01 / HARDWARE
Choose the right hardware.
We size compute, memory and storage around your model, users, response-time needs and budget.
WHAT YOU RECEIVEHardware specification & purchasing recommendations
POSSEAI / AI LAB
AI models.
Deployed locally.
Hardware selection, server setup, model fine-tuning and evaluation — delivered by one team.
Plan your deployment ↗MODEL ADAPTATION LOCAL DEPLOYMENT ONGOING OPERATIONS
01 / COMPLETE LOCAL AI DELIVERY
From choosing hardware
to a working local model.
One delivery process, with a clear result at every step.
02 / MODEL FINE-TUNING
Fine-tuned
for your business.
Adapt a model to your terminology, task requirements and expected output. Prepare the data, train the model and test it on examples it has not seen.
EXAMPLE INPUT
“Pump P-104 is leaking at North Site. Please arrange an inspection. Site access has not been confirmed.”
A general answer.
You should arrange an inspection of the leaking pump and confirm access with the site team.
The team still needs to turn the reply into a job record.
A usable job record.
- Equipment
- P-104
- Location
- North Site
- Reported issue
- Leak — inspection required
- Access
- Not confirmed
- Next step
- Confirm site access before scheduling
Illustrative input and target format. Actual improvement is measured on your evaluation set.
Company examples→Data preparation→Fine-tuning→Held-out evaluation
03 / MEASURED BEFORE HANDOVER
See how
your model performs.
Compare the baseline and fine-tuned model on the same test set. Review quality, response time and hardware requirements before approving deployment.
MODEL EVALUATION
Report previewBaseline vs. adapted model
| Evaluation measure | Base model | Fine-tuned model | Acceptance criteria |
|---|---|---|---|
| Business task completion | Awaiting test | Awaiting test | Agreed task success rate |
| Domain terminology | Awaiting review | Awaiting review | Correct use in test cases |
| Output format compliance | Awaiting test | Awaiting test | Required fields & structure |
| Response time | Awaiting benchmark | Awaiting benchmark | Target workload & concurrency |
| Memory & resource usage | Awaiting benchmark | Awaiting benchmark | Selected deployment hardware |
Same test setRecorded configurationReviewable results
Agree the target. Define useful results and acceptance criteria before training.
Inspect the failures. Review missed cases and decide what to improve or route to a person.
Make the rollout decision. Deliver the report alongside the model and deployment configuration.
04 / DEPLOYMENT & HANDOVER
A local model.
Ready for your team.
Give employees a way to use the model, or connect it to existing software. We configure access, document the setup and help your team operate it.
- Internal web interface or API access
- Business system integration
- Operating documentation & team training
- Agreed monitoring, maintenance & model updates
YOUR INFRASTRUCTURE
Local model service
↓Local model service
EmployeesBusiness systemsAgent & Chats
Data flows and external connections are defined for your deployment.
A FEW THINGS TO KNOW
Good questions.
01 / GOOD TO KNOW
Test against agreed requirements.
We compare the base and adapted model on agreed test cases, review task quality and benchmark performance on the target hardware. You receive the results and an acceptance recommendation.
LET’S BUILD SOMETHING USEFUL
Plan your
local AI deployment.
Tell us your use case, existing hardware and deployment requirements.
Talk to AI Lab ↗