AI You Can Audit. Built on Data You Control.
Weefer AI delivers Generative AI Assistants and AI Agents that work with your enterprise data, supported by a governed Data Foundation, Security, Access Control, and Audit Trails for enterprise needs.
Start with one use case. Validate with a PoC. Scale based on business needs.
Enterprise AI Requires More Than a High-Performing AI Model
Successful AI implementation also depends on Data Quality, Security, Access Control, and Governance to ensure AI works according to enterprise requirements.
AI Responses Without Clear Sources
Without a Retrieval Layer and governed data sources, AI may produce inaccurate answers that are difficult to verify or lack business context.
Data Access Without Proper Controls
Integrating AI with enterprise data and systems requires Access Control so information is available only to authorized users.
AI Automation Without Governance
AI Agents that execute cross-system workflows need Permission Control and Audit Trails so their activities can be monitored and reviewed.
One Foundation for Building Multiple Enterprise AI Solutions
Successful AI implementation also depends on Data Quality, Security, Access Control, and Governance to ensure AI works according to enterprise requirements.
Weefer AI Data Foundation
A data foundation combining a Data Warehouse, Retrieval Layer, and MCP Server to support data use and connect AI with enterprise systems.
Weefer AI Knowledge
An AI Assistant that helps employees find information in policies, SOPs, contracts, and operational data across multiple channels, with Source Citations for verification.
Weefer AI Agent
AI Agents designed to interact with SAP, HRIS, ITSM, and other enterprise systems through permission controls and action logging.
From Enterprise Data to Usable AI Solutions
Weefer AI connects data sources, a Retrieval Layer, AI models, and business systems in an architecture designed around use-case requirements, Security, and Access Control.
Enterprise Data
Documents, internal knowledge, operational data
Data Warehouse
Data prepared for AI use
Retrieval Layer
Relevant information from governed sources
AI Models
Models selected for the use case and deployment environment
AI Knowledge
Answers with Source Citation
AI Agent + MCP
Integration with business systems
ARCHITECTURE OVERVIEW
From enterprise data to governed AI workflows.
The main Weefer AI flow, from data sources to solutions used by teams.
01
Enterprise Sources
ERP, HRIS, documents, email, databases, and internal systems.
02
Data Foundation
Data Warehouse, data preparation, permissions, and data governance.
03
Retrieval Layer
Retrieves relevant context based on access permissions, with traceable sources.
04
AI Model Layer
AI models are selected based on use-case requirements and deployment options.
SOLUTIONS
Weefer AI Knowledge
An AI Assistant that finds information and provides answers with Source Citations.
Weefer AI Agent
An AI Agent that executes workflows through authorized system connections.
Teams
WhatsApp
Telegram
Other Chat Apps
1 / PREPARE
Weefer AI Data Foundation
A data foundation combining a Data Warehouse, Retrieval Layer, and MCP Server to support data use and connect AI with enterprise systems.
2 / RETRIEVE
Weefer AI Knowledge
An AI Assistant that helps employees find information in policies, SOPs, contracts, and operational data across multiple channels, with Source Citations for verification.
3 / CONNECT
Weefer AI Agent
The MCP Server enables AI Agents to interact with integrated SAP/ERP systems according to defined permissions.
A Data Foundation for Long-Term AI Needs
Successful AI implementation also depends on Data Quality, Security, Access Control, and Governance to ensure AI works according to enterprise requirements.
AI-Ready Data Warehouse
Enterprise data is prepared in a foundation designed to support its use by AI solutions.
Retrieval Layer
Relevant information is retrieved from governed sources to support AI answers that can be traced back to their sources.
Model Context Protocol (MCP) Server
The MCP Server connects AI Agents to enterprise systems based on defined permissions.
Reusable Architecture
The same foundation can be reused to support AI Knowledge and AI Agent development as business needs evolve.
Make Enterprise Knowledge Easier to Find and Verify
Weefer AI Knowledge helps employees access information from internal sources through an AI Assistant, without manually searching through multiple documents.
Enterprise Knowledge Assistant
Find information from policies, SOPs, contracts, and enterprise knowledge sources through conversations with AI.
Answers with Sources
Answers include Source Citations so users can verify the information sources used.
Multiple Access Channels
The assistant can be accessed through Microsoft Teams, WhatsApp, Telegram, or a custom web agent, depending on the implementation design.
Controlled Knowledge Access
Information access is designed to account for user permissions and the access rules of each data source.
Connect AI to Your Work and Business Systems
Weefer AI Agent supports AI-powered automation that interacts with enterprise systems through access controls and action logging designed for specific requirements.
Enterprise System Integration
Build integrations with SAP, HRIS, ITSM, and other systems based on use-case requirements.
Permission-Based Access
AI Agent access to systems follows defined permission mechanisms.
Auditable Actions
Data access and agent actions are logged to support review.
Expandable Use Cases
Start with one well-defined workflow, then expand integrations based on evaluation results.
