Custom AI Development
Our clients analyzed 13,000+ field marketing events, evaluated statewide social services programs, and searched through millions of event photos using AI this year.
Natural Language Analysis for Field Marketing
Advantage Solutions manages thousands of experiential marketing events for Anheuser-Busch InBev brands. Their account directors needed to analyze performance across markets, identify underperforming programs, and extract consumer sentiment from ambassador reports. The traditional approach meant exporting data to spreadsheets and manually reviewing event feedback.
mAInevent Agents changed that. The platform connects directly to MainEvent's database and lets users ask questions in plain English: "How did Houston perform in Q3?" or "What consumer feedback themes came up in Texas?" The AI generates market summaries, calculates conversion rates, and surfaces patterns in qualitative feedback.
"AI is able to point out things we might not have thought of previously. Non-technical people can log in, ask natural language questions, and get the info they need."
The system analyzed over 13,000 events in its first deployment. Advantage Solutions now uses it for weekly reporting, ad-hoc client requests, and performance risk assessment.
AI-Powered Data Analysis for Social Services
Social services organizations collect extensive data across case management, service delivery, and program evaluation. Analyzing that data traditionally meant building custom reports, writing database queries, or waiting for technical staff availability. Collaborate Agents eliminates those bottlenecks through natural language analysis.
Children's Advocacy Centers of Illinois uses the platform to analyze statewide program data. Instead of constructing reports manually, analysts ask questions in plain English: "Where do we see demographic disparities in service wait times?" or "Which interventions produce the best client outcomes?" The system generates interactive dashboards, combines internal case data with external sources like Census information, and identifies patterns across thousands of cases.
The platform detects equity issues, recommends resource allocation based on timing and location patterns, flags data quality anomalies, and measures program effectiveness across different intervention types. Analysts can request real-time dashboard updates by specifying additional metrics or visualizations.
"Collaborate Agents is going to be a game-changer, making it so much easier to understand and analyze our state's data."
The platform maintains HIPAA and SOC 2 compliance and holds AWS Public Sector Partner status. The AI infrastructure operates on the same secure foundation that supports hundreds of nonprofit organizations using Collaborate for case management and service delivery.
Visual Asset Search for Brand Management
Kraft Heinz's Brand Communications team manages visual assets from the Oscar Mayer Wienermobile Tour. Six Wienermobiles travel 20,000 miles annually, appear at 1,200+ events across 40+ cities, and generate thousands of photos. Sales teams, operations, customers, and partners regularly request specific images: "Show me the Wienermobile at Walmart" or "Find compliant shelf setups from the Chicago event."
Previously, fulfilling these requests meant manually sorting through photo archives.
mAInevent Vision applies computer vision to MainEvent's photo library. Object recognition identifies promotional materials, venue types, and marketing elements. Natural language search lets users query the system conversationally. The platform ranks results by relevance and filters by event metadata like location and date.
"We will save countless hours that we used to spend manually sorting photos. We can respond to requests with the speed and accuracy they deserve."
Infrastructure Built for Scale
These implementations run on infrastructure processing over 10 billion tokens monthly across our organization. In August 2025, we achieved nearly limitless token capacity across multiple providers including Anthropic, OpenAI, and Google, with Business Associate Agreements in place with each for HIPAA compliance.
Our infrastructure routes requests across AWS Bedrock, Azure, Google, and direct provider APIs. This multi-cloud architecture eliminates vendor lock-in and provides automatic failover when providers experience issues. If one service degrades, traffic routes to alternatives without user interruption.
Dozens of developers across our teams use AI daily for code review, architecture decisions, and testing. This isn't a side project or pilot program. AI infrastructure is core to how we build software.
Validation before deployment: We validate AI systems through comprehensive test suites before production release. Each test suite includes hundreds of query executions across different analytical patterns - market analysis, multi-dimensional grouping, time-series comparisons, and custom field queries. When identical questions return identical numerical results across all runs, we've proven the architecture works. This validation approach requires significant compute investment, but it demonstrates engineering rigor that production deployments demand.
What Makes These Implementations Work
These three solutions share common architectural principles:
Multiple LLM providers: We maintain relationships with OpenAI, Anthropic, and Google. Different models excel at different tasks. We route queries to the most effective model for each use case and can pivot providers as capabilities evolve.
Secure infrastructure: HIPAA and SOC 2 compliance aren't optional for our clients. Our infrastructure meets these standards by default. Social services organizations, healthcare nonprofits, and enterprise marketing teams operate on the same secure foundation.
Domain-specific integrations: Generic AI can't access MainEvent's event data, Census databases, or proprietary case management systems. Each implementation required custom integration work. We build these connections based on client requirements, whether that's third-party APIs, secure web search, government data sources, or proprietary databases.
Natural language interfaces: Users shouldn't need to learn query languages or navigate complex report builders. These systems respond to plain English questions because that's how professionals think about their problems.
How We Work
The examples above represent production implementations. They're not prototypes. Real users query these systems daily, integrate them into workflows, and depend on accurate results.
Each implementation started with specific operational challenges:
- Account directors waiting days for custom reports
- Social services organizations struggling to analyze statewide program data
- Brand managers manually sorting thousands of event photos
We designed solutions around those problems, built integrations to relevant data sources, and deployed on infrastructure that meets industry compliance requirements.
If you're evaluating AI implementations for your organization, we've likely solved similar problems. We handle custom integrations, manage compliance requirements, and build tailored solutions.
Contact us to discuss your AI project: info@networkninja.com