriptions where available. For diary and viewing management, Geo Diary access is included in the build scope. Where the API does not yet expose a specific data point, workflow gaps are handled with staff-style automation that mirrors exactly how a negotiator would interact with the system directly.

How to evaluate a Reapit AI build

The right question to ask any supplier is simple: where does the data come from, and where does the output go? If the answer involves a spreadsheet export or a separate dashboard your team has to check independently of AgencyCloud, it is not a Reapit AI integration. It is a parallel system, and parallel systems create drift.

A real Reapit integration reads live records from AgencyCloud, acts on real events, and writes results back to the same records your team is already using. The workflow does not fork. The negotiator does not have to go somewhere else to see what the AI did.

Sortd's starting point is a discovery call where we map your current Reapit usage, identify the highest-friction jobs in your pipeline, and scope a working version of the agent. We build the MVP, wire it into your Reapit data in a test environment, and run it before anything touches a live contact.

If Reapit AI integration is something you are evaluating for your agency, start with a conversation.