Top-broker private deployment
Single platform powers research, compliance and service with unified data and models.
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 Banks / brokers / insurers
- Project duration
- 10–16 weeks
- Tech stack
- Multimodal backbone
- Deployment
- Private deployment
2. Business Context & Pain Points
The customer is a Enterprise / Group player in Finance, with the core pain concentrated in "Service & CX". 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 "Enterprise Native Multimodal Model Platform", Global AI DAO integrated the following capability stack into a single solution:
- Multimodal backbone —— Wired into the critical business path across ingestion, inference and human-in-the-loop collaboration.
- Deployment: Private deployment, balancing data compliance, performance SLA and operability.
4. Quantified Outcomes (Before vs After)
| Metric | Before | After | Delta |
|---|---|---|---|
| time-to-prod | 100% | 40% | -60% |
Source metric: -60% time-to-prod, 70%+ cross-business reuse.
5. Specs & Fit
| Deployment | Private / hybrid cloud / on-premise |
| I/O | Text / code / audio / image / video |
| Min cluster | 4×A800 or NPU equivalent |
| Hallucination control | RAG + knowledge-graph cross-check |
| SLA | 99.9% availability, 24/7 support |