Managed Data & AI Services

Keep Your Data and AI Systems Running, Reliable, and Ready to Scale

Discuss Your Data & AI Operations

Building and deploying a data or AI system is only the beginning. Once these systems become part of everyday operations, they require ongoing monitoring, maintenance, troubleshooting, optimization, and improvement.

BuildingBlocks provides managed data and AI services to help organizations operate and maintain their data platforms, pipelines, AI applications, integrations, analytics environments, and supporting infrastructure.

Managed Data & AI Capabilities

Monitor and maintain critical data pipelines to identify failures, resolve delays, troubleshoot workflow issues, and keep data processes running reliably.

Manage and support data platforms, databases, warehouses, and related infrastructure through ongoing monitoring, maintenance, troubleshooting, and performance improvements.

Monitor AI applications and supporting systems to track performance, usage, system behavior, integrations, and other operational requirements.

Maintain and update AI applications as models, APIs, data sources, integrations, configurations, and business requirements change.

Evaluate AI and model performance and make ongoing improvements to configurations, models, workflows, and supporting systems based on operational requirements.

Maintain and troubleshoot connections between data and AI environments, enterprise applications, APIs, platforms, and external services.

Managed Data & AI Capabilities

Managed Data & AI Services support the ongoing operation of data and AI environments after implementation.

01

Data Pipeline Monitoring & Support

Monitor critical data pipelines, investigate failures and delays, troubleshoot workflow issues, and maintain integrations as source systems change.

02

Data Platform Operations

Support databases, data warehouses, data platforms, and related infrastructure through monitoring, maintenance, troubleshooting, and performance optimization.

03

AI System Monitoring

Monitor AI applications and supporting systems based on operational requirements, including performance, usage, system behavior, integrations, and response quality.

04

AI Application Maintenance

Maintain AI applications as models, APIs, data sources, integrations, configurations, and business requirements evolve.

05

AI & Model Performance Optimization

Support ongoing evaluation, performance analysis, configuration changes, model updates, and optimization activities based on system requirements.

06

Integration & API Support

Maintain connections between AI and data environments, enterprise applications, APIs, platforms, and external services.

Our Managed Data & AI Approach

Understand the Environment

Review the relevant data platforms, AI applications, integrations, infrastructure, dependencies, workflows, and operational requirements.

Define Operational Priorities

Identify critical systems, important workflows, performance requirements, dependencies, and areas where operational issues could create business disruption.

Establish Monitoring & Support

Set up appropriate monitoring and support processes to identify issues, investigate problems, and respond to operational incidents.

Maintain & Improve

Provide ongoing maintenance, troubleshooting, integration updates, configuration changes, performance optimization, and technical improvements.

Review & Scale

Adapt the managed environment as data volumes, system usage, infrastructure requirements, and business needs change.

Why Data and AI Systems Need Ongoing Management

  • Failed or delayed data pipelines
  • Data integration problems
  • Data quality issues
  • AI application performance changes
  • Production incidents
  • API and integration failures
  • Increasing infrastructure requirements
  • Growing technical debt
  • Limited internal capacity for ongoing support

Managed Services Across Your Data & AI Environment

AI Consulting

Helps organizations identify AI opportunities, establish priorities, and determine implementation direction.

Data & AI Advisory

Helps organizations evaluate data and AI priorities, readiness, capabilities, and business requirements.

Data Governance

Establishes ownership, standards, controls, quality practices, and processes for managing data.

Data & AI Engineering

Builds the pipelines, platforms, integrations, applications, and technical infrastructure required to implement data and AI initiatives.

Managed Data & AI Services

Provides ongoing monitoring, maintenance, troubleshooting, optimization, and operational support once systems are in use.

Related Services

Need Ongoing Support for Your Data and AI Systems?
Data and AI systems require ongoing technical attention as applications, integrations, data, infrastructure, and business requirements evolve.

Chris Clifford

Managing Partner, BuildingBlocks Consulting

Talk with an expert, not sales

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    Questions
    & Answers

    What are Managed Data & AI Services?

    Managed Data & AI Services provide ongoing operational support for data platforms, data pipelines, AI applications, integrations, analytics environments, and related infrastructure. Support can include monitoring, maintenance, troubleshooting, optimization, and continuous improvement.

    How are managed services different from Data & AI Engineering?

    Data & AI Engineering focuses on designing, building, integrating, and deploying technical systems. Managed services focus on operating, monitoring, maintaining, troubleshooting, and improving those systems after deployment.

    Can managed services support AI applications already in production?

    Yes. Managed services can support existing AI applications through monitoring, maintenance, integration support, troubleshooting, performance optimization, and technical updates.

    Can managed services work alongside an internal engineering team?

    Yes. Managed services can supplement internal teams by providing additional operational capacity, specialized technical support, monitoring, maintenance, or support for specific environments.

    What types of systems can managed services support?

    Managed services can support data pipelines, data platforms, warehouses, analytics environments, AI applications, machine learning systems, generative AI applications, APIs, integrations, and related infrastructure.

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