Unlocking Renter Insights: How Mission Helped LeaseLock Build an AI-Powered Customer Intelligence Foundation

LeaseLock, an innovative InsurTech company eliminating security deposits for property owners thus making apartments more affordable for renters, partnered with Mission to develop an AI-powered system for comprehensive customer intelligence. Through Mission's AWS expertise, LeaseLock successfully validated combining multiple data sources with large language models (LLMs) to gain holistic insights into customer behavior and satisfaction. The engagement transferred critical AI capabilities and architectural patterns that LeaseLock's team has applied to production systems. Claims efficiency and adjudication processes using these same data integration and sentiment analysis techniques are now used by industry leaders.

LeaseLock is the only true lease insurance provider for rental housing. Our AI powered underwriting program, LeaseLock Shield™ , predicts risk and optimizes coverage for properties and portfolios. Owners and operators gain notable profit protection while accelerating leasing, minimizing burden, and removing reputation and legal risk. With over $14 billion in leases insured, LeaseLock is reshaping the way the rental housing industry manages financial risk, while delivering significant benefits to renters. As an accredited GRESB partner, LeaseLock is dedicated to improving housing accessibility by offering renters greater financial flexibility while protecting properties against the risk of bad debt. Learn more at www.leaselock.com.

LeaseLock was developing its AI strategy when a specific use case emerged requiring specialized expertise in combining datasets with large language models. The company leveraged its existing AWS relationship to identify the right partner for rapid iteration and capability development before internalizing the techniques.

AWS introduced Mission to LeaseLock as an ideal partner for their specific use case, and that recommendation proved decisive. The quality of Mission's team and their approach to engagement stood out during initial conversations. As Sudip Shekhawat, CTO of LeaseLock, noted, success in these partnerships comes down to people. Mission offered the right combination of technical depth and collaborative engagement that LeaseLock needed for rapid validation and capability development. The team's focus on understanding the problem at hand rather than proposing expansive solutions aligned perfectly with LeaseLock's pragmatic approach to validating AI initiatives before broader implementation.

AWS provides the comprehensive service portfolio LeaseLock needs for launching applications with integrated AI capabilities. As a cloud pioneer, AWS continues developing its platform while making significant advances in AI services. The availability of out-of-the-box solutions for AI implementation has been particularly valuable for LeaseLock's innovation roadmap. AWS's breadth of services and ongoing evolution in the AI space position it as the natural foundation for LeaseLock's technology initiatives.

Mission partnered with LeaseLock to design and implement a practical AWS-based framework that could unify data from across the organization and apply LLM capabilities to extract meaningful insights. The system brought together support tickets, internal development records, communication, internal documents, sentiment analysis, and operational metrics into a single analytical environment. Using Amazon Bedrock for LLM-powered interpretation and Amazon SageMaker for model development, Mission built a two-pronged approach that supported both customer behavior analysis and an advisor assistant. Both functions were powered by the same integrated dataset.

A core design principle was intentional simplicity. Mission focused on creating an architecture that was modern, easy for LeaseLock’s team to work with and manageable within their existing technical capacity. Instead of introducing unnecessary complexity, the architects established clear patterns for data ingestion, transformation, and analysis. This made the multi-dataset AI system accessible to a lean internal team. The work validated that an AWS-native approach could reliably produce insights about customer sentiment, operational health, and recurring patterns across support and product workflows.

Mission’s engagement philosophy was equally important. The team centered the project on LeaseLock’s immediate questions: whether the approach was technically feasible, what level of investment it would require, and whether the insights would translate into business value. Planning remained intentionally conservative and anchored to the decisions LeaseLock needed to make at the time. This approach gave LeaseLock a realistic view of cost, timeline, and resource requirements. It allowed the company to evaluate the concept with clarity and determine the appropriate next steps.

Throughout the engagement, Mission emphasized hands-on collaboration and knowledge transfer. LeaseLock’s internal team worked directly within the environment, gaining experience with the architectural patterns, LLM workflows, and data-integration methods that powered the solution. By the conclusion of the project, LeaseLock had not only a validated prototype but also the skills and confidence to apply these methods to additional AI initiatives. The team has since used the same patterns to build production systems for claims efficiency and adjudication. The work completed with Mission accelerated LeaseLock’s broader AI roadmap and continues to influence multiple high-value operational use cases.

Mission and AWS helped LeaseLock validate, build, and operationalize AI-driven workflows with clear business impact.

Mission’s work confirmed that a multi-dataset, LLM-powered architecture on AWS could deliver measurable operational value. The engagement provided clear answers on feasibility, investment requirements, and the expected return. With the foundational patterns established, LeaseLock quickly applied the AWS-native workflows to high-priority operational use cases.        

LeaseLock also strengthened its internal AI capability. By adopting the architectural patterns and data-integration methods built on AWS, the team can now scale similar approaches across customer intelligence, risk analytics, and operational automation. The initial project created a repeatable model that continues to accelerate LeaseLock’s AI roadmap and deepen its adoption of AWS services.