AI development services we offer
| Service | What you get | Typical use |
|---|---|---|
| Generative AI development | Applications built on large language models, with prompts, guardrails and evaluation | Drafting, summarisation, extraction, internal copilots |
| LLM application development | Model selection, fine-tuning where it pays, and deployment through your cloud or self-hosted | Domain assistants, classification, structured output at scale |
| RAG development | Search and question answering over your documents and data, with citations and access control | Knowledge assistants, policy and support answers |
| AI agent development | Agents that use your systems and follow your approval rules | Back-office, CRM and ERP processes, customer service |
| Machine learning development | Forecasting, scoring, anomaly detection and computer vision models with MLOps | Demand, risk, fraud, quality inspection |
| AI app development | Web and internal applications with AI features, APIs and dashboards | Customer-facing AI products, internal tools |
How our AI software development works
- 01
Scope and data review
We confirm the use case, success measures and data access, and agree a fixed price for the first milestone.
- 02
Prototype on your data
A working prototype evaluated against your real examples within 3 to 5 weeks, so you decide on results.
- 03
Production build
Integration with your systems, security, access control, monitoring and cost controls, deployed in your cloud or data centre.
- 04
Handover and support
Documentation, runbooks and training for your team, with optional ongoing support and model updates.
Models and technology
We are model-agnostic. Depending on your data rules and budget we use hosted models through Azure OpenAI, Amazon Bedrock or Google Vertex AI, or open-weight models such as Llama, Mistral and Qwen hosted privately. Retrieval uses the vector and search stores that fit your stack, and every system ships with an evaluation set built from your own cases.
How to choose an AI development company
- Ask for a prototype on your own data before a large contract.
- Check that you will own the code, prompts, evaluation sets and models.
- Ask how quality is measured and re-tested after every model change.
- Prefer fixed milestones to open-ended time and materials for the first build.
- Check who does the work: the people who scope it should build it.
Frequently asked questions
What do AI development services include?
Scoping, data preparation, model selection or training, application and integration work, evaluation, security, deployment and handover. Solnix covers generative AI, LLM, RAG, AI agent and machine learning development.
How much does custom AI development cost?
It depends on scope, data and integrations. Solnix prices builds as fixed milestones after scoping, and starts with a paid consultation from $100 that is credited toward the build.
How long does it take to build an AI application?
Our standard is a working prototype on your data within 3 to 5 weeks and a first production release within about 60 days.
Do we need to fine-tune a model?
Usually not at first. Retrieval over your data with good prompts and evaluation covers most use cases. Fine-tuning pays off for a consistent output format, domain vocabulary, or matching a larger model with a smaller, cheaper one.
Can you build AI that keeps our data private?
Yes. We deploy into your own cloud account or data centre, and can self-host open-weight models so data never leaves your boundary.