Critical systems × AI engineering · since 2012

Keep what works. Build what’s next.

A dedicated engineering team that takes long-term responsibility for your critical systems, including complex, high-traffic ones: from maintenance and continuous development to AI agents in your business processes.

  • ~7 yrsaverage client relationship
  • 1+full-time developer on every project
Illustration · not a live system
Your core system stable

Tap a capability to connect it. The core stays stable.

2/5 connected · core stable

Numbers we can stand behind

2012

Building, maintaining and evolving software since.

~7

Years: our average client relationship. Some are approaching a decade.

1+

Full-time developer dedicated to every project.

Knowledge stays with you.

Decisions are documented and shared with your team, so your system does not depend on one person’s memory.

02 / How we work with you

A dedicated team. Clear responsibility.

Every engagement has at least one full-time developer who stays with your system. You choose how we work together, and we agree up front on what we own.

01

Dedicated developers

Developers who join your team and your way of working. You lead the priorities; we bring continuous engineering capacity and growing system knowledge.

02

Managed engineering

UVISION runs the development within an agreed scope, with clear responsibility for planning, delivery and ongoing communication.

First phase

Taking over the system

  • A working map of the system: architecture, integrations, critical paths
  • Access, environments and the release process verified
  • A risk list and a stabilization plan, ordered by business priority
  • First fixes shipped through the real release process
  • A knowledge base that stays with your team

Scope, support hours and response expectations are agreed for each engagement. Meet our approach

From the field

What this looks like for clients.

Travel & tourism9 years together

A traditional tour operator

The challenge
A traditional company running on outdated systems that could not support the business change it needed. Annual turnover was about $1M.
What we did
We became the company’s development arm and built its technology in-house: the B2C website, B2B interfaces for human and automated agents, APIs and now MCP, and the internal ERP. Today we are taking it into the era of AI agents.
What changed
Turnover grew to about $10M within two years and about $20M after five, on the platform we built and keep developing.

Telecom · AI and BIAlmost 10 years together

A telecom connectivity and data company, since acquired by an international group

The challenge
Legacy, monolithic interfaces that had to become a SaaS product.
What we did
Outsourced development throughout the move from monolithic interfaces to a SaaS product, with data science and data engineering alongside the software.
What changed
The product moved to a SaaS model, the company was later acquired, and we still work together.

03 / Same system, new abilities

Built for industries that modernize carefully.

Travel, hospitality, logistics, insurance. Proven systems run these businesses, and every change carries risk. AI earns its place as a layer on top of what already works, one workflow at a time.

Existing system

A booking engine with years of fare rules and integrations.

AI capability

A customer assistant that reads live booking status and policy through read-only tools.

Guardrail

It explains and prepares. Changes run through the existing flow after the customer confirms. Unclear cases go to a person.

Value

Staff spend their time on exceptions, not status questions.

IllustrativeIllustrative examples, not client projects. Drag the handle to compare.

04 / Since 2012

The stack keeps changing. The responsibility doesn’t.

Every wave added a layer. The systems underneath still had to run, and someone had to understand them.

  1. 2012

    Monoliths and on-prem servers

  2. +cloud

    Cloud migrations

  3. +mobile

    Mobile and APIs everywhere

  4. +services

    Containers and microservices

  5. +scale

    Everything online, traffic at scale

  6. +LLM

    Large language models

  7. +agents

    Agents and MCP

  8. now

    Your next step

The longer we work together, the more we understand what matters.

Your business logic, the integrations nobody wants to touch, the decisions behind the code. We build that knowledge over time, so your next step starts from understanding.

Our client relationships average around seven years. Some are approaching a decade.

05 / HOW WE WORK

Understand deeply. Move forward deliberately.

Meet our approach
  1. 01

    Understand

    Map the system, its dependencies and the processes your business relies on.

  2. 02

    Stabilize

    Agree on priorities, build a testing baseline and address the risks that matter first.

  3. 03

    Evolve

    Develop new capabilities and introduce AI where it creates measurable value.

  4. 04

    Stay involved

    Keep developing, maintaining and transferring knowledge with a dedicated team.

06 / AI with boundaries

Useful AI knows its limits.

We design every AI capability with the same care as the system it touches. These switches stay on.

Least privilege

Only the data and actions the task needs. Nothing more.

Read first

Start by reading. Writing to live systems comes later, deliberately.

Human approval

A person approves consequential actions: money, records, customers.

Audit trail

Every AI action is logged and traceable.

Evaluate first

Representative cases, failure paths and cost, measured against a baseline before rollout.

A way back

Every change is planned with a way to roll it back.

MCP · API

MCP (Model Context Protocol) is an open standard that lets AI use your systems’ tools in a permissioned way. We use it, or plain APIs, wherever each system supports it.

Engineering principles we design with. Specific controls are agreed for each system.

07 / Try it now

Ask about your system. Get a real answer.

A real AI assistant (Google Gemini), grounded in what UVISION does. Describe your system or your challenge, and leave your details whenever you want a person to follow up.

AI can make mistakes. Messages are sent to Google Gemini to generate replies, and chats are stored to improve our service. Please avoid sensitive information. Privacy

UVISION AIGemini

Hi, I’m UVISION’s AI assistant. Tell me about a system or workflow you want to improve. A rough problem is a fine place to start.

08 / ENGINEERING PERSPECTIVES

Ideas for systems that need to last.

Explore all insights

Start a conversation

Tell us what can’t break.

What your systems do, what needs to improve and where you want to go. We’ll start from there.

UVISION AI

AI assistant · a person follows up

UVISION AI

Hi, I’m UVISION’s AI assistant. What system or workflow would you like to improve? You can start with a problem, even if the solution is not clear yet.

AI can make mistakes. Messages are sent to Google Gemini to generate replies, and chats are stored to improve our service. Please avoid sensitive information. Privacy