Cloud, Your Own Server or Offline: Where Should Your AI Run?
Three ways to run AI in an Indian business, what each one costs you in control and speed, and how to pick one for your first job.
Your team sends invoices, contracts and customer details through email and WhatsApp every day. Before an AI reads any of it, you need to decide where that data will sit. That choice sets what you can automate and who can see your documents. There are three options, and none of them is right for every business.
Cloud AI
Your data goes to a provider you choose, such as AWS, Google Cloud or Azure. The models are the largest ones available, and it is the fastest way to start.
- Fits: supplier emails, product questions, drafts of reports. Documents that may leave your premises.
- Limit: your data is processed on someone else's servers. Read the provider's terms before you send customer records.
Your own server
We run open models such as Llama or Mistral on a server you own, in your office or a data centre you pick. Documents stay inside your network.
- Fits: customer and financial records that must not leave your control.
- Limit: you look after the hardware, and the models are smaller than the largest cloud ones.
Fully offline
The model runs on a machine with no internet connection. Nothing leaves that machine.
- Fits: your most sensitive documents, such as legal files.
- Limit: updates are manual and large jobs run slower.
How to choose for your first job
Start with the job, not the tool. Pick one repeat task that eats your team's week: reading invoices and entering them in Tally, answering the same customer questions on WhatsApp, or drafting a weekly report from your ERP. Then ask these questions.
- Would you be comfortable emailing these documents to an outside vendor?
- How many people use the result, and how fast must it answer?
- Who will look after the server if the work stays on your premises?
If the answer to the first is yes, start in the cloud. If it is no, start on your own server. If the documents are too sensitive even for your own network, go offline.
Keep a person in the loop
Whichever option you pick, a person should approve anything important. An assistant can read an invoice and prepare the Tally entry. Someone on your team confirms amounts above a limit you set.
Start with one pilot
We do not rebuild everything at once. First we sit with your team and find the repeat work. Then we build one job and run it in your environment, and you compare it with how you do it today. If it works, we extend it.
Each project is quoted in INR after the first review, so the first commitment stays small. See how it works, read the FAQ, or contact us on WhatsApp to book a free AI workflow review.