AI Solutions & AI Operations

Give AI a clear path to production.

Move generative and predictive AI from prototype to reliable, governed production systems.

  • Agentic AI
  • RAG
  • Vector DBs
  • MLOps
  • LLMOps
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2 capability areas · 5 services

What we deliver in AI Solutions.

Build useful agentic workflows and retrieval systems, then engineer the evaluation, deployment and operating boundaries they need.

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Deliverables

What you receive.

We agree acceptance criteria, evidence and handover as part of the scope, before implementation begins.

  • An agreed use case, data boundary and human review policy
  • Retrieval or agent implementation with repeatable evaluation cases
  • Deployment records, monitoring and a production handover

In practice

Answer from the right knowledge. Escalate the rest.

An example support team needs an assistant that uses approved knowledge and avoids unauthorized account actions.

Step 1

Define sources, document permissions and permitted tools.

Step 2

Build retrieval and evaluate grounded answers and abstentions.

Step 3

Version prompts and models; monitor quality, drift and cost.

The useful result

A bounded workflow with evidence-linked answers, evaluated failure cases and human escalation.

Getting started

Start with one use case and an evaluation baseline.

Helpful starting context

The workflow, permitted data sources, representative questions, failure costs and the person accountable for decisions.

Set the boundaries early

AI evaluation reduces uncertainty; it does not guarantee correct answers. Production application AI is distinct from workplace AI access and governance in Managed TechOps.

Engagement models

Choose how we engage.

The practice defines the expertise. The engagement defines who owns what.

Consulting

Make a better technical decision.

Best when
You need clarity before you commit budget.
DotConn
Leads the assessment and recommendations.
You receive
Assessment, options, architecture decisions and a prioritized roadmap.
Discuss this model

Implementation

Deliver an agreed technical change.

Best when
The target is clear and needs building.
DotConn
Coordinates delivery and validates acceptance criteria.
You receive
A working system, tested configuration, documentation and handover.
Discuss this model

Managed service

Keep agreed work running.

Best when
You want a platform or IT area run for you.
DotConn
Owns recurring service activities and reporting.
You receive
Runbooks, service reports, review cadence and escalation records.
Discuss this model

Managed pod

One team around a delivery scope.

Best when
You have a backlog, not a headcount gap.
DotConn
Coordinates specialists and delivery reporting.
You receive
An agreed backlog, delivery ownership, working increments and knowledge transfer.
Discuss this model

Staff augmentation

Your direction. Extra specialist capacity.

Best when
Your team leads and needs more hands.
DotConn
Supplies vetted specialists and coordinates the engagement.
You receive
A defined role and capacity, onboarding plan and customer-directed contributions.
Discuss this model