Keep your applications, data platforms, and testing operations reliable while freeing your engineers to focus on business priorities. KMS takes responsibility for agreed day-to-day services, with clear ownership, measurable performance, and continuous engineering improvements supported by AI-enabled workflows
When your best engineers are busy keeping systems running, there’s little time left to build what’s next. Recurring incidents, rising costs and unclear ownership slowly eat into the capacity your business needs to move forward.
Our best engineers spend too much time maintaining existing systems and fixing recurring issues. We need them focused on building new capabilities.
Our team spends hours on recurring incidents and manual operational tasks. We need to address the causes and automate repetitive work.
Too many teams and vendors are involved in daily operations. We need clear ownership, predictable service levels, and faster issue resolution.
Running our current environment keeps getting more expensive. We need to control costs without increasing operational risk.
Repetitive testing takes up too much QA and engineering time. We need more testing capacity to keep releases moving without compromising quality.
We cannot modernize everything right now, but we still need our existing systems to remain reliable and supported.
We need a partner who takes responsibility for daily operations and improves the environment as our business needs change.
Choose the area creating the most operational pressure, or combine services under a shared operating model with defined responsibilities and performance measures.
We partner with ambitious organizations to solve complex problems, craft meaningful experiences, and deliver measurable results.
Addepto, a KMS Technology company, partnered with Woodward, a global manufacturing organization, to optimize complex production processes across multiple facilities. The client was struggling with the huge amount of manual labor during testing processes.
KMS Technology helped iPipeline, a global leader in digital solutions for life insurance and financial services, to transform its quality engineering practice into an automation-first, AI-powered model.
A European fashion retailer needed to optimize its Databricks-based data platform and reduce rapidly increasing infrastructure costs. Our team was engaged to optimize costs, stabilize the platform, and design a scalable, future-ready data architecture aligned with cross-functional business needs.
KMS Managed Services follow a consistent operating model across Applications, Data, and Quality Engineering. The goal is not simply to maintain technology environments, but to take operational responsibility, improve performance over time, and create a path toward modernization and future-state capabilities.
Environment assessment and dependency map
Knowledge transfer documentation and runbooks
Defined SLAs, KPIs, and responsibilities
Operational baseline and initial backlog
Prioritized risk remediation plan
Incident and reliability improvements
Standardized operational procedures
Ongoing service management and support
SLA and KPI performance reporting
Incident and change management
Prioritized operational backlog
Automation and optimization backlog
Performance and cost improvements
Reliability and quality enhancements
Technical debt reduction initiatives
Technology improvement recommendations
Modernization readiness assessment
Prioritized evolution roadmap
Managed Services require more than responding to incidents and meeting service levels. KMS combines application engineering, data expertise, quality engineering, and AI-enabled execution to improve the technology your business depends on.
Select your industry to explore tailored Managed.
Reliable transactions depend on well-supported applications and accurate financial data. Clear operational ownership and traceable testing help your teams manage risk and control costs.
Keep transaction processing, payment platforms, and financial applications reliable through ongoing maintenance, incident management, and performance optimization.
Improve the accuracy, consistency, and traceability of financial data across transaction pipelines, regulatory reporting, and risk management systems.
Strengthen regression testing, transaction validation, and audit traceability across financial applications to support compliant, reliable releases.
Reduce recurring incidents, manual reconciliation, and infrastructure inefficiencies while maintaining the reliability of business-critical financial systems.
Support care delivery with dependable clinical applications, connected patient data, and carefully validated software changes.
Keep EHR, patient management, clinical trial, and healthcare applications reliable through continuous support, issue resolution, and performance improvements.
Maintain the quality, integrity, and availability of patient and clinical research data across integrations, analytics platforms, and reporting environments.
Strengthen automated testing, requirements traceability, and release validation for healthcare applications subject to strict security and regulatory requirements.
Maintain and optimize integrations between EHRs, laboratory systems, and healthcare platforms, including FHIR-based data exchange, to reduce operational disruptions.
Growing your product should leave room to build it. Managed application support, data operations, and AI-enabled testing give engineers more capacity for new capabilities.
Maintain production SaaS applications through proactive monitoring, incident resolution, performance tuning, and ongoing technical improvements.
Improve the reliability, scalability, and cost efficiency of cloud-based data platforms and pipelines as product usage and data volumes increase.
Expand test coverage and accelerate regression testing through AI-assisted workflows, helping QA keep pace with increasingly frequent product releases.
Improve CI/CD processes, deployment reliability, and release validation to reduce manual engineering effort and support faster product delivery.
Reduce the risk of software issues disrupting production. Maintain critical MES and ERP applications, monitor industrial data flows, and test changes across connected systems.
Keep manufacturing execution systems, ERP platforms, and production-critical applications reliable through ongoing maintenance, troubleshooting, and performance optimization.
Maintain reliable data flows between shop-floor equipment, IoT platforms, MES, and enterprise systems to support production visibility and operational analytics.
