AI development
AI development company that tells you where AI actually works
We run our own AI platform, ryha.dev, so we have learned in production where this technology is reliable and where it will embarrass you in front of a customer. We add AI into systems you already run — assistants, chatbots, search and recommendations — with guardrails and a cost model.
What this includes
The work, and what you receive for it.
AI integration
Adding AI into systems you already run — assistants, chatbots, search, recommendations.
You receive
- Use-case assessment
- Model selection
- Integration
- Guardrails
- Cost model
Business process automation
Removing manual steps from onboarding, invoicing, approvals and support.
You receive
- Process map
- Automation build
- Exception handling
- Audit log
Workflow automation
Connecting CRM, ERP, Google Workspace, Microsoft 365 and WhatsApp so data moves on its own.
You receive
- Integration map
- Connectors
- Error alerting
- Runbook
Intelligent document processing
Reading invoices, contracts, forms and receipts automatically and pushing the data where it belongs.
You receive
- Extraction pipeline
- Accuracy report
- Human-review queue
Technology research
Evaluating tools, platforms and approaches against your specific constraints.
You receive
- Options comparison
- Recommendation
- Cost and risk notes
Product research
Studying competitors, users and market movement before a product decision.
You receive
- Competitor analysis
- User research
- Market summary
Proof of concept
A small, throwaway build that answers one technical question definitively.
You receive
- Working prototype
- Findings
- Feasibility verdict
- Effort estimate
Innovation consulting
Working out where AI, automation, cloud or security actually change your economics.
You receive
- Opportunity map
- Prioritisation
- Business case
How we work
One process, no surprises at the finish.
- A
We sit with the people who will use it, not just the person buying it, and write down what it has to do.
- B
You get a scope, a number and a timeline before any production code exists — including the monthly running cost.
- C
We build in short cycles with a working demo at the end of each one.
- D
Handover: your repository, your cloud account, documentation, training, and a named engineer who knows the system.
Who this is for
Back-office teams
Accounts, HR or admin staff spending hours on data entry.
Support teams
The same twenty questions arriving every day.
Document-heavy operations
Invoices and forms moving through people who should be doing something else.
Teams considering AI
You need to know if it works on your data before you plan around it.
Facing a platform decision
A choice you'll live with for five years.
About to commit a large budget
A small research spend that prevents a large mistake.
Questions
Answers before you ask.
- Does our business actually need AI?
- Often not. Most companies first need to stop copying data between systems by hand. We start with work that is repetitive, high-volume and rule-based, and use AI only where the work needs judgement about language, documents or patterns.
- What does an AI integration include?
- A use-case assessment, model selection, the integration itself, guardrails for unsafe or low-confidence output, and a monthly running cost model.
- Can you prove it works on our data before we commit?
- Yes. Our research division runs scoped feasibility work to answer whether a model is accurate enough on your documents before you plan around it.
Tell us the problem. We'll tell you what it actually needs.
You get a straight answer on scope, cost and timeline — and an honest note if we think this is not the work you should be doing first.