Case Studies : GeniusVets – DynamoDB
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Large language models are prediction engines. They excel at language but they cannot reliably do math. In domains where a miscalculated mortgage, tax liability, or compliance figure can trigger regulatory action, probabilistic AI output is not a minor inconvenience, it is an unacceptable risk. LLM math errors, inconsistent AI output accuracy, and the absence of any audit trail for AI calculations are problems that companies of all sizes, Startups to Enterprises, cannot afford to ignore.
TrueMath was built to solve this. Their approach: keep the AI's natural language interface for interpreting queries, but hand the actual computation to a purpose-built deterministic calculation engine, one that delivers the same verified, auditable answer every time. The challenge was transitioning this innovation from a validated proof of concept into a production-ready AI system capable of supporting paying customers in regulated industries.
We'd built AI into almost every part of our workflow except for where calculations were required. The stakes were too high to trust a model that might give a different answer tomorrow than it did today. TrueMath closed that gap."

Metal Toad and TrueMath strategically chose AWS as the platform for TrueMath's modernized production platform for its best in class services. The core AWS stack was designed for enterprise reliability: Amazon CloudFront for content delivery and DDoS protection, Elastic Load Balancing and AWS Fargate for containerized hosting, Amazon RDS (PostgreSQL) for relational data, Amazon ElastiCache (Redis) for caching, AWS WAF for application-layer security, Amazon CloudWatch for observability, and Amazon Bedrock for the natural language processing layer that feeds TrueMath's deterministic computation engine.
Beyond core infrastructure, Metal Toad implemented the commercial and operational layer that makes a platform a business. An MCP Server was deployed to enable AI assistant integration architecture, making TrueMath a native tool for Claude, GPT, and any MCP-compatible assistant. A custom analytics pipeline surfaced API usage patterns and business intelligence. Security hardening included IAM least-privilege, AWS GuardDuty, CloudTrail audit logging, and AWS Security Hub; laying the foundation for future compliance.
TrueMath's deterministic calculation engine entered production running on standard CPUs, no GPU infrastructure required. This reduces operational costs and energy consumption while achieving financial-grade accuracy that probabilistic LLMs cannot match. The platform delivers accurate, repeatable AI calculations with a complete audit trail: exactly what Finance, Real Estate, and Enterprise compliance workflows demand.
Looking ahead, TrueMath is now poised to scale globally, innovate faster, and has already accelerated their time-to-market by at least 6 months. With a robust production environment built on AWS, seamless AI assistant integration, and a solid foundation for operational excellence, TrueMath can focus on expanding their customer base and enhancing their platform. The success of this deployment sets the stage for TrueMath to achieve their 2026 market launch with an initial target of onboarding their first 25 paying customers.
Metal Toad helps companies move from proof of concept to production on AWS, with the security and operational rigor to support workloads scaling from day one.
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