A State Agency in Maryland

Client Background

The Agency is a leading state agency responsible for providing environmental and technical services to public and private partners. Its mission spans waste management, water treatment, recycling, and renewable energy initiatives across the state.

The Agency envisioned a conversational, human-like AI assistant that could understand natural language, provide accurate answers instantly, and support a wide variety of queries without requiring predefined commands.

Client Need

Objectives

The project’s goal was to design and implement a Generative AI-powered digital assistant that would:

Enable context-aware, human-like conversations with users.
Retrieve accurate information dynamically from diverse data sources and web content.
Support multi-turn conversations, remembering context from earlier exchanges.
Be secure, scalable, and easily integrable with the Agency’s existing website and systems.
Reduce call-center load and improve citizen satisfaction through faster, more accurate responses.

Challenges

The Agency faced several technological and operational hurdles before deployment:

Rigid Search Systems: Existing web search tools required exact matches, leaving users frustrated.
Data Fragmentation: Relevant information was distributed across separate sites, PDFs, and databases.
Limited Staff Availability: Customer service teams were overwhelmed by repetitive inquiries.
Privacy & Compliance Needs: The system had to handle sensitive environmental data securely, following state IT and data retention guidelines.

Our Solution

Infojini designed a Generative AI (GenAI) agent that could converse naturally, interpret intent, and retrieve accurate, up-to-date information, all without depending on static keywords.

Key Features

Contextual Understanding: The GenAI agent used large language models (LLMs) fine-tuned with the Agency-specific terminology, enabling nuanced comprehension of environmental terms.
Dynamic Knowledge Access: Integrated APIs fetched data from multiple sources — including Agency’s CMS, open datasets, and external partner sites — ensuring live, reliable answers.
Conversational Memory: Users could continue conversations seamlessly, as the AI remembered context and intent across multiple queries.
Secure Deployment: The agent operated within a secure cloud environment, implementing role-based data access and encryption for sensitive content.

See Our Solutions in Action

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Realized Benefits

Instead of static web pages and lengthy navigation, users could now “talk” to the system, asking about recycling locations, permit requirements, and water testing schedules in everyday language.

The Agency reported significant drops in repetitive support tickets, better citizen engagement, and a stronger perception of digital modernization. The success of this pilot project established a foundation for scaling conversational AI across other state agencies.

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