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MLOps Services, AI Model
Monitoring & Maintenance
Retainers

Q: Can you maintain AI systems that were built by another agency?

Yes. We conduct a preliminary 1-week code and architecture review to audit the existing codebase before onboarding external systems into our retainer SLAs.

Q: What happens if an API provider experiences an outage?

Our monitoring systems trigger instant alerts, automatically rerouting inference requests to fallback models or deploying maintenance notifications according to pre-configured failover rules.

Ensure zero downtime, sub-second latency, and consistent accuracy for your live AI models and automated workflows with dedicated ongoing engineering retainers.

View Retainer Packages › Schedule an MLOps Consultation ›

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24/7 Pipeline & Model Observability: Real-time tracking of latency, token spend, and error rates.

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Proactive Drift & Hallucination Prevention: Continuous prompt tuning, retrieval optimization, and evaluation benchmarks.

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Guaranteed SLA Response Times: Priority access to senior engineers for API breaking changes and updates.

Problem & Solution

AI Systems Degrade Over Time Without Active Maintenance

Deploying an AI model is only the starting point. Upstream API deprecations, changing internal documents, and model drift will degrade accuracy and increase response latency over time.

The Problem

When an AI pipeline breaks or hallucinates, internal operations halt and customer trust is damaged.

The Solution

Our ongoing MLOps retainers provide proactive system monitoring, prompt adjustments, vector re-indexing, and bug fixes to keep your AI infrastructure running reliably.

Core Capabilities

Model Drift & Accuracy Monitoring

We run automated evaluation suites to benchmark system accuracy against baseline datasets, catching hallucinations and degradation early.

Prompt & Vector Retrieval Optimization

Regular re-chunking of internal knowledge bases, embedding model updates, and prompt tuning to reduce token costs and improve speed.

API Versioning & Deprecation Maintenance

Proactively update your pipelines when third-party providers (OpenAI, Anthropic, cloud databases) release new API versions or deprecate legacy endpoints.

Cloud Infrastructure & Cost Management

Actively monitor vector database scaling, memory utilization, and caching strategies to minimize monthly cloud compute invoices.

24/7

Always-On AI Operations

Phases: Audit, Build, Test, Monitor

12+

Years of Hands-On IT Engineering Experience

Offices: Dubai, Karachi & USA

Book a Free AI Strategy Call ›

Retainer SLA Packages

Features Growth Operations Enterprise Dedicated

Monitoring Coverage 24/7 Automated Error Alerts 24/7 Automated Alerts + Dedicated Engineer

Response Time SLA < 8 Business Hours < 1 Hour Priority Escalation

Monthly Tuning Hours 15 Dedicated Engineering Hours 40 Dedicated Engineering Hours

Evaluation Benchmarks Monthly Accuracy Reports Bi-Weekly Continuous Evaluation

Communication Channel Shared Slack/Teams Channel Dedicated Slack/Teams + Bi-Weekly Strategy Call

Your Success Story Starts Here
Let’s Begin!

Frequently Asked Questions

Got questions? We've answered the most common ones about working with RixDigi — from services to timelines to support.

Can you maintain AI systems that were built by another agency?

Yes. We conduct a preliminary 1-week code and architecture review to audit the existing codebase before onboarding external systems into our retainer SLAs.

What happens if an API provider experiences an outage?

Our monitoring systems trigger instant alerts, automatically rerouting inference requests to fallback models or deploying maintenance notifications according to pre-configured failover rules.

Keep Your Production AI Infrastructure Fast & Reliable

Schedule an introductory review to discuss monthly engineering and MLOps support for your systems.

Book Your MLOps Review ›

Ready to Bring Enterprise-Grade AI into Your Operations?

Book a 30-minute discovery session with our engineering team to evaluate your workflows and identify your highest-impact AI opportunities.