Agentic AI

Agentic AI built for measurable operational outcomes.

Reduce manual workflow delays with AI agents mapped to documented business value streams.

Modernize legacy processes using technology-agnostic architectures and cloud partner expertise.

Lower deployment risk through scaled Agile DevOps, inspection, and standardized documentation.

Improve operational continuity with rapid knowledge transfer and immediate backup coverage.

Move from AI ideas to production use cases supported by Microsoft, AWS, Oracle, and Google Cloud.

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Trusted By

Trusted for Complex Digital Transformation

Delivery discipline, technical flexibility, and user-focused design for AI-enabled operations.

TechZavy engineered a high-performance, centralized platform that bridged our legacy applications and brought us fully into the Azure cloud. The real game-changer has been their innovative use of Azure Open AI and autonomous agents to automate the reconciliation of judicial comments and sentencing departures. By seamlessly integrating our data with MNCIS and the DOC, TechZavy eliminated decades of data silos and drastically reduced our team’s manual administrative overhead. They delivered a solution that perfectly supports our statutory mandate

Tim Ogg

Director of MBCC-IT, Minnesota Sentencing Guidelines Commission

Moving our legacy databases to an Azure SQL Managed Instance was a massive undertaking, but TechZavy executed it flawlessly. Their managed cloud services optimized our system architecture, boosting scalability and guaranteeing zero downtime.

TechZavy has been meeting all contract obligations, including application development, data mapping, and process improvements. They have been extremely flexible in working with our technical and business requirements, have adjusted schedules and accommodated our resource timelines very well. Has worked extremely well with us in clarifying and adjusting deliverables as defined in the contract and has shown adaptability with us for minor modifications. Overall TechZavy has helped us advance our project as we approach production launch in the coming months.

Robert Wehausen

MNIT Supervisor, BWSR - Minnesota IT Services

TechZavy’s contributions to AI-driven enhancements—particularly the CRM chatbot for the MMCAP Members Portal—have meaningfully improved system functionality and user experience. Shan played a key role in modernizing the MMCAP analytics (ProductFile) processing by leading its migration from a legacy SSMS platform to an Azure-based solution using Data Factory, Databricks, and AI-supported optimizations. Also excelled in multiple roles as Project Manager, Azure Administrator, and AI Architect roles

Michelle Perish

Application Support Specialist, State of Minnesota

Shan has led the development of our department’s online platform that captures energy efficiency program data reported by 100+ Minnesota electric and gas utilities. Shan and TechZavy team have an exceptional level of technical expertise and a keen ability to implement user-friendly designs. I highly recommend Shan to anyone who is looking to develop software product solutions.

Adam Y. Zoet

Energy Planner, Director, Minnesota Department of Commerce

TechZavy Consultant has been doing wonderful on the projects they have been working on. I’m very happy with the quality of work and productivity. My goals are being met.

Lisa Zitek-Jones

QA Supervisor, MNIT Partnering with MN Pollution Control Agency

Agentic AI Applied to Public-Sector Modernization

Unifying Fragmented Justice Data Into One Intelligent, AI-Driven Case Platform

How a state sentencing commission replaced siloed legacy systems with a modern, AI-powered ecosystem for case management.

Modernizing Mission-Critical Government Procurement Data Systems With Azure and AI

How a legacy-heavy public-sector procurement platform became a fast, secure, cloud-native operation.

Modernizing Statewide Energy Reporting for Minnesota’s Regulatory Future

From a decade-old legacy system to a cloud-native platform serving 200+ utilities across Minnesota.

Ensuring Air Quality Data Accuracy for a Public-Sector Environmental Monitoring Platform

How full-stack QA and sprint traceability turned data from multiple third-party sensors into air-quality readings the public can trust.

Modernizing a Statewide Wetland Mitigation System With a Unifed Azure Platform

From decades of legacy data and manual workflows to an integrated, transparent, cloud-based mitigation system.

Awards & Certifications

Agentic AI Services Built for Production Outcomes

Governed AI workflow delivery

Use-Case Strategy

Prioritize high-value use cases

TechZavy starts with operational discovery to determine where agentic AI can create measurable value. Business analysts and solution architects map current workflows, system dependencies, user roles, data sources, and decision points before recommending automation.

This reduces the risk of building an AI agent that does not fit daily operations. Deliverables may include use-case prioritization, workflow maps, technical feasibility notes, governance needs, and a phased roadmap for production deployment.

Workflow Agents

Automate with operational control

Agentic workflow design defines how AI agents should reason, retrieve data, trigger actions, escalate exceptions, and involve human review. TechZavy designs these workflows around business rules, system constraints, and operational controls rather than generic automation templates.

Your organization gains structured task routing, repeatable decision support, exception handling, and documentation-ready process logic. This creates a stronger foundation for secure adoption across service, data, compliance, and operational teams.

System Integration

Connect AI to enterprise systems

Reliable AI agents depend on clean access to the systems and data that drive daily work. TechZavy builds technology-agnostic integrations across cloud platforms, applications, APIs, databases, IoT environments, and legacy systems where needed.

Experience with Azure-hosted platforms, Azure Databricks Lakehouse modernization, and enterprise data modernization helps support secure retrieval, validation, and action. The result is an AI layer that works with existing architecture while supporting future modernization priorities.

AI Governance

Scale AI with secure guardrails

Agentic AI must be governed before it is scaled. TechZavy helps define review points, access controls, audit trails, data handling rules, prompt and response controls, and escalation paths so AI agents operate within clear boundaries.

