Exploring AI Agents for Federal Teams

MetroStar-Built AI Tools that Remove Friction from Federal Workflows

MetroStar’s AI Agents are purpose-built to enhance federal operations, reduce manual tasks, and improve workflow speed and accuracy. These tools don’t replace people; they empower them. Our agents are designed to help teams work smarter, move faster, and focus on what matters most. Explore how our AI Agents are driving innovation across government operations.

Where are Agents Integrated?

Designed with security, scalability, and cost-efficiency in mind, our agents integrate seamlessly into internal systems without requiring a full system overhaul.

HR Systems
Internal Portals
Operating Environments
Document Repositories

Meet the AI Agent Team

Meet Mira

Recruitment Automation

Meet Penny

Internal Support Prototype

Meet Ann

Proposal Tooling

Meet Mira

Recruitment Automation

Meet Penny

Internal Support Prototype

Meet Ann

Proposal Tooling

Mira | Recruitment Automation

Mira is an AI-enabled recruitment agent created to enhance MetroStar’s internal recruitment processes so recruiters can focus their expertise on strategic tasks that only humans can do. She helps streamline job searches, answer common applicant questions, and simplify resume submissions, delivering a faster, more intuitive experience for job seekers. Built on Microsoft Azure AI, Mira is designed to integrate easily with applicant tracking systems, CRM platforms, and HR dashboards without requiring custom builds or reengineering.

Mira’s Use Case: Mission Aligned Matching

Mira surfaces high-fit candidates based on security, skill, and role relevance. She automates quick questions potential candidates have on anything from job applications to MetroStar’s benefit packages.

Mira is built for security and compliance and holds FedRAMP-aligned compliance. Credentials are managed in encrypted layers, and the system adheres to secure-by-design best practices.

In the Works: Streamlined Interview Coordination
Mira is set to automate outreach and scheduling to keep hiring cycles on track.

chat with mira

Mira | Recruitment Automation

Mira is an AI-enabled recruitment agent created to enhance MetroStar’s internal recruitment processes so recruiters can focus their expertise on strategic tasks that only humans can do. She helps streamline job searches, answer common applicant questions, and simplify resume submissions, delivering a faster, more intuitive experience for job seekers. Built on Microsoft Azure AI, Mira is designed to integrate easily with applicant tracking systems, CRM platforms, and HR dashboards without requiring custom builds or reengineering.

Mira’s Use Case: Mission Aligned Matching

Mira surfaces high-fit candidates based on security, skill, and role relevance. She automates quick questions potential candidates have on anything from job applications to MetroStar’s benefit packages.

Mira is built for security and compliance. Credentials are managed in encrypted layers, and the system adheres to secure-by-design best practices.

In the Works: Streamlined Interview Coordination. Mira is set to automate outreach and scheduling to keep hiring cycles on track.

chat with mira

Penny | Internal Support Prototype

Penny is an internal AI assistant designed to help employees get timely answers while reducing repetitive requests for HR teams.

Penny’s Use Case:

Built using a low-code platform, Penny relies on pre-approved content sources and structured metadata for consistent, policy-aligned responses. She’s designed for future expansion into enterprise tools like HR portals or compliance platforms.

Smarter Self-Service: Penny retrieves info about leave balances, training resources, and HR policies for employees to reduce back-and-forth routine requests, freeing HR for strategic work

In the Works:
Future enhancements may include expanded coverage, deeper system integration, and more natural language support.

In the Works:
Future enhancements may include expanded coverage, deeper system integration, and more natural language support.

Penny | Internal Support Prototype

Penny is an internal AI assistant designed to help employees get timely answers while reducing repetitive requests for HR teams.

Penny’s Use Case:

Built using a low-code platform, Penny relies on pre-approved content sources and structured metadata for consistent, policy-aligned responses. She’s designed for future expansion into enterprise tools like HR portals or compliance platforms.

Smarter Self-Service: Penny retrieves info about leave balances, training resources, and HR policies for employees to reduce back-and-forth routine requests, freeing HR for strategic work

Ann | Proposal Tooling

Ann explores how AI might support long-form content analysis and development for federal proposals. She focuses on content discovery, outline alignment, and draft assistance.

Ann’s Use Case:

Ann is built within a low-code environment and operates as a retrieval-based assistant. She relies on tagged metadata and prompt-based querying, with limited capacity for multi-turn reasoning or decision-making.

Smarter Content Surfacing: Ann locates reusable language from past performance, boilerplate libraries, and technical responses.

Outline and Draft Navigation: Ann aligns content to proposal structure, draft comparisons, and win theme tracking

In the Works: Feedback Awareness
The team is exploring how Ann might manage review cycles, track feedback, and coordinate across volumes.

Ann | Proposal Tooling

Ann explores how AI might support long-form content analysis and development for federal proposals. She focuses on content discovery, outline alignment, and draft assistance.

Ann’s Use Case:

Ann is built within a low-code environment and operates as a retrieval-based assistant. She relies on tagged metadata and prompt-based querying, with limited capacity for multi-turn reasoning or decision-making.

Smarter Content Surfacing: Ann locates reusable language from past performance, boilerplate libraries, and technical responses.

Outline and Draft Navigation: Ann aligns content to proposal structure, draft comparisons, and win theme tracking

In the Works: Feedback Awareness
The team is exploring how Ann might manage review cycles, track feedback, and coordinate across volumes.

Our Commitment to Responsible, Transparent AI

Trust is foundational not optional. Our Agents are developed with the same rigor that define MetroStar’s enterprise-grade services, with federal compliance expectations and human accountability in mind. These safeguards include:

Rigorous Development Testing

Every agent undergoes real-world stress testing before internal deployment or pilot consideration.

High-Accuracy
Standards

Agent responses are tuned to government workflows using curated and annotated source content.

Explainable &
Auditable

Outputs can be traced to their source, with human oversight and clear error boundaries.

Built to
Integrate

Our agents connect to platforms already in use — from document repositories to HR portals — to reduce switching costs and avoid duplication.

Governed
by People

All AI support is reviewed, improved, and overseen by MetroStar’s experts and end users. No agent makes final decisions.

Azure-Powered AI Agents

Built on Microsoft Azure AI Services, MetroStar’s Digital Labor Agents combine security, compliance, and speed to streamline workflows. With FedRAMP-aligned infrastructure and seamless integration into the Microsoft ecosystem, these agents can connect to tools like Teams, Entra ID, and the Power Platform, making them extensible across enterprise operations.

Our agents aren’t trained models, but they incorporate advanced prompt engineering to interpret and act on requests. This approach ensures flexibility without the risks and resource demands of an in-house model training. The result is AI assistants that automate repetitive tasks, answer questions quickly, and accelerate everyday processes, freeing your teams to focus on higher-impact work.

Azure-Powered AI Agents

Built on Microsoft Azure AI Services, MetroStar’s Digital Labor Agents combine security, compliance, and speed to streamline workflows. With FedRAMP-aligned infrastructure and seamless integration into the Microsoft ecosystem, these agents can connect to tools like Teams, Entra ID, and the Power Platform, making them extensible across enterprise operations.

Our agents aren’t trained models, but they incorporate advanced prompt engineering to interpret and act on requests. This approach ensures flexibility without the risks and resource demands of an in-house model training. The result is AI assistants that automate repetitive tasks, answer questions quickly, and accelerate everyday processes, freeing your teams to focus on higher-impact work.

Explore a Pilot or Demo with Our Team

Connect with our team to explore how MetroStar’s AI Agents streamline operations, enhance workforce performance, and deliver measurable impact.