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Private AI & On-Premise LLM Deployment in Bangladesh
AI that runs inside your walls.
For banks, NBFIs, telecoms, hospitals and government. We deploy AI assistants on your own servers or private cloud using open models, so documents and customer data never leave your control — with the same safety rules, access controls and audit logs as our other solutions.
Illustration · sample business
The problem
Why regulated companies cannot use public AI tools.
Staff already paste internal text into public chatbots. For many organisations that is a policy and compliance risk.
Customer and internal data copied into outside services.
Banking, health and government rules limit where data may go.
No record of what was asked or answered.
Staff use personal tools because nothing approved exists.
How it works
From requirements to a running private AI.
Your IT and security teams stay in control.
Use cases, data types and rules.
Servers, model choice and network design.
Installed on your hardware or private cloud.
Your documents and directory connected.
Tested with your security team.
Monitoring, updates and new use cases.
Model, documents, index and logs on your infrastructure.
Access through your directory and roles.
Customer data sent to public AI services.
What we build
Six parts of a private AI deployment.
Designed with your IT and security teams.
Model selection
The right open model for your use case and hardware.
- Bangla and English ability
- Size vs speed balance
- Tested on your tasks
On-premise install
Runs in your data centre or private cloud.
- Your servers or GPU
- Air-gapped option
- Documented setup
Private knowledge
Your documents searched locally.
- Policies, circulars, manuals
- Version control
- Answers with sources
Access & audit
Fits your security model.
- Directory and roles
- Full question and answer log
- Retention by your policy
Use-case apps
Assistants your staff actually use.
- Staff knowledge assistant
- Document AI
- Customer-service drafts for review
Operations
Ongoing care with your IT team.
- Monitoring and updates
- Model upgrades when you approve
- Monthly report
Example use cases
What private AI does for regulated teams.
Real work, inside your network.
Example uses for sample organisations. Your deployment follows your own data and access policies.
Safety
Security your auditors can check.
Designed for regulators, auditors and security teams.
Answers are generated inside your network.
Directory, roles and data classification respected.
Questions, answers, sources and users recorded.
Model and software updates only with your approval.
Connects to
Fits your infrastructure.
Works with the infrastructure your IT team already runs. The names below are examples, not partnerships.
From an SEO agency
Trust that shows in public, too.
A clear, public explanation of how you use AI responsibly builds trust with customers and regulators. We help you publish it accurately.
- A responsible-AI page that matches what you actually do.
- Clear privacy wording for AI features.
- Consistent facts about your services across the web.
- Schema and FAQs so AI assistants describe you correctly.
Before and after
What changes for your organisation.
AI benefits, without data leaving.
| Task | Today, by hand | With the AI assistant |
|---|---|---|
| Staff using AI | Personal public tools | Approved private assistant |
| Data location | Unknown outside services | Your own servers |
| Audit | No record | Every question logged |
| Document search | Manual, slow | Answers with sources |
| Updates | Uncontrolled | Through your change control |
Who it is for
Built for regulated organisations.
Where data location matters most.
Circulars, policies and operations.
Compliance and customer-service drafts.
Process knowledge and support drafts.
Admin SOPs and records support.
Document search and citizen-service drafts.
The process
How we build it with you.
Nothing goes live without your written approval. Your IT and security teams approve each stage.
Use cases, data and compliance needs.
Architecture, model and hardware plan.
Small deployment on test data.
Security review and rollout.
Monitoring, updates, new use cases.
What you give us
- Use cases and the teams involved
- Infrastructure details and security requirements
- Sample documents or test data
- Contacts in IT, security and compliance
What you get
- A private AI running in your environment
- Use-case assistants for your staff
- Access control and full audit logs
- Documentation and ongoing support
FAQ
Private AI deployment questions.
It means running AI models and assistants on your own servers or private cloud, so documents and customer data stay inside your network instead of going to public AI services.
Several open models handle Bangla and English. We test candidate models on your own tasks before choosing one.
Usually yes for good speed. We size the hardware to your use cases and number of users, and can start small.
Yes. Answers can be generated fully inside your network; updates are delivered through your IT team.
We design to your compliance requirements and work with your compliance team. Final compliance decisions remain yours.
Common uses are policy and circular questions, document search, document data extraction and drafting replies for human review.
Only if you approve a specific, read-only use case. By default it works on documents, not account data.
Documents update as your teams publish new versions; model and software updates happen through your change control.
It depends on infrastructure and approvals. We start with a proof of concept and share the plan before work begins.
Share your use cases and infrastructure needs. A senior team member replies within one working day to arrange a confidential discussion.
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