Internal system integration
Runs inside the corporate network alongside LDAP, ticketing, CRM, DMS and knowledge base systems.
Closed-network chatbot architecture
Offer AI-powered support while keeping corporate data inside.
The on-premise architecture runs the knowledge base, the model layer and the integrations inside the corporate network. Security, logging, authorisation and audit processes follow your own standards.
Closed-network deploymentRole-based accessAuditable logsCorporate knowledge base
Secure architecture
Data stays inside the corporate boundary
Data leaving for outside services
Prompts, documents and answer content are never sent out
Corporate networkRunning
Model layer
Runs on corporate hardware
Knowledge base
Corporate documents and records
Authorisation
Role-based access (RBAC)
Audit log
Every answer on the record
Every component sits on corporate hardware, and integrations run over the internal network.
Closed network
No external internet access needed
RBAC
Role-based authorisation
Audit
End-to-end audit trail
Compliance
Data protection law and corporate policy
Architecture layers
Everything runs inside the corporate network — the knowledge base, the model and the integrations.
Security, logging, authorisation and audit processes follow your own corporate standards.
Safe answer generation
Answers rest only on authorised sources, and control layers handle sensitive content.
Audit trail
User, source, answer and action records are kept in a form security teams can review.
Secure answer path
From the question to the audit record, every step stays inside the corporate network.
Answers rest only on authorised sources, and control layers step in for sensitive content.
1
The question comes from inside
An employee asks from an interface on the corporate network or from the existing portal.
2
Identity and permission are checked
The role of the user is verified centrally through LDAP or Active Directory.
3
Permitted sources are retrieved
The answer is assembled only from documents and records the user is allowed to reach.
4
The model runs on site
Prompt and document content are processed without leaving corporate hardware.
5
The safety filter is applied
Sensitive content, masking and content control rules run before the answer goes out.
6
Sourced answer and record
The answer returns with source references, and user, source and action are written to the audit log.
No prompt, document or answer is ever sent to an external service.
On-prem · deployment modelRBAC · access controlAudit · logging layer
Audit and control
Answer, source, user and action all stay traceable end to end.
Finance, public sector, defence, healthcare and other regulated industries get a chatbot experience that fits their data policies.
- Data sovereignty is preserved
- Access to knowledge becomes controlled
- Internal support load drops
FinancePublic sectorDefenceHealthcareRegulated industries
Audit record
Recent activity
09:42Answered
a.yilmaz
Payroll Policy v3
09:41Access denied
m.demir
Board Meeting Note
09:39Answered
s.kaya
Procurement Instruction
09:37Masked
e.arslan
Finance Report · Confidential
Records can be forwarded to your corporate SIEM and log management tools.
Rollout
The on-premise chatbot goes live through a controlled rollout in three steps.
The infrastructure lands in your environment, permissions map to your central identity provider, and usage and quality are audited on a regular cadence.
The infrastructure is placed
The model, services and data sources are deployed into your environment.
Model server
GPU or CPU on corporate hardware
Vector database
Storage inside the organisation
Application service
Reached over the internal network
Permissions are connected
User roles and source access map to the central identity provider.
HR teamPersonnel documents
FinanceBudgets and reports
All employeesGeneral procedures
Answers are monitored
Usage, quality and security records are audited on a regular cadence.
Weekly usage and audit report
On-Premise Chatbot
Let us map out a chatbot architecture that fits your security boundary.
We review your network topology, identity infrastructure and data classification policies, then prepare the deployment plan.