This approach supports compliance-sensitive environments where uptime, traceability, and user trust matter. Testing, validation, and documentation are built into the delivery lifecycle, helping reduce operational risk before AI workflows move into production use.

Production Delivery

Deploy with managed continuity

TechZavy supports AI agents from concept through production deployment using scaled Agile DevOps practices. Teams coordinate architecture, development, testing, release planning, documentation, and stakeholder inspection to keep progress visible.

This delivery model is designed for environments where delays, staffing gaps, and unclear ownership can disrupt transformation. Rapid knowledge transfer, immediate backup coverage, and standardized DevOps documentation help sustain continuity throughout the agentic AI lifecycle.

Performance Tuning

Measure and improve AI impact

Once deployed, agentic AI should be measured against operational goals. TechZavy helps monitor workflow performance, adoption, exception rates, user experience, and process impact so agents can be refined over time.

AIOps-enhanced delivery, predictive metrics, and analytics-driven feedback loops support continuous improvement. This helps your organization move beyond initial automation into a managed AI capability that adapts to changing business requirements and sustained production needs.

Our Elite Partners

Proven Delivery Strength Behind Agentic AI

80%

First-Call Resolution

95%

Customer Satisfaction

5 Day

Client Onboarding

Turn AI Strategy Into Operational Execution

Agentic AI is most valuable when it is designed around a real operational constraint: slow approvals, fragmented data, repeated service requests, compliance-heavy documentation, or manual decision support. TechZavy helps convert those constraints into governed AI workflows that can act, route, summarize, validate, and recommend within defined business rules.

The result is practical transformation, not experimental automation. Each initiative is shaped by architecture readiness, data quality, security requirements, user adoption, and delivery continuity. With experience across public-sector modernization, healthcare-vendor environments, data platforms, and managed IT services, TechZavy builds agentic systems that support measurable outcomes while reducing project disruption.

Build AI Agents With Governance and Control

Agentic AI requires more than model selection. It needs secure integration, process discipline, and clear ownership across users, data, and systems.

Identify workflows where AI agents can reduce repetitive effort and response time.
Connect cloud, data, legacy, and application environments through technology-agnostic architectures.
Use AIOps-enhanced delivery to monitor quality, sentiment, risk, and deployment progress.
Apply guardrails for human review, auditability, access control, and operational compliance.
Support production adoption with documentation, knowledge transfer, testing, and backup coverage.

Deploy Agentic AI With Enterprise Delivery Discipline

TechZavy’s Agentic AI approach is grounded in enterprise delivery experience. Public-sector modernization work, Azure Databricks Lakehouse initiatives, AI-driven case management, and managed hosting environments show how AI, data, and cloud architecture can support complex operations without losing transparency.

Your team gains a structured path from use-case discovery to deployment: value-stream alignment, data readiness assessment, workflow design, model integration, testing, monitoring, and continuous improvement. Backed by Microsoft AI Cloud Partner, Oracle Cloud Partner, AWS Solutions Provider, and Google Cloud Partner status, TechZavy helps deploy agentic AI where it can improve decisions, sustain operations, and create measurable business value.

Plan Your Agentic AI Initiative

Identify high-impact AI workflows and reduce delivery risk.

Explore Related AI, Cloud, and IT Services

Frequently Asked Questions

What does the agentic AI service actually provide for enterprise organizations?

The agentic AI service delivers intelligent automation by mapping AI agents to your documented business value streams, targeting operational bottlenecks such as manual approvals, fragmented data, and repetitive service requests. You gain technology-agnostic solutions that integrate with cloud, legacy, and IoT systems, all designed for measurable outcomes. This service modernizes your workflows, supports compliance, and ensures rapid knowledge transfer for sustained performance.

How can agentic AI improve operational efficiency and reduce project risk?

Agentic AI helps you reduce manual workflow delays and streamline decision support by assigning AI agents to repetitive or compliance-heavy processes. This minimizes project disruption and enhances continuity through:

Automated routing, summarization, and validation
Real-time monitoring and sentiment analysis
Immediate backup coverage and standardized documentation
Faster adoption of high-impact use cases, supported by leading cloud providers

What is the typical approach to implementing agentic AI in a complex IT environment?

Implementation starts with identifying pain points and value streams where AI can deliver measurable results. The process includes:

Assessment of your architecture readiness, data quality, and compliance needs
Design of technology-agnostic AI agents that integrate with legacy and cloud platforms
Agile DevOps delivery with transparent documentation and rapid onboarding
Structured knowledge transfer and ongoing monitoring to ensure operational stability

How long does it take to deploy agentic AI solutions and what are the cost factors?

Deployment timelines vary based on workflow complexity, integration requirements, and data readiness. Most projects achieve production use cases within a few weeks to several months. Cost is determined by scope, number of AI agents, required integrations, and ongoing managed support. Predictable cost models are used to support unlimited user and data scalability, so you can align investment with value delivered.

What sets this agentic AI offering apart from other AI service providers?

This agentic AI service stands out through its public-sector track record, rapid mobilization, and proven delivery for compliance-sensitive environments. You benefit from:

Microsoft, AWS, Oracle, and Google Cloud partnerships for robust cloud integration
Documented success in government, healthcare, and environmental modernization
Scalable Agile DevOps, proactive talent retention, and immediate backup coverage
Focus on measurable operational outcomes, not just experimental automation