Native AI Development & Data Sovereignty
Custom AI apps built for your business and hosted on hardware you own, so your data stays under your control.
Your data, your hardware, your rules
Most AI tools send your documents and questions to someone else’s servers. Native AI runs the model on a machine in your office or data centre. You decide who uses it, what it can see and where the data lives.
Data stays in your building
Prompts, documents and answers stay on your network. Nothing goes to an outside AI provider unless you choose to send it.
You control access
Logins, roles and audit logs decide who can ask what, and every query can be traced.
Costs you can plan
You pay for hardware once and use the app as much as you need, instead of paying per message or per seat.
Works without the internet
Apps keep running on your local network during outages, and can be fully cut off from the internet if you need that.
AI apps and the machines they run on
Tap a service to see what it covers.
- Custom AI app development
- Private assistants over your documents
- Document and data processing
- On-premises model hosting
- Hardware sizing and setup
- Security and access control
- Integration with your systems
- Support, monitoring and model updates
01Custom AI app development
Chat assistants, internal copilots and tools built around how your team works, with a simple web interface that opens in any browser on your network.
Ask about this →02Private assistants over your documents
An assistant that answers questions from your policies, manuals, contracts and records, and shows which document each answer came from. This approach is called retrieval-augmented generation (RAG).
Ask about this →03Document and data processing
Read invoices, forms and scanned files, pull out the fields you need, classify and summarize them, and send the results into your systems.
Ask about this →04On-premises model hosting
We install and tune open-weight models for text, speech and vision, such as Llama, Mistral, Qwen and Whisper, on your own machines, and pick the size that fits the job.
Ask about this →05Hardware sizing and setup
We size the machine to the app: a mini server or compact workstation, the RAM the models need, and a GPU only when the workload calls for one. Then we set it up, install the drivers and models, and test it on your network.
Ask about this →06Security and access control
User logins, role-based access, audit logs, encrypted storage and network rules, with a fully offline (air-gapped) option.
Ask about this →07Integration with your systems
Connect the AI to your ERP, CRM, databases, email or WhatsApp through APIs, without the data leaving your network.
Ask about this →08Support, monitoring and model updates
Updates, backups, performance checks and newer models when they do the job better.
Ask about this →Hardware sized to the app, not the other way round
Indicative tiers. We confirm the final sizing after a workload check: how many people use it, how much data it reads and how fast it needs to answer.
Starter: mini server
A compact PC or mini server with 32 to 64 GB of RAM, CPU only or a small GPU. Suits document Q&A for a small team, transcription and form reading with small models.
Team: workstation server
64 to 128 GB of RAM and one GPU with 16 to 24 GB of memory. Suits an assistant used by a department, with quick replies from mid-size models.
Department: GPU server
128 GB of RAM or more and one or more GPUs with 48 GB of memory or more. Suits larger models, many users at once, vision work and fine-tuning.
How a native AI project runs
- Workload checkWho will use it, what data it needs and how fast it must answer.
- Models and hardwareWe pick the models and size the machine.
- Build the appInterface, logic and connections to your systems.
- Install on your premisesSet up, secured and tested on your network.
- Test with your teamReal questions and real documents, then adjustments.
- Support and updatesMonitoring, backups and better models over time.
Services that pair with this one
Most projects need more than one skill. These are the services clients most often combine with this one.
Frequently asked questions
What is data sovereignty?
Keeping your data under your control, in the place and jurisdiction you choose. With native AI, the model, your documents and the logs all sit on hardware you own.
Do I need a GPU?
Not always. Small models and some tasks run on a CPU with enough RAM. A GPU makes chat-style apps faster and lets you run larger models. We recommend one only when the workload needs it.
Is a local model as good as ChatGPT?
For focused business tasks, a well-chosen open model that reads your own documents often does the job well. For broad general knowledge, the largest cloud models are still ahead. We’ll tell you where that trade-off sits for your use case.
Can it work without the internet?
Yes. Once installed, the app and models run on your local network. Internet access is only needed for updates, and even those can be done offline.
Does this help with India’s DPDP Act?
Keeping personal data on your own servers makes it easier to control who processes it and where, which supports compliance with the Digital Personal Data Protection Act, 2023. It is not a substitute for legal advice.
Can it connect to our existing software?
Yes, through APIs to your ERP, CRM, databases, email or messaging tools, all inside your network.
Plan your native AI setup
Tell us what you want the AI to do and what data it needs. We’ll suggest the models and the hardware.
From the blog: Native AI Development & Data Sovereignty
Read what we’ve written about native AI development and data sovereignty.
