Service · Custom AI
Custom AI development, priced in the open
LLM apps on your data, RAG over your documents, computer vision and predictive models. Launch from $4,900 in 2-3 weeks, or 12 monthly payments at 0%.
Teams buried in documents
Tenders, contracts, policies or medical notes that people read line by line today.
Products adding AI
A SaaS or app that needs an AI feature its users will actually trust.
Operations with a manual bottleneck
A process where people copy, check or summarise the same kind of information all day.
Leaders who need proof first
Companies that want one working AI feature before signing off a larger budget.
What you get,in writing.
- A working AI system on your own data
- Retrieval (RAG) with citations back to the source
- Evaluation set and accuracy baseline
- Human review and approval steps where mistakes cost most
- Integration with your existing systems
- Monitoring, logging and handover documentation
- Full source code in your repository
- 1
Discovery call
We learn the workflow, the data and what a wrong answer would cost. You get a fixed, line-item quote.
- 2
Launch
One AI feature end to end on your real data, measured against a baseline.
- 3
Production build
Integrations, review steps, security and monitoring.
- 4
Launch
Rolled out to real users, with the people who check the AI's work trained on it.
- 5
Improve
We watch what reviewers change and tune the system where it matters.
What custom AI actually means here
Custom does not mean training a model from scratch. Most of our products run on general models such as GPT-4o and Whisper. What is custom is everything around the model: how your documents are read, which passages the model is allowed to use, what rules it must follow, and where a person checks the result.
That is where most AI projects fail, and where the value is. Syphon AI reads 200-page tenders, including tables and scanned pages, and links every answer to the exact page. Contract Blitz explains supplier contracts clause by clause and never says anything that is not in the contract. Esperwise writes medical notes in each doctor's own style. None of that comes from a better model. It comes from the system built around it.
- LLM applications. Assistants, copilots and agents that work on your data and your rules.
- Retrieval (RAG). Answers grounded in your documents, with the source one click away.
- Computer vision. Reading images, scans and documents that are pictures, not text.
- Predictive models. Forecasts and scores from your historical data.
How the price is set
Every project gets a fixed, line-item quote after a discovery call, so you know what each part of the build costs before work starts. There is no hourly meter. The published ranges below are where most projects land.
| Stage | Price | Timeline | What you get |
|---|---|---|---|
| Launch | $4,900 | 2–3 weeks | One AI feature and one integration, working on your real data |
| Product (MVP) | $12,000 | 4–6 weeks | Three core features, admin and two integrations, ready for users |
| Custom platform | From $25,000 | Per scope | Several roles, tenants or systems, priced by parts |
Four things move the price inside a range: how ready your data is, whether any model training is needed, how many systems it has to connect to, and what support you want after launch. A clean, well-documented data source and one integration sits at the bottom of a range. Scanned archives, several systems and strict compliance sit at the top.
Built so people trust it
An AI system only pays for itself if people use it instead of working around it. So every build includes the parts that earn trust, not only the parts that demo well.
- Citations. Answers link to the page and line they came from, so checking takes seconds.
- An honest “I don't know”. When the source does not cover a question, the system says so instead of guessing.
- A person where it matters. Drafts stay drafts until someone approves or signs them.
- Rules that work without the AI. Safety-critical checks follow your own rules, so they hold even if the model is switched off.
These patterns come from products we have shipped. Our inspiration page shows them in detail, with a link to the case study where each one runs.
An AI product your customers or team use every day.
Step 2 · Add partsPrices from our published list. We confirm the final, fixed price on one call. Running costs such as AI models, hosting and phone minutes are paid to those providers directly.
Built with this service
All case studies →Syphon AI
Reads 200-page tenders, flags the deal-breakers, and cites every answer.
Esperwise
Interviews the patient, listens to the visit, and writes the note the way the doctor would.
Contract Blitz
Explains every clause in plain English, flags what bites, and tells you what to ask for.
Brands10x
An AI CEO, CFO, CMO, COO and Chief of Staff that plan together around the same goals.
Common questions
How much does custom AI development cost?
Launch is $4,900 for one AI feature and one integration in 2 to 3 weeks. Product is $12,000 for an MVP with three core features in 4 to 6 weeks, plus $2,000 for each extra feature. Custom platforms start at $25,000. Pay once, or in 12 monthly payments at 0% with nothing down.
How long does it take?
Launch takes 2 to 3 weeks and Product 4 to 6 weeks. Custom platform timelines are set per scope.
Do you train your own models?
Usually not. Most products run on general models such as GPT-4o and Whisper, with retrieval over your own data. Training is only worth it when the data and the volume justify it, and it is priced separately in the quote.
What drives the cost up or down?
Data readiness, model training needs, integration scope and the support you want after launch.
Who owns the code?
You do. The full source code goes into your repository.
Can you start with a cheaper test?
Yes. If you want to test one idea first, our $500 Validation Build gets one flow live in 72 hours, and the fee is credited in full if you continue.