Upcoming Event: The AI Agent Implementation Framework
Upcoming Event: The AI Agent Implementation Framework
Digital Sportsman
Panama City, Florida
Outdoor Recreation Technology / SaaS
Amazon Bedrock, AWS Lambda, Amazon API Gateway, Amazon RDS (PostgreSQL), Amazon ECS (Fargate), Amazon ECR, Application Load Balancer (ALB), Docker, GitHub Actions (CI/CD)
Digital Sportsman is an all-in-one booking and management platform built for outdoor adventure professionals, including fishing guides, charter captains, rental operators, and tour outfitters. Despite a powerful platform, their guide community lacked any practical way to query and interpret their own business data, leaving critical revenue and booking insights out of reach. Avahi designed and built an AI-powered analytics dashboard on AWS that enables guides to ask business questions in plain English and receive accurate, visualized answers in seconds. Leveraging Amazon Bedrock, Amazon RDS, AWS Lambda, and Amazon ECS Fargate, the solution delivered self-service analytics to a non-technical user base with per-guide data isolation and a fully automated deployment pipeline, transforming how Digital Sportsman’s community understands and grows their businesses.
Digital Sportsman is a technology platform purpose-built for the outdoor adventure industry. Based in Panama City, Florida, the company provides an all-in-one solution that combines online booking and reservations, CRM, marketing automation, resource management, accounting, and AI-powered reporting for guides, charter captains, rental operators, marinas, tour operators, and outfitters. Operating on a no-commission model that sets it apart from competitors, Digital Sportsman’s mission is to help outdoor professionals streamline operations, increase bookings, and grow their businesses through technology. The platform earned a Bronze Stevie Award in the 2025 American Business Awards for its innovation and measurable value to outdoor professionals.
Digital Sportsman’s platform serves a community of professional outdoor guides, including fishing guides, hunting outfitters, charter captains, and adventure instructors, who run lean, operationally demanding businesses. These professionals are experts in the field, but most do not have the time or technical background to pull data from databases, write SQL queries, or navigate complex reporting tools.
The result was a significant analytics blind spot. Guides could not easily answer fundamental questions about their own businesses. Which experiences were generating the most revenue? Who were the top customers that quarter? How were bookings trending over time? Getting those answers required either SQL knowledge or hours of manual spreadsheet work, neither of which was practical for a working guide managing trips, clients, and equipment daily.
Without a self-service analytics solution, Digital Sportsman risked limiting the value its platform could deliver to the guide community. In a market increasingly driven by data-informed decision-making, the inability for guides to access and act on their own business data represented both a user experience gap and a competitive vulnerability that needed to be addressed.
Digital Sportsman’s existing infrastructure was already running on AWS, making it the natural platform for extending the application with AI-powered analytics capabilities. AWS offered a comprehensive set of managed services that aligned precisely with the project’s requirements. Amazon Bedrock provided access to foundation models for natural language processing without the operational overhead of managing model infrastructure. Amazon RDS delivered a managed PostgreSQL database for reliable, secure data storage. AWS Lambda enabled a serverless backend architecture that scales automatically with demand while minimizing cost during low-traffic periods.
The combination of AWS Fargate for container orchestration, Amazon ECR for image management, and Application Load Balancer for traffic routing provided a production-grade deployment foundation with built-in high availability, all without requiring Digital Sportsman to manage underlying server infrastructure.
Avahi brought deep expertise in building generative AI solutions on AWS, with specific experience in natural language-to-SQL translation, prompt engineering, and Amazon Bedrock integration. As a premier AWS consulting partner, Avahi had the technical depth to design and deliver a production-ready AI analytics platform within a six-week engagement timeline.
The project required more than standard application development. It demanded careful prompt engineering to ensure that AI-generated SQL queries were accurate, properly scoped to individual guides’ data, and consistent across a wide variety of natural language inputs. Avahi’s experience building NLP-driven data platforms positioned the team to address these challenges effectively from the very start of the engagement.
Avahi designed and built the Digital Sportsman AI Dashboard, a real-time analytics platform that enables outdoor guides to ask business questions in plain English and receive accurate, visualized answers in seconds. Rather than requiring SQL knowledge or manual report building, a guide can type a question such as “What was my revenue last month?” or “Who are my top customers this year?” and receive a chart, data summary, and plain-English interpretation of the results, all through a conversational interface.
The platform architecture follows a serverless and container-based design on AWS. The backend is a Python API built with FastAPI, deployed as an AWS Lambda function via Amazon API Gateway. When a guide submits a question through the AI chat interface, the API passes the query to Amazon Bedrock, which runs Anthropic Claude Sonnet 3.5. The model converts the natural language question into a SQL query, enforcing strict rules through prompt engineering: every query is scoped to the authenticated guide’s own data, uses correct table joins, and references the appropriate date fields. This prompt-level enforcement prevents data leakage across users and ensures calculation accuracy.
The generated SQL executes against a PostgreSQL database hosted on Amazon RDS. The query results are returned to the model, which generates a human-readable chart title, axis labels, and a brief interpretation of what the data shows. The complete package, including chart data, interpretation, and metadata, is delivered to the frontend for visualization.
The frontend is a React 18 application styled with Tailwind CSS and rendered using the Recharts charting library. It supports bar charts, line charts, area charts, pie charts, KPI summary cards, and ranked lists. The frontend runs in a Docker container deployed on AWS ECS Fargate and is exposed through an Application Load Balancer with HTTPS termination.
The AI chat interface includes suggested starter prompts to help guides discover what questions they can ask, lowering the barrier for first-time users. When a query is too vague to answer accurately, the system asks a clarifying follow-up question rather than returning an irrelevant response. For time-series data with sufficient history, the platform generates predictive forecasts using linear regression, projecting trends for the next three months.
Every code change triggers an automated CI/CD pipeline: new container images are built, pushed to Amazon ECR, and deployed to their respective services, eliminating manual deployment steps and ensuring consistent, repeatable releases across the entire platform.
Comprehensive technical documentation and handover materials
Digital Sportsman’s guide community gained analytics capabilities that did not previously exist, and the data powering those analytics is accurate enough to trust for real business decisions. Guides who previously had no practical way to assess their revenue trends, booking patterns, or customer performance can now get answers in seconds through a conversational interface, with no technical skills required. The platform bridges a critical gap between a powerful SaaS product and the non-technical professionals it serves.
The platform was architected for growth. The serverless AWS infrastructure scales automatically with demand, and the delivered architecture documentation provides Digital Sportsman’s team with a clear roadmap for adding write capabilities, pinned charts, and model tuning in future phases.
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