An AI assistant in action
Four business scenarios. Documented response times. Editorial changes disclosed.
Processed locally on our own hardware, without an external model API or cloud AI.
What can local AI actually do?
For this study, we put our own AI assistant to work on real business tasks: from client quotes and customer communication to technical support. This is our own benchmark (proof of concept), not a client project. All test content was processed on our own hardware using locally executed models. No external model API or cloud AI was used for processing. The displayed times are single measurements from the original test run, not a performance guarantee.
The Results
Complete Client Quote
A full quote with package recommendation, pricing table, and signature
Privacy argument
A compelling case for local AI vs. ChatGPT
Response edited for accuracy
Follow-Up Email
A professional follow-up email to a business partner
Response edited for accuracy
Technical Support
Website performance explained for non-techies
Response edited for accuracy
How to read the measurements
The four scenarios shown each document one test run with qwen3:14b. They are a snapshot, not a comparison of different models.
Four individual tests
- ✓ Model: qwen3:14b
- ✓ Four business scenarios
- ✓ 12.7 to 29.7 seconds
- ✓ Three edits disclosed
No generalization
- – No multi-model comparison
- – No test of automatic model selection
- – No availability measurement
- – No guaranteed response time
Ready for your own in-house AI?
Comparable results are possible in your business as well, depending on hardware, model, and use case. With a properly configured local solution, the content submitted for processing is handled within your infrastructure.
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