CodeX71 brand markCodeX71CodeX71Better business. Built together.
العربيةWorkshop

Keep AI working well for your business.

Check the quality, reliability and cost of your AI tools as information and business needs change.

  1. 01Agree the starting point
  2. 02Test
  3. 03Monitor
  4. 04Improve

The business need

WHAT NEEDS TO IMPROVE

Answers can become less useful as documents, models and business needs change. AI needs regular checks after launch.

WHAT WE HELP YOU ACHIEVE

Ongoing support to maintain the quality and reliability of your AI tools, manage human review and track costs.

What the support
includes.

AI managed services

Keep AI useful
in everyday work.

Check the quality, reliability and cost of your AI tools as information and business needs change.

01AI model support

Release and track model updates, watch for falling performance and plan improvements.

02Answer quality

Test answers and prompts, compare new versions and review quality before changes go live.

03Knowledge updates

Keep the approved documents and information used by AI current and accessible to the right people.

04AI assistant support

Monitor tasks, fix failures and make sure people can step in when needed.

05AI safety & oversight

Protect sensitive data, test for unsafe behaviour and keep records for review.

06AI speed & costs

Track response times and usage costs, then look for ways to improve value without losing quality.

A closer look at
what we deliver.

Choose the services that fit your challenge. We agree priorities, scope and success measures with your team before delivery.

01 / Managed Services

AI managed services

Keep AI applications useful as information, models and business needs change, with agreed quality checks and operating responsibilities.

What we can help you with

  • MLOps, LLMOps and release management
  • Quality, safety and cost monitoring
  • Model, prompt and knowledge updates

Example use

Review an AI assistant’s answers after knowledge changes and manage improvements through a controlled release.

What we can measure

AI quality trendCost and latency per task

Examples illustrate possible uses. Measures are agreed against your starting point; they are not promises of a specific result. Platform names describe technologies we can support. They do not imply a CodeX71 certification, vendor partnership or endorsement.

Our expertise

How this can help
your business.

Examples of how this service could help. These are not completed customer projects.

Answer quality

Know when answers need attention

Keep a set of test questions, compare updates and investigate when quality falls.

Plan your project
Business knowledge

Keep the information current

Check document updates and access so the AI uses the right information.

Plan your project
AI running costs

Understand the cost of each task

Review response times and usage costs alongside answer quality and human review needs.

Plan your project

Support with a plan for continuous improvement

WHAT HAPPENS AT EACH STEP

  1. 01

    During support

    Monitor the AI service, handle issues and involve people where agreed.

  2. 02

    At service reviews

    Review answers, source information, model updates and spending.

  3. 03

    At planning reviews

    Agree better instructions, information updates and changes to the AI tools.

OPERATIONAL MEASUREMENT

Define what healthy service means

Agree the baseline, measurement window, data source, owner and review cadence before setting targets. These are measurement definitions, not published service guarantees or customer results.

SLO and service scope

A service-level objective (SLO) is a target for an agreed workload or critical flow, measured by a defined indicator. Document exclusions, dependencies and support hours. Any service-level agreement (SLA) is set separately in the contract.

Detection and restoration

MTTD: mean elapsed time from the agreed incident-start timestamp to detection. MTTR here: mean time from detection to service restoration. Report severity, sample size and time window; agree recovery objectives and test runbooks.

AI quality and cost

Compare retrieval quality, groundedness and task completion with a versioned evaluation baseline. Track input or output drift, review exceptions, token usage and cost per accepted task.

Measurement framework: Microsoft reliability metrics · AI observability

Define service scope and responsibilities

We agree the AI tools and information covered, quality measures, human checks, permitted changes, support hours and usage budgets.

CLEAR RESPONSIBILITIES
SupportUpdatesSecurityData qualityAI qualityCosts

We agree support hours, team roles, response times and service targets around your business needs. We review reliability, issue resolution, update quality, data accuracy and AI cost.

Connect this service
to your UAE priorities.

Explore practical outcomes and the relevant initiatives, then choose a first step for your organisation.

What you need to know.

Can you support the solution after launch?

Yes. We can support applications, data and AI, manage updates and plan improvements. We agree service hours, response times, responsibilities and costs before support starts.

Who will manage and deliver the work?

CodeX71 leads the work from the UAE, supported by a global team. We agree onsite or remote support, team roles and how progress will be reviewed.

Discuss your application
or AI use case.

Start with a free workshop. Customers and partners can define the problem, the intended outcome and a practical next step.

Book a free workshop