AI Application Monitoring
Monitor relevant application indicators, integration status, errors, usage, and availability based on the system's requirements.
AI Support & Maintenance
AI Support and Maintenance for Reliable Business Applications
An AI solution needs attention after deployment. Changes in data, model behavior, application dependencies, and business requirements can affect how well it performs over time.
SmartHire Technologies helps businesses plan and maintain AI applications through appropriate monitoring, troubleshooting, integration checks, and performance evaluation.
AI application lifecycle
Monitoring & improvement
AI Application Monitoring
Monitor relevant application indicators, integration status, errors, usage, and availability based on the system's requirements.
AI Output Evaluation
Review output quality against agreed criteria and representative examples.
AI Application Updates
Support planned changes to prompts, configurations, application logic, or model versions, with appropriate testing before release.
The exact scope should be agreed before support begins.
Ongoing AI reliability
Our support approach focuses on keeping AI-enabled workflows useful and reliable as your business and technical environment evolve. Depending on the application, this may include reviewing output quality, investigating issues, monitoring usage and costs, and identifying opportunities for improvement.
The objective is to help businesses maintain confidence in their AI solutions and address problems before they become larger operational disruptions.
Business Challenges
Keep AI Applications Reliable as Your Business Changes
AI applications may behave differently as inputs, usage patterns, dependencies, and requirements change.
Businesses may need help with:
A structured support approach helps identify which aspects of the system need monitoring and how issues should be investigated and resolved.
Investigating unexpected outputs.
Monitoring application availability and integration health.
Evaluating output quality.
Managing changes to models, APIs, or dependencies.
Controlling usage and operating costs.
Addressing errors and workflow failures.
Maintaining appropriate security and access controls.
Support and Maintenance Services
Maintain the Performance of Your AI Applications
AI Output Evaluation
Review output quality against agreed criteria and representative examples.
For applications that use generative AI, this may include checking relevance, factual grounding, consistency, and adherence to expected behavior.
Troubleshooting and Issue Resolution
Investigate reported issues involving application behavior, integration failures, configuration, or unexpected outputs.
AI Integration Maintenance
Review the connections between AI services and existing business applications, including API changes and dependency issues.
Performance and Cost Optimization
Identify opportunities to improve response times, reduce unnecessary model calls, or use resources more efficiently where technically feasible.
AI Application Updates
Support planned changes to prompts, configurations, application logic, or model versions, with appropriate testing before release.
Reliability and Lifecycle Management
Build a Practical Approach to Ongoing AI Reliability
AI maintenance should be aligned with the risk and importance of the application.
A low-risk internal assistant may need a different level of monitoring from an application that influences critical operational decisions.
The exact scope should be agreed before support begins.
A suitable support plan may define:
Performance and reliability indicators.
Testing requirements for changes.
Issue reporting and escalation procedures.
Review of output quality.
Backup and recovery requirements where applicable.
Access and security checks.
Maintenance responsibilities and reporting.
Support Process
From Initial Review to Ongoing Improvement
Review the AI application, integrations, and known issues.
Identify monitoring needs, performance indicators, and support priorities.
Establish appropriate testing, troubleshooting, and change procedures.
Investigate and address issues within the agreed scope.
Review performance and recommend improvements based on observed results.
Frequently Asked Questions
AI Support & Maintenance FAQs
Depending on the agreement, it can include monitoring, troubleshooting, integration maintenance, output evaluation, updates, and performance optimization.
Models, APIs, data, dependencies, and business requirements can change. Maintenance helps identify issues and keep the application aligned with its intended purpose.
Yes. Changes in input data, usage patterns, dependencies, or the surrounding environment can affect performance. Monitoring and evaluation help identify relevant changes.
It may help identify inefficient workflows, unnecessary model calls, or opportunities to optimize resource usage. Actual savings depend on the application and available improvements.
Potentially, subject to a technical review, access to the necessary systems and documentation, and agreement on the support scope.
Get in Touch
Need Help Maintaining an AI Application?
Whether you need help investigating an existing issue or planning ongoing maintenance, SmartHire can discuss the requirements and identify an appropriate support approach.
