AI & Automation
AI that does work, not demos.
Assistants, agents, document intelligence and automated workflows — grounded in your own data, evaluated against real cases, and shipped into production.
The problem
The pilot impressed everyone. Then it met the edge cases.
A language model demo is easy. What is hard is the part afterwards: grounding answers in your actual documents, handling the case the model gets confidently wrong, and knowing whether last week's prompt change made things better or worse.
Most stalled AI projects did not fail technically. They failed because nobody defined what a correct answer was, so nobody could tell when the system stopped producing one.
How we solve it
Start from the evaluation, not the demo.
We begin by writing down what a good answer looks like on real cases from your business, then build the retrieval and prompting to hit it — so every later change can be measured rather than argued about.
Systems ship with citations back to source documents, a confidence threshold that routes uncertain cases to a person, and logging that shows exactly what the model saw.
03What is included
Capabilities in this service.
- Use-case selection and feasibility assessment
- Retrieval-augmented generation over your own content
- Document extraction, classification and validation
- AI assistants for customers and for internal teams
- Agents that execute multi-step workflows across your tools
- Evaluation sets, regression testing and prompt version control
- Human-in-the-loop review, guardrails and cost controls
What good looks like
- Answers that cite the document they came from
- Uncertain cases routed to a person instead of guessed at
- A measurable baseline, so changes can be proven
These are the standards we hold the work to — not results claimed on someone else's behalf.
04Process
How the engagement runs.
01
Discover
1–2 weeks
Understand the business problem before proposing a technical one.
02
Design
2–4 weeks
Decide the model, then the screens.
03
Build
4–16 weeks
Ship in slices that work end to end.
04
Launch
1–2 weeks
Go live without holding your breath.
05
Grow
Ongoing
Iterate against what real usage tells you.
05Technology
What we build it with.
Defaults, not dogma. Where your team already runs a stack, we work in it.
Models
- Claude
- OpenAI
- Open-weight models
Retrieval
- Vector search
- PostgreSQL + pgvector
- Hybrid ranking
Runtime
- Node.js
- Streaming APIs
- Queues
- Evaluation harness
06Relevant work
Software we have built in this discipline.
Live toolRequirements Generator
Turns a rough idea into a structured requirements document — scope, features, stack and milestones — ready to send to any developer.
Generate a brief
Live toolWebsite Checker
Scores any public website on SEO, mobile, security and Core Web Vitals, then writes a prioritised fix plan.
Run a check- Live tool
Avryxa Assistant
The assistant on this site — grounded in the site's own content, so it answers from what we actually publish.
Ask it something
07Questions
Before you ask.
Wherever you require it to go. We work with providers that offer no-training guarantees, and can deploy against a model in your own cloud tenancy where policy demands it. Retention and logging are configured deliberately, not left at defaults.
Retrieval grounds answers in your documents and every response cites its sources. Where a question falls outside what was retrieved, the system is built to say so and hand off rather than improvise.
A narrow, high-volume task with a clear right answer — document extraction, first-line support, internal search. Two to four weeks to a working system evaluated against real cases.
Model routing by task difficulty, caching, and hard budget ceilings with alerting. Cost per resolved case is tracked from the first week.
Yes, and that is often the better path. Adding retrieval and assistance to a product people already use beats launching a separate AI product nobody has a habit around.
Keep exploring
Other services.
- Custom SoftwareBusiness systems, internal tools and workflow platforms built around how your company actually operates.
- Web ApplicationsScalable, fast, customer-facing web applications and platforms built on modern frameworks.
- Mobile ApplicationsiOS and Android applications — native and cross-platform — built to survive real-world networks and devices.
Start here
Good software starts with a straight conversation.
No pitch deck, no discovery fee. Describe the problem and we will tell you what it would take to solve it — and what it would cost.