AI Solutions
Private AI
For data that can't leave your control, we run AI models on-device, on your own servers or in your own cloud account. You get the benefit of AI without sending sensitive information to a third-party service.
Your data never leaves
Private by designIs this for you?
You’ll get value from this if…
- Your data is regulated, confidential or under NDA
- Policy forbids sending data to public AI services
- Your product must work offline
- You want predictable costs without per-call fees
Benefits
What changes for your business
Data stays in your control
Nothing is sent to a third-party AI service.
Works offline
On-device models keep working without a connection.
Predictable cost
No per-request fees from an outside provider.
What you get
What we deliver
Model selection
Open models chosen and tested for your task and hardware.
Private deployment
Running on-device, on your servers or in your cloud account.
Security controls
Access control, logging and data handling that fit your policy.
Performance tuning
Optimised so it runs fast enough on the hardware you have.
How it works
From first call to running in production
- 01
Requirements
Where data may go, what hardware is available, what quality is needed.
- 02
Evaluate
Benchmark open models on your own examples.
- 03
Deploy
Package and run the model in your environment.
- 04
Operate
Monitor, update and hand over.
Example applications
What this looks like in practice
Typical applications of this service. Illustrative, not client case studies.
- 01On-device transcription for confidential recordings
- 02Document search over sensitive files on your own servers
- 03Classification of regulated data inside your cloud account
- 04Offline AI features in desktop and mobile apps
Shipped work
Where we've built this
Technology
Tools we work with
- Whisper
- Open-source LLMs
- Ollama
- Docker
- GPU servers
- AWS
Why Bitfumes
Built by engineers who ship
Senior team, no hand-offs
The engineers on your first call are the ones who build your product.
10+ years of engineering leadership
Led by Sarthak Shrivastava, Docker Captain, AWS Certified Solutions Architect, AWS Certified Developer.
We teach this for a living
156K+ developers learn from our founder on YouTube, and 100K+ on Udemy.
Production, not prototypes
Tests, monitoring and handover are part of every build, not extras.
How to start
From first conversation to production
- 1
Talk to us
Tell us the problem. We come back with a straight view on whether it is worth building.
Get in touch - 2
Build
A senior team embeds with yours and ships in short cycles, with a demo every week.
- 3
Run and improve
We hand over cleanly, or stay on to monitor, support and extend what we built.
FAQs
Common questions
Are private models as good as the big cloud models?
For many focused tasks, such as transcription, classification and extraction, open models are close enough. For open-ended reasoning, cloud models often still lead, and we will tell you where that trade-off falls for you.
What hardware do we need?
It depends on the model. Some run on a laptop; larger ones need a GPU server. We size this during evaluation.
Can you give an example?
Our AudioBolo app runs a Whisper speech model on the Mac itself, so audio is transcribed on-device and never uploaded.
Can private AI meet compliance requirements?
Keeping data in your environment removes a major compliance risk. We design access, logging and retention to fit your specific obligations.
Do we lose access to model updates?
No. You choose when to update, and we can test new model versions before they go live.
Insights
Related reading
Next step
Want this built into your business, not just explained?
Tell us the problem and we'll come back within one business day with a straight view on whether AI is worth it for you, and what it would take to build.
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