Group KG + ChatBI
KG drives natural-language analytics for business users.
Evidence notice: cases, figures and inferred project metadata are unverified scenario illustrations, not established client outcomes, credentials or return promises. Signed contracts define scope, fees, baselines, acceptance and data responsibilities; client business data stays off-chain.
1. Project Overview
- Customer type
- Top-tier Cross-industry enterprises
- Project duration
- 10–16 weeks
- Tech stack
- Knowledge / RAG · ChatBI / NL2SQL · Graph neural networks
- Deployment
- Hybrid cloud
2. Business Context & Pain Points
The customer is a Enterprise / Group player in General, with the core pain concentrated in "Knowledge & Q&A". Manual workflows and point tools could not scale or stay consistent, driving up response time, operating cost and compliance risk. This project delivered an end-to-end AI upgrade for that workflow.
3. Solution
Anchored on "Multimodal Data Governance & Vector Lake Platform", Global AI DAO integrated the following capability stack into a single solution:
- Knowledge / RAG —— Wired into the critical business path across ingestion, inference and human-in-the-loop collaboration.
- ChatBI / NL2SQL —— Wired into the critical business path across ingestion, inference and human-in-the-loop collaboration.
- Graph neural networks —— Wired into the critical business path across ingestion, inference and human-in-the-loop collaboration.
- Deployment: Hybrid cloud, balancing data compliance, performance SLA and operability.
4. Quantified Outcomes (Before vs After)
Source metric: 90%+ NL-analytics accuracy.
5. Specs & Fit
| Governance | Cleaning / labeling / vectorization / KG |
| Multimodal | Text / image / video / audio |
| Real-time ingest | Kafka / CDC / API |
| P95 retrieval | <80ms at billion-scale |