AI Practice
Intelligence, engineered in.
Not an AI demo. Alisys builds AI into products that ship — agents that do work, systems that understand your data, automation that removes the busywork. Thirteen capabilities, one engineering team.
the practice
One AI application.Many moving parts.
AI across the lifecycle
- AI + Product
- AI + Automation
- AI + Data
- AI + Engineering
- AI + Customer Experience
- AI + Operations
how we ship ai
From business case toproduction.
- 01
Find the value
Where does AI remove real cost or risk? We start with the business case, not the tech.
- 02
Prototype fast
A working slice in days — enough to judge quality, latency and cost with real data.
- 03
Build the eval
A test set that scores every change, so quality is measured, not felt.
- 04
Add guardrails
Input/output checks, retrieval grounding, cost limits and a human fallback.
- 05
Ship to production
Wrapped in a real UX, monitored, with the cost per request known.
- 06
Operate & improve
MLOps: monitoring, drift detection, prompt and model updates over time.
ai + everything
AI isn't a silo.It runs through the work.
- AI + PRODUCTSmarter featuresDrafting, search, recommendations and assistants inside your product.
- AI + AUTOMATIONLess busyworkDocument handling, triage, data entry and back-office workflows.
- AI + DATAUsable intelligencePipelines, embeddings and analytics that turn data into decisions.
- AI + ENGINEERINGFaster deliveryAI-assisted coding and testing — with humans owning the outcome.
straight answers
The questionsthis raises.
Both — but we default to the most reliable, lowest-cost option. Most business problems are solved by integrating a hosted model (OpenAI, Anthropic, Gemini) with your data via retrieval. We build or fine-tune custom models when the data and the problem genuinely require it.
Retrieval over your own sources, structured output, an evaluation set that runs on every change, guardrails on inputs and outputs, and a human fallback path. We treat "it answered wrong" as a bug with a test, not an acceptable quirk.
We design for cost from the start — caching, model routing (cheap model first), token budgets and usage limits — and we show you the per-request cost before launch so there are no surprise bills.
Yes. AI Integration is one of our most common engagements — adding drafting, search, classification, summarisation or automation to software you already run, without a rebuild.
You do. We hand over readable code, the evaluation set, the prompts and the deployment config — and we can stay on for MLOps and monitoring if you want us to.
start
Where would AI actually help?
Tell us the problem. We'll come back with whether AI is the right tool, and if so, the fastest path to a production system.