AI & Automation
AI that does a specific job inside your product or operations.
What’s included
Overview
The useful question is not “how do we add AI?” but “which task should it take off someone’s plate?”. We design and build AI features around concrete jobs: answering questions from your documents, extracting data from files, classifying and routing requests, drafting responses, or predicting an outcome from your data.
We choose between hosted models and open-weight models you run yourself based on cost, data sensitivity and accuracy, and we build evaluation into the product so quality is measured rather than assumed. Our own products — DialWise AI’s voice agents and Lauki’s food-response predictions — are built the same way.
What you get
Which tasks are worth automating, expected accuracy, running costs and risks.
A working version on your real data, with evaluation results.
Integrated into your product or tools, with monitoring and guardrails.
Test sets and metrics that show whether quality holds as models change.
How we work
The task, the users, the data and what “good enough” means.
A narrow working version tested against real examples.
Accuracy, cost and failure cases measured before anyone relies on it.
Production build inside your product or workflow.
Quality tracking, feedback loops and model updates.
FAQ
It should not be, and we design for that: we use providers and settings that exclude your data from training, or run open-weight models on infrastructure you control.
We agree a test set and success criteria at the start, measure against them before launch and keep measuring after launch.
Yes. For sensitive data we deploy open-weight models on your infrastructure. DialWise AI, our voice agent platform, supports fully local deployment.
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