AI cost reduction (LLM FinOps)
Lower AI spend without losing quality: model cascades, caching, local models and per-task measurement.
Private AI: language models on your own servers, for data you can't send out
Open-source LLMs running on your own servers, with a confidentiality gate and fine-tuning, so you can use AI on sensitive data without sending it to the cloud.
01The problem
Confidential data (patients, legal cases, clients) rules out cloud AI, so the alternative has been not using AI at all.
02How we solve it
Open-source models (Llama, Qwen) served locally, QLoRA fine-tuning when needed, a confidentiality gate that decides what may go to the cloud, and quality measurement.
03How it works
-
Sensitive data
The use case involves patient, case or client data.
-
Confidentiality gate
A filter decides, by purpose, what may go to the cloud and what stays in-house.
-
Local model
Open-source models such as Llama and Qwen run on your server, fine-tuned when needed.
-
Measured answer
Quality is measured and compared with cloud models before production.
04What changes in practice
AI on confidential data. Patient, case and client data processed without leaving your servers.
Documented compliance. Data flows described for privacy laws such as Brazil's LGPD and for audits.
Proven quality. The local model is compared with cloud models before it goes into use.
05What you get
- Local model server
- Confidentiality gate by purpose
- Fine-tuning (when needed) with evaluation
- Documentation for data-protection reviews
06How the pilot works
- Scope
- One use case with sensitive data
- Timeline
- 4 to 8 weeks
What we measure
- quality compared with a cloud model
- cost per query
- data that no longer leaves your servers
Metrics are agreed before we start. With the numbers in hand, you decide whether to move to production.
07Pricing
Pricing
Custom quote after a free assessment (hardware and licenses not included)
Billing: project plus ongoing support.
Every project is quoted in writing after a free assessment, in US dollars or euros.
08Who it's for
- Law firms and teams bound by professional secrecy
- Hospitals, clinics and labs
- Lenders, credit unions and public agencies
Industries where this service comes up most:
09Frequently asked questions
How much does it cost to run AI on your own servers?
Every project is quoted after a free assessment, based on scope, volume and the systems involved. You get a fixed-price proposal in writing before any work starts.
How long does it take to put a local model into production?
The pilot takes 4 to 8 weeks. Typical scope: one use case with sensitive data.
Are local models good enough?
For many tasks, yes. We measure quality against cloud models before deciding.
What server do I need?
It depends on the model and the volume. The assessment sizes the hardware before any purchase, and many cases run on a single dedicated GPU.
Who builds it
Osney A. de Souza
AI engineer · Joinville, Brazil
Five years of software development and AI systems in production. The person who handles your project is the one who designs it and writes the code.
- Runs an AI-assisted audit platform in production, backed by thousands of automated tests
- License plate recognition with deep learning for large-scale video monitoring
- Software Engineering student (Univille, expected 2027)
Free assessment
Let's see if this fits your case
Tell us how the process works today, the rough volume and the systems involved. If it makes sense, you'll get a pilot proposal with scope, timeline and metrics.
Send an emailjuniorthesouza017@gmail.com
Message on WhatsApp(47) 98864-2296
Tell us about the process, the rough volume and the systems involved. You'll hear back from the engineer who would build it.
Related services
AI adoption: assessment, pilot and training
From “we want to use AI” to a measured pilot in production, with security and privacy built in.
AI governance: EU AI Act, NIST AI RMF and ISO/IEC 42001
Inventory, risk classification, technical evaluation and documentation of your AI systems to answer customers in the EU and the US. A gap assessment, not a certification.