AI Development Services
AI that does a real job in your product.
NetOfficials builds AI features for B2B companies: assistants and chatbots grounded in your own data, machine learning models, document processing and workflow automation. We start from the task you want done, then choose the right approach, and one team takes it from a written scope to production. For language model applications, see our LLM development services.
- Building software since
- 2011
- Approved before the build
- Written scope
- Tracked in Jira
- Sprint demos
- Confirmed in the contract
- Your IP
AI Development Services We Offer
Pick a starting point, or describe the job you want done and we will recommend the right approach: a language model, a machine learning model or plain automation.
- Generative AI
Generative AI Development
Content, summaries and workflow features built on language models.
Learn more - Generative AI
LLM Development and Fine-Tuning
Language-model applications grounded in your own data.
Learn more - Generative AI
AI Chatbot Development
Support and sales assistants for customers and staff.
Learn more - Generative AI
Natural Language Processing
Extract meaning from text, documents and conversations.
Learn more - Machine learning
Machine Learning Development
Models that learn from your data to classify and predict.
Learn more - Machine learning
Deep Learning Development
Neural networks for images, audio and complex patterns.
Learn more - Machine learning
Predictive Analytics
Forecasts and risk scores from your historical data.
Learn more - Machine learning
Recommendation Engine Development
Suggest the right product, content or next step.
Learn more - Machine learning
Computer Vision Development
Software that reads and understands images and video.
Learn more - Delivery and integration
AI Process Automation
Remove repetitive manual steps from business workflows.
Learn more - Delivery and integration
AI Integration
Add AI features to the systems you already run.
Learn more - Delivery and integration
AI Consulting
Find where AI will help, and where it will not.
Learn more - Delivery and integration
MLOps and ML Pipelines
Deploy, monitor and retrain models reliably.
Learn more - Delivery and integration
Hire AI/ML Developers
Add AI specialists to your existing team.
Learn more
Which AI Approach Fits Your Problem?
Not every problem needs a language model, and not every problem needs a custom-trained model. We pick the approach that fits the job, the data you have and the level of control you need.
A language model is usually the better fit when
- The work involves reading, writing or summarising text
- Answers should come from your own documents
- Requirements change often and need flexible behaviour
- You have little labelled training data
| Consideration | Language model (LLM) | Machine learning model |
|---|---|---|
| Best at | Text, documents and conversation | Predictions from structured data |
| Training data needed | Little beyond your own content | Labelled examples of the outcome |
| Output | Flexible, written answers | Consistent scores and classifications |
| Predictability | Needs guardrails and review | Consistent once trained |
| Time to a first prototype | Usually faster | Longer data preparation |
| Typical uses | Assistants, search, drafting | Forecasting, scoring, recommendations |
How We Deliver AI
Every project moves from a written scope to agreed review points, so you always know what is happening and what comes next.
Discovery
We define the job to be done, how success is measured and what data is available.
Signed scopeData and Prototype
A small working prototype on your real content shows what is possible before a full build.
Approved prototypeBuild and Evaluate
We build in sprints and test answers and accuracy against examples you agree.
Demo every sprintRelease and Hand Over
We deploy, set up monitoring and hand over the code and documentation.
Software you own
Why Choose NetOfficials for AI Development
The working terms below are part of every engagement, not extras.
One Cross-Functional Team
Design, development, testing and DevOps run through a single team, so decisions stay connected.
Senior From Day One
The senior engineer who scopes your work stays involved while it is delivered.
You Own Everything
IP assignment is confirmed in the contract, and you receive the full source code and documentation at handover.
Mutual NDA
We sign a mutual NDA before you share the details of your project.
Your Working Hours
We agree a communication window that suits your time zone at the start.
Visible Progress
Work is tracked in Jira, with a demo and your feedback at the end of every sprint.
How We Choose the Right AI Stack
We recommend technology for your project and your team's future, not for our convenience. Three questions guide every choice.
Will it handle your load?
We size the design for your expected users, data and growth, so it does not need rebuilding when the business grows.
Will it fit your systems?
We check how the stack connects with the tools, databases and partners you already rely on before we commit to it.
Can you support it later?
We favour well-supported technology with a wide talent pool, so your own team or any future partner can maintain it.
Technologies we work with
Python
TensorFlow
TypeScript
GraphQL
PostgreSQL
MongoDB
AWS
Azure
Google Cloud
Docker
KubernetesFlexible Ways to Work With Us
Pick the model that fits where your project is today. You can move between them as it grows.
Project Delivery
We deliver an agreed scope, timeline and price.
- Written discovery scope
- Milestone reviews
- Best for a clear first release
- For ongoing work
Dedicated Team
A team that works only on your project, led by a named delivery lead.
- Cross-functional team
- Sprint demos and planning in Jira
- Scale the team up or down
Team Extension
Specialists who join your existing team, tools and processes.
- Works in your process and tools
- Agreed overlap hours
- Best for adding a missing skill
AI for Your Industry
We learn the rules, users and systems of your sector first, then design the work around them.
AI Development FAQs
Where should a company start with AI?
With one clear job to be done, such as answering support questions from your documents or sorting incoming forms. We define the job, the data and how success is measured in discovery, then prove it with a small prototype.
Will our data be used to train public models?
That depends on the design we agree with you. We describe how your data is stored, processed and protected in the written scope before the build, and we sign a mutual NDA before you share anything.
Who owns the models, code and prompts?
You do. IP assignment is confirmed in the contract before the build begins, and you receive the code and documentation at handover.
How do you check that the AI gives good answers?
We agree test examples with you, measure answers against them each sprint, and show the results in the sprint demo.
Can you add AI to our existing product?
Yes. AI integration adds features such as search, summaries or assistants to the systems you already run.
Do you need a lot of data to start?
Not always. Language-model applications can work from your existing documents, while custom machine learning models need labelled examples. We tell you which applies in discovery.
Explore Our Other Practices
Ready to Build Your AI Solution?
Share a few details. A senior engineer reads every brief and replies with questions and a suggested next step.
- We review your briefAnd reply with questions
- We sign a mutual NDABefore you share the details
- You get a written scopeTeam, timeline and model, before any commitment