Strengthen integration, regression, and release testing across production and supply chain applications to reduce the risk of software changes disrupting operations.
Reduce recurring system issues, manual operational work, and infrastructure inefficiencies to improve production continuity and technology operating costs.
Internal engineering teams spend less time managing incidents, maintaining legacy systems, and handling repetitive operational tasks, creating more room for product development and business priorities
Defined service levels, consistent reporting, and clear ownership provide greater visibility into technology performance and operational responsibilities.
Proactive maintenance, improved monitoring, and recurring issue resolution help reduce service disruptions and strengthen operational consistency.
Continuous optimization, automation, and transparent service performance help reduce avoidable effort and improve cost predictability.
AI-enabled quality engineering and standardized testing processes improve validation capacity, helping delivery teams maintain quality as release demands increase.
A prioritized improvement backlog keeps performance, quality, and technical debt under review so existing technology can evolve alongside business needs.
When applications, data pipelines, and testing activities are spread across internal teams and external vendors, accountability becomes fragmented.
KMS establishes defined ownership, service responsibilities, escalation paths, and measurable performance expectations. Your teams gain a clear view of who is responsible for each service and how its performance is managed.
A successful managed service begins with a clear understanding of the environment, its dependencies, and the operational knowledge required to support it.
The transition establishes runbooks, monitoring, access, responsibilities, and service baselines before ongoing operations begin. Existing knowledge is captured and structured to reduce dependency on individual team members.
Day-to-day support should create opportunities for improvement rather than simply preserving the current environment.
Recurring incidents, repetitive activities, performance bottlenecks, and technical debt become inputs for a continuously prioritized engineering backlog. As improvements are delivered, operations become more efficient and predictable.
AI can help reduce the manual effort associated with selected engineering and quality processes without removing human accountability.
For managed quality engineering, VELOX, our AI orchestration tool, supports activities such as requirements validation, test design, execution, traceability, and reporting. Experienced engineers remain responsible for reviewing critical outputs and maintaining service quality.
Improvement priorities are informed by business value, operational risk, performance, and available service capacity.
A shared backlog and regular service reviews keep technical work connected to agreed business priorities. Your organization retains visibility into investment decisions while KMS manages execution within the defined service scope.
Ongoing operations and modernization do not have to compete for the same internal engineering capacity.
Managed Services maintain and improve the current environment while helping identify the applications, platforms, and processes that would benefit from deeper changes. Larger modernization initiatives can then be planned and scoped separately without compromising day-to-day service responsibility.
Managed Services involve assigning ongoing responsibility for defined technology operations to a specialized service provider. Rather than supplying additional engineers alone, the provider manages agreed services against established performance expectations.
KMS Managed Services cover legacy application management, data operations, and quality engineering, combining daily service delivery with continuous improvement.
Staff augmentation adds professionals to an existing team, typically under the client's day-to-day direction. Managed Services establish ownership of an agreed service scope, with defined responsibilities, service levels, reporting, and performance management. The distinction is accountability for managing the service rather than simply providing additional engineering capacity.
KMS Managed Services cover three areas: legacy application operations through Lights On, data platform and pipeline operations through Data Squads, and quality engineering through AI Testing Squad. You can engage one area or combine them under a single operating model.
Managed Services become valuable when daily maintenance, incidents, testing, and data operations consume too much internal engineering capacity. Companies typically consider them when operational costs are increasing, service reliability is becoming harder to maintain, or strategic initiatives are consistently delayed by support responsibilities.
Performance is managed through agreed SLAs, KPIs, service reporting, and a prioritized operational backlog. Measures depend on the service but can cover reliability, incident management, testing performance, data quality, operational efficiency, and continuous improvement outcomes.
Your team stays in control of priorities and decisions, and their capacity moves toward modernization, product, data, and AI work. Knowledge captured during the engagement is documented in runbooks, so operational understanding stays available to your organization.
Yes. All three offerings follow the same operating model, so you can start with the area creating the most pressure and extend the scope as priorities change.
Managed Services include continuous improvement and can support targeted enhancements, platform upgrades, and modernization readiness.
Larger architectural transformations, major migrations, and extensive modernization programs may require a separate scope. This allows ongoing operations to remain stable while transformation work is planned.
“Please extend a big ‘thank you’ to your team for an excellent job of closing the 70+ security vulnerabilities tickets last quarter, in addition to other feature and maintenance work scheduled for Q1.”
“It has been great working with KMS. They have already given us some great suggestions around code formatting and improvements, and how we can improve our overall workflow”.
Addepto, a KMS Technology company, partnered with Woodward, a global manufacturing organization, to optimize complex production processes across multiple facilities. The client was struggling with the huge amount of manual labor during testing processes.
KMS Technology helped iPipeline, a global leader in digital solutions for life insurance and financial services, to transform its quality engineering practice into an automation-first, AI-powered model.
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