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Techoptionz

AI Solutions

AI solutions and workflow automation

We build AI into software that people actually use at work — document and image processing, extraction and classification, assistants grounded in your own data, and automations that remove repetitive steps. We scope AI work against a measurable baseline, so you can tell whether it worked.

Outcomes

What you get out of it

  • Repetitive document and data-entry work handled automatically
  • Faster turnaround on quoting, matching and classification tasks
  • Answers drawn from your own documents rather than a generic model
  • A measured before-and-after, not a demo

Deliverables

What we deliver

  1. 01AI feasibility assessment against a measured baseline
  2. 02Data readiness and privacy review
  3. 03Prototype on your real data
  4. 04Production integration into existing systems
  5. 05Evaluation harness and accuracy monitoring
  6. 06Human-in-the-loop review workflows

Typical stack

  • Python
  • TypeScript
  • Claude API
  • OpenAI API
  • Vector databases
  • AWS

Proof

Where we have done this

Real systems that used this capability.
Software productsAustralia

AI capability built into an existing software product

AI features engineered into production software for an Australian software company — scoped, prototyped and integrated rather than bolted on.

  • Python
  • TypeScript
  • LLM APIs
  • REST APIs
Read the case study

Questions

AI Solutions FAQs

01How do you stop an AI feature from making things up?
Three things, in order of importance: ground the model in your own data rather than its training memory, constrain output to a schema the system validates, and route low-confidence cases to a human. We also build an evaluation set from your real examples so accuracy is measured, not assumed.
02Does our data get used to train someone else's model?
Not under the enterprise API terms we deploy on, which exclude customer data from training by default. Where data cannot leave your infrastructure at all, we scope self-hosted models instead. This is settled during the data readiness review, before any build starts.
03What does an AI project cost to run each month?
Inference cost depends on volume and model choice, and is usually a small fraction of the cost of the manual work it replaces. We model the running cost during the feasibility phase so there are no surprises, and design for the cheapest model that clears your accuracy bar.

Next step

Have a project worth scoping properly?

Tell us what you are trying to build. If it is a fit we will say so, and if it is not we will tell you that too.

Start a conversationhello@techoptionz.com
  • 01An engineer reads itUsually within one business day.
  • 02A 30-minute callProcess, constraints, deadline.
  • 03An honest answerA way forward, or a clear no.