AI Process Automation
Relayworks AI automates end-to-end business processes — document intake, data extraction, classification, routing, reconciliation and follow-up — combining language models with conventional automation. We use a model only where judgement is genuinely required, which is what keeps the system fast, cheap and predictable.
What this solves
The industry reflex is to put a language model in the middle of every process. It is usually the wrong call: models are slower, costlier and less predictable than code for anything deterministic. The skill is knowing which 20% of a workflow actually needs judgement.
What is included
- Document processing
- Invoices, purchase orders, claims, contracts, KYC packets — extraction with confidence scoring and human review where confidence is low.
- Classification & routing
- Tickets, emails and requests categorised and sent to the right queue or system, with the reasoning logged.
- Data reconciliation
- Matching records across systems that were never designed to agree with each other.
- Workflow orchestration
- Multi-step processes with retries, state, audit trails and clean failure handling.
- Exception handling
- The 5% that does not fit the pattern, routed to a person with the context they need to resolve it in seconds.
- Hybrid design
- Rules where rules work, models where judgement is needed. Often the biggest cost and latency win in the whole project.
What working with us looks like
| Detail | |
|---|---|
| Typical duration | Six to twelve weeks |
| Commercials | Fixed scope and a fixed number, agreed before work starts. No hourly billing. |
| Team | Senior-led. The people who scope the work do the work. |
| Code ownership | Yours outright, including the evaluation suite and infrastructure definitions |
| Evaluation | A labelled test set from your real cases, with thresholds agreed before build |
| After launch | Defect warranty, then optional managed operations |
AI Process Automation
It depends entirely on document quality and variability, and anyone quoting you a single number without seeing your documents is guessing. What we commit to is a measured accuracy figure on your documents before you commit to a build, plus confidence thresholds that route uncertain cases to a human rather than guessing.
Usually. We have integrated with everything from modern REST APIs to database-level access and scheduled file drops. Legacy integration is a scoping question, not a blocker — we establish it during the sprint.
In our experience it moves them off the repetitive portion and onto exceptions and judgement work. We would rather you heard that plainly than discovered it after the fact — and it is worth deciding what you intend before you automate, not after.
Other services
AI Consulting & Strategy
Find the two or three processes where AI actually pays, model the return, and prove it with a working prototype — in two weeks.
AI agent developmentAI Agent Development
Agents that take real actions in real systems — with tool access, guardrails, escalation paths and an evaluation suite that proves they work.
LLM & RAG integrationLLM & RAG Integration
Making your own data usable by a language model — retrieval that returns the right passage, answers grounded in sources, and measured accuracy.
Managed AIManaged AI Operations
Someone accountable for your AI system after launch — monitoring, evaluation, model migrations, cost control and a monthly report against the metric.
Let’s find out what AI can actually do in your business.
A 30-minute call. We will tell you honestly whether there is a case worth building — and if there is not, we will say so.