AI-Powered Property Sales Assistant for Primeland Properties

About the Company

Primeland Properties is a Lagos-based real estate company focused on connecting customers with genuine land and property opportunities. The business operates with a sales and operations team of approximately 10 to 15 people, managing property enquiries, available listings, customer requirements, property documentation, and follow-up activities across its sales operations.

Customer Challenge

As Primeland Properties expanded its property portfolio and generated more sales enquiries, sales representatives spent increasing amounts of time manually researching properties before responding to prospective buyers. Before working with Digitspot, a typical enquiry required staff to review customer requirements, search available property records, retrieve supporting documentation, identify suitable listings, prepare property information, and determine the next follow-up action.

The manual process typically required 20 to 30 minutes for each qualified enquiry. With approximately 80 to 100 property enquiries received each month, staff were spending an estimated 30 to 45 hours monthly on property research and enquiry preparation. This created a growing operational bottleneck, with response speed and sales capacity increasingly dependent on how quickly individual representatives could complete these repetitive tasks.

Partner's Solution

Digitspot implemented an internal Agentic AI Property Sales Assistant using Amazon Bedrock Agents, orchestrating Anthropic's Claude Sonnet 4.5 model. Staff access the assistant through Amazon API Gateway. Unlike a simple generative AI chatbot, the solution orchestrates multiple steps required to process a property enquiry: the agent interprets customer requirements, searches the available property knowledge base, retrieves relevant property information and documentation, identifies suitable listings, prepares a property brief, and generates appropriate follow-up actions for sales staff.

Amazon Bedrock Knowledge Bases provides access to approved property information and supporting documentation stored in Amazon S3. AWS Lambda enables the agent to execute approved business actions — searching listings, preparing briefs, and flagging missing information — while a separate Lambda function connects the workflow to Amazon DynamoDB, which maintains enquiry and workflow records including status, assigned representative, and follow-up due dates.

Amazon Cognito and AWS IAM control access to the internal application and its business data, while Amazon CloudWatch provides monitoring of application and agent activity. The agent supports sales staff rather than making autonomous property or commercial decisions, with authorised employees retaining responsibility for validating property information and determining final sales actions.

Results and Benefits

• Average property enquiry research and preparation time was reduced by approximately 60%, from 20 to 30 minutes to approximately 8 to 12 minutes per qualified enquiry
• The sales team reduced manual research effort by approximately 25 to 30 hours per month, allowing representatives to dedicate more time to prospect engagement and sales activities
• Staff can now process property requirements and retrieve relevant listing information through a single internal AI-assisted workflow
• Property briefs and follow-up actions are generated more consistently, reducing the risk of missed information and delayed sales activities
• The agent can coordinate multiple steps in the enquiry process while final property validation, customer engagement, and sales decisions remain under human oversight

About the Partner

Digitspot, established in 2011, continues to pursue its vision of helping both small and large-scale companies leverage cloud solutions to drive growth and innovation. As an AWS Advanced Partner, Digitspot remains committed to delivering world-class cloud strategies and implementations.