iFigure — A Next-Generation Enterprise AI Agent with RAG

iFigure is an enterprise-grade AI solution designed for organizations that require precision, control, and security. Built on a Retrieval-Augmented Generation (RAG) architecture, iFigure leverages the enterprise search engine Kavunka to access internal and external knowledge sources.

The solution is delivered for on-premise deployment on the customer’s infrastructure and is ideal for:

• Customer portal and SaaS platform support
• Internal corporate knowledge assistants
• Technical and regulatory documentation systems
• Engineering and legal knowledge bases

iFigure is not just an LLM with search. It is a multi-stage intelligent system designed to ensure answer quality and reliability.

1. Analysis — Intelligent Query Understanding

At this stage, iFigure:

• Analyzes the user’s question
• Extracts key terms
• Identifies the query type (fact, instruction, calculation, comparison)
• Builds structured query objects

Result: a precise search profile instead of a vague keyword request.

2. Search — Deep Retrieval via Kavunka

iFigure sends structured search queries to Kavunka and retrieves:

• Relevant paragraphs
• Extracted document fragments
• Technical descriptions
• Regulatory excerpts

Importantly, the search returns specific text fragments, not entire documents — significantly reducing noise.

3. Learning — Extracting Core Meaning

iFigure:

• Analyzes retrieved paragraphs
• Identifies key phrases and semantic blocks
• Determines which fragments truly answer the question

This stage performs semantic filtering — the system does not merely read text; it isolates meaningful information structures.

4. Thinking — Structured Prompt Construction

At this stage:

• Irrelevant information is removed
• A strict system context is formed
• A controlled prompt is prepared for the LLM

The LLM receives only verified and relevant information.

5. Answer — Controlled Generation with PWG

A key differentiator of iFigure is PWG (Permitted Word Generation) technology.
During inference:

• The model may generate content only using words and facts present in the system context
• If a non-relevant word is produced, it is removed
• If a generated text block goes beyond the approved context, it is discarded
• The model retries generation within the permitted constraints

This ensures:

• Hallucination control
• No fabricated data
• Strict source grounding
• Predictable system behavior

Security

• On-premise deployment
• Full data ownership and control
• No third-party data exposure

Source Governance

• Answers generated strictly from indexed data
• Source traceability
• Transparent response formation logic

Operational Control

• Token-level generation control
• Customizable filtering rules
• Adaptation to industry-specific compliance requirements

Scalability

• Multi-user portal support
• Enterprise-wide deployment
• API integration with CRM, ERP, PLM, and other systems

• Complex product technical support
• Engineering enterprises
• Financial and legal organizations
• Manufacturing companies
• SaaS platforms with extensive documentation

iFigure is not just an AI chatbot. It is a controlled, secure, and enterprise-grade knowledge generation system built on RAG.

Together with Kavunka, you gain:

• Precision
• Security
• Hallucination resistance
• Generation control
• Full on-premise deployment

If your organization needs an AI system that does not invent information but works strictly within your data — iFigure is built for that purpose.