Managed AI Services

What Is Managed AI Services?

Managed AI at Sphere means delegating the day-to-day operations of your AI systems to an experienced team. This includes managing data pipelines, monitoring performance, retraining models, maintaining infrastructure, and resolving technical issues before they impact production.

As a result, your team spends less time on maintenance, avoids disruptions, and benefits from AI systems that remain stable and efficient. In other words, Sphere provides the operational discipline needed to support AI at scale. It’s backed by clear accountability, measurable results, and continuous system improvement.

Zero Surprises

We fix issues before you see them. You stay focused on growth.

One Accountable Partner

No finger-pointing. We run your stack like it’s ours.

Flexible Capacity

Scale support up or down based on project or workload volume.

Why You Need Managed AI

By 2025, nearly 67% of organizations are leveraging AI-powered tools to enhance operations. But are they performing at 100%?

AI Operations Drain Engineering Capacity

Engineers spend more time managing pipelines and troubleshooting outages than building features. Core projects slow down as support work piles up.

Models Decay Without Active Tuning

Model drift, performance degradation, and rising costs are common without ongoing tuning Left unchecked, these issues affect user experience and ROI.

Production AI Is Hard to Scale

Launching a first version is easy compared to scaling it. As usage grows infrastructure stress rises and production gaps appear.

What We Do

AI Infrastructure Assessment & Migration

In-depth assessment of your current AI infrastructure, pipelines, and models. This includes identification of bottlenecks, technical debt, and performance constraints. We then design and execute a clear migration plan to transition ownership efficiently.

Infrastructure & AIOps Management

Ongoing management of compute, storage, orchestration, and data workflows. AIOps capabilities (automated anomaly detection, incident triggering, root cause analysis) streamline operations and reduce manual firefighting.

Model Monitoring & Retraining

Continuous monitoring of model accuracy and drift, with retraining pipelines and version control in place. Ensures production-ready models via seamless updates and rollback mechanisms.

Performance & Cost Optimization

Regular performance reviews to right-size resources, tune autoscaling, and eliminate waste. Cloud spending is tracked and optimized without compromising output or latency.

Security & Compliance

AI-specific security measures (access control, logging, intrusion detection, encryption), along with regulatory compliance and auditing-ready processes. Proactive risk management and policy governance.

Strategic Reviews & Reporting

Quarterly reviews that tie technical performance to business KPIs, including model ROI, cost-benefit analysis, stability metrics. Includes actionable recommendations for next-phase scaling or pivots.

Start With a Free Consultation

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Success Stories

Find out more

Is Your Organization Ready for AI?

AI can drive real results, but only if your team, data, and systems are prepared for it. Before you invest, make sure the foundations are in place. Use our practical checklist to spot the gaps, avoid false starts, and set your AI projects up for success.

Download

The 5 Pillars of Implementing a Successful AI Strategy

Hear from

our clients

Hear from our clients

Lee Ebreo

VP of Engineering at Credit Ninja

These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.

Selah Ben-Haim

VP of Engineering at Prominence Advisors

Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).

Ben Crawford

Senior Product Manager at Enova Financial

I would expect to be delighted. It's been a really positive experience, working with Sphere, and I would expect you to have the same.

Mark Friedgan

CEO at CreditNinja

Sphere consistently prioritizes the needs of their clients, demonstrating both agility and teamwork. As an offshore team, they have been an integral part of our organization and we plan to continue growing with them.

René Pfitzner

Co-Founder at Experify

Sphere provided excellent full-stack development manpower to augment our team and help push our product forward. They are easy to work with, tech-savvy and proactive.

Bruce Burdick

Chief Information Officer at Integra Credit

We've been working with Sphere and its excellent consultants since our founding. I've found that they are true partners in the success of our business.

Jemal Swoboda

CEO at Dabble

The resources and developers that Sphere Software provides are skilled and have the required technical expertise, but more importantly, they have helped us build a culture of excellence within our team.

Arthur Tretyak

Founder and CEO at IntegraCredit

With Sphere, we were able to migrate in half the time it would take to train an additional FTE… and for a fraction of the cost. Our experience with Sphere has been exceptional.

Lee Ebreo

VP of Engineering at Credit Ninja

These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.

Selah Ben-Haim

VP of Engineering at Prominence Advisors

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Years of Excellence

Projects Delivered

Countries

Globally diverse, community-focused

Clients

top 20 average 8+ years

Featured Team Members

Katya Savenkova

Director of Operations

Anton Shemerey

Director of Technology

Dmytro Shein

Solution Architect

Oleg Kukareka

Solution Architect

Frequently Asked Questions

Managed AI services provide end-to-end operational management for your AI systems — from infrastructure and pipelines to model monitoring and optimisation. They ensure your AI runs smoothly in production without draining your in-house engineering capacity.

They eliminate repetitive support tasks so engineers can focus on core product work. Instead of managing data pipelines, retraining models, or troubleshooting outages, your team spends time innovating — while the managed AI provider ensures uptime, performance, and compliance.

Sphere covers the full AI lifecycle: infrastructure setup and monitoring, data pipeline management, model drift detection and retraining, cloud optimisation and cost control, AI governance and compliance reporting, plus 24/7 system monitoring and support. These services combine AIOps practices, predictive analytics, and automation to maintain peak performance.

As organisations scale AI adoption, model management, cloud costs, and compliance grow exponentially. Managed AI services provide a scalable framework — enabling continuous monitoring, elastic infrastructure, and consistent ROI without internal overhead.

Any data-driven organisation can benefit. The most common adopters are in Banking & Financial Services (model risk monitoring, regulatory compliance), Healthcare (AI reliability for diagnostics and analytics), Manufacturing (predictive maintenance, process optimisation), and Logistics & Retail (real-time demand forecasting and automation).

By continuously monitoring for model drift, retraining on fresh data, and optimising inference performance, managed services keep models accurate and relevant. This boosts ROI by aligning outputs with real-world business conditions and reducing operational downtime.

Sphere implements enterprise-grade AI governance: secure access control, encrypted data handling, audit-ready logging, and compliance with GDPR, SOC 2, and industry standards. Each managed AI environment is designed for transparency, accountability, and reliability.

Costs depend on project scale, infrastructure complexity, and data volumes. Sphere’s managed AI pricing is flexible — focused on cost-efficiency and measurable value, avoiding hidden overhead and aligning spend with tangible business outcomes.

Most onboarding projects take 2–4 weeks, starting with an AI readiness assessment and environment audit. The process includes infrastructure review, workflow mapping, KPI definition, and gradual migration to managed operations with minimal downtime.

Key metrics include model accuracy and drift rates, system uptime and failure response time, cost-to-performance ratio, time saved by internal teams, and overall ROI from AI investments. Sphere provides transparent reporting dashboards for ongoing visibility.

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We move fast, think big, and deliver alongside you — turning bold ideas into real progress, quickly and visibly.

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