Aareon builds AAVA, an AI virtual assistant integrated into its German property-management ERP, using Amazon Bedrock
Aareon· GermanyAmazon Bedrock · Amazon Nova · Anthropic Claude
Aareon, a Germany-headquartered property management software provider, integrated an AI virtual assistant called AAVA into its German ERP solution Wodis Yuneo using Amazon Bedrock. AAVA lets real estate housing company customers query documents, request information through chat, automate processes, and accelerate workflows -- including scheduling appointments between tenants and craftsmen, coding invoices, analyzing images to draft damage reports, and sorting incoming email, with both text and voice support. Aareon uses various LLMs available through Bedrock, including Anthropic's Claude models and Amazon Nova models, testing and selecting models by complexity and price performance for each use case (for example, a higher token-limit model for calculating service charges). The Bedrock deployment runs in the AWS Germany (Frankfurt) Region to help meet GDPR requirements, with customer data not used to train or improve the underlying models. The first version of AAVA was built in 4 weeks and announced to customers within 6 months, developed with support from AWS Partner Reply.
Overview
Aareon, a Germany-headquartered property management software provider, integrated an AI virtual assistant called AAVA into its German ERP solution Wodis Yuneo using Amazon Bedrock. AAVA lets real estate housing company customers query documents, request information through chat, automate processes, and accelerate workflows -- including scheduling appointments between tenants and craftsmen, coding invoices, analyzing images to draft damage reports, and sorting incoming email, with both text and voice support. Aareon uses various LLMs available through Bedrock, including Anthropic's Claude models and Amazon Nova models, testing and selecting models by complexity and price performance for each use case (for example, a higher token-limit model for calculating service charges). The Bedrock deployment runs in the AWS Germany (Frankfurt) Region to help meet GDPR requirements, with customer data not used to train or improve the underlying models. The first version of AAVA was built in 4 weeks and announced to customers within 6 months, developed with support from AWS Partner Reply.
The challenge
Aareon saw the potential for AI to automate repetitive daily tasks for its customers -- real estate housing companies that manage multiple rental properties -- and sought to help them accomplish all property management processes in one place, reducing manual workflows such as filing damage reports and scheduling appointments.
The solution
Aareon integrated an AI virtual assistant, AAVA, into its German ERP solution Wodis Yuneo by connecting the backend to Amazon Bedrock, using large language models including Anthropic's Claude models and Amazon Nova models. The company tests LLMs and selects the model with the best accuracy and price performance for each use case, for example a higher token-limit model for calculating service charges. The Bedrock deployment runs in the AWS Germany (Frankfurt) Region to help meet GDPR requirements, and customer data is not used to train or improve the underlying models. Aareon accelerated the project by working with AWS Partner Reply to build the solution interface.
Reported business value
AAVA helps customers query documents, request information through chat, automate processes, and accelerate workflows, including scheduling appointments between tenants and craftsmen, coding invoices, analyzing images to draft damage reports, and sorting incoming email, with both text and voice support. Aareon developed the first version of AAVA in 4 weeks and announced it to customers within 6 months. Overall, the company's AI solutions help reduce repetitive work, freeing customers to focus on meaningful customer interactions.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other real estate entries in the register.
Matching home buyers with their dream house
Compass, a real estate technology company, uses the Databricks Data + AI Platform to deliver predictive intelligence that identifies homeowners likely to sell, helping agents optimize marketing budgets and outreach strategies, replacing siloed ad hoc data lakes with a unified platform.
CompassDatabricks Data + AI Platform · Unity Catalog · Databricks SQL
First American Data & Analytics fine-tunes open-source LLMs on Databricks, cutting extraction costs 70%
First American Data & Analytics (DNA), a property-centric information provider to the real estate and title insurance industries, used the Databricks Data + AI Platform to fine-tune open-source LLMs (Mistral, Llama 3, Llama 3.1) for page-level classification and extraction of 100+ data fields from roughly 4 million historical title policy images dating to the 1930s. Using Delta Lake, Databricks Model Training, Managed MLflow, and serverless Model Serving on about 50 GPUs, the team fine-tuned models in two weeks versus the two-plus months it previously took on other platforms. The project cut extraction costs by 70%, reduced project completion time by 75% (months to weeks), and increased the number of data elements extracted tenfold.
Gazelle: Smart validation and 99.9%-accurate property descriptions with Gemini
Gazelle, a Swedish startup automating property documentation for real estate agents in Sweden and Norway, uses Google's Gemini 1.5 Pro to extract key information from lengthy property documents like building-inspection and electricity reports and generate sales content. Gemini increased output accuracy from less than 95% to 99.9%, reduced content generation time from four hours to 10 seconds, and helped Gazelle launch four new products in under a year, saving brokers 4 to 6 hours of manual work per property.
ECE Group rolls out Microsoft 365 Copilot, with 70 percent of pilot users wanting to keep their licence
German real estate and shopping centre operator ECE Group rolled out Microsoft 365 Copilot after manual information searches and data compilation slowed daily work. It went from budget approval to first pilot training in three months, using Copilot for meeting minutes, customer presentation ideas and press release drafts. The Microsoft customer story reports that around 70 percent of pilot participants want to continue using it.
ECE Group· GermanyMicrosoft 365 Copilot
Was this helpful?
Your feedback helps us improve our use case database