Secure by Design. Built for Enterprise Control
Weefer AI considers Security, Data Privacy, Access Control, Audit Trails, and deployment options as part of the solution design, based on implementation requirements and configuration.
Role-Based Access Control
Data access rights are determined by user identity, role, and permissions according to the mechanisms implemented.
Row-Level Security
Where supported by the systems and configuration in use, access can be restricted to specific records so users only see data they are authorized to access.
Personal Data Masking
Personal Data Masking helps protect sensitive information by masking personal data during Data Ingestion, according to the implemented configuration.
Controlled AI Actions
AI Agents access systems through MCP using defined permission mechanisms.
Audit Trail
Data access and AI Agent actions are logged according to the solution’s capabilities and configuration.
Governance by Design
The solution design considers relevant governance and regulatory requirements, including Indonesia’s Personal Data Protection Law and OJK regulations where applicable.
Security controls, audit scope, and regulatory compliance must be validated against each enterprise’s architecture and requirements.
Choose an AI Environment That Fits Your Enterprise
Weefer AI supports model environments that can be tailored to Security, Data Residency, infrastructure, and internal enterprise policies.
AI Model Aggregator
Access AI models through an aggregator service suited to implementation requirements.
Huawei Cloud MaaS
Use AI models through Model-as-a-Service in the Huawei Cloud environment.
Private GPU
A private GPU environment for AI workloads that require dedicated infrastructure.
On-Premise
Deployment on enterprise infrastructure according to its architecture and internal policies.
Start With the Most Relevant Business Need
Choose a use case based on business needs, data readiness, and enterprise systems. Start with one clearly defined problem, then evaluate the results.
Human Resources
Help employees find HR policies, SOPs, and information through an AI Knowledge Assistant.
IT Service Management
Support information access and ITSM workflows with AI solutions for enterprise operations.
ERP & Enterprise Operations
Explore AI integration with SAP and other business systems to support operational needs.
Enterprise Knowledge Management
Make internal knowledge easier to access through answers with verifiable sources.
Cross-System Automation
Develop AI Agents to support cross-application workflows with permission controls and Audit Trails.
Not Sure Where to Start?
The Weefer team can help map your requirements and identify which use case to evaluate first.
Start With an Assessment. Validate the Solution. Scale Based on the Results.
A phased approach helps enterprises evaluate Data Readiness, validate solutions through a PoC, and determine the next implementation steps based on business needs.
Step 1
2 Weeks · FreeAssessment
Evaluate data sources, Access Control, Data Residency, and business requirements to identify priority AI use cases.
Output
Map data readiness and Security, identify initial gaps, and recommend a first use case.
Step 2
6 Weeks · Fixed PriceProof of Concept
Build and evaluate a solution for one department based on data, Security requirements, and agreed Success Criteria.
Output
An evaluable PoC before the enterprise decides on next steps.
Step 3
Phased · Based on NeedsScale
Expand the Data Foundation, MCP Server integrations, and AI Agent implementation based on PoC results and business priorities.
Output
AI solutions that can scale incrementally as enterprise needs evolve.
A Technology Partner That Understands Enterprise Environments
Weefer has delivered software and enterprise integration in Indonesia since 2004, including HR, ITSM, ERP, and customer service platforms.
Enterprise Technology Experience
Experience delivering business solutions and system integration for enterprises in Indonesia.
Huawei Premier Partner
Huawei technology partnership with solution options including Huawei Cloud MaaS and Private GPU.
Flexible Infrastructure
Flexible deployment options, including Huawei Cloud Indonesia and dedicated on-premises GPUs.
Integrated Implementation
An approach that connects the Data Foundation, AI solutions, system integration, Security, and Governance.
Build Enterprise AI on the Right Foundation
Assess your data readiness, Security requirements, and AI opportunities with a free two-week assessment from Weefer.
What You Need to Know About Weefer AI
Weefer AI is an Enterprise AI solution that delivers AI Knowledge and AI Agents on top of enterprise data, supported by a Data Foundation and Security and Governance mechanisms defined by the implementation design.
AI Knowledge helps users find information from internal sources with Source Citations. AI Agent is designed to support workflows and interact with business systems through defined permission mechanisms.
Not necessarily. Model environment options include Huawei Cloud MaaS, Private GPU, or on-premises deployment, depending on requirements and implementation architecture.
Weefer AI is designed to support integration with SAP, HRIS, ITSM, and other systems. Integration scope depends on the systems, available access, and use-case requirements.
The solution approach includes Access Control, Personal Data Masking, permission mechanisms for AI Agents, Audit Trails, and deployment options based on implementation needs.
Weefer AI Knowledge is designed to include Source Citations so users can check the information sources used in an answer.
The assessment takes two weeks and is free. The PoC phase is designed to take six weeks at a fixed price, while further development proceeds in phases.
No. An enterprise can start with one use case, evaluate the results, and expand the solution according to its needs and business priorities.
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