Gov hotline 12345 assistant
City-wide policies and how-to guides inlined for real-time agent assistance.
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
- Government & public sector
- Project duration
- 6–8 weeks
- Tech stack
- Multi-agent · Speech / ASR-TTS
- Deployment
- Private deployment
2. Business Context & Pain Points
The customer is a Mid-market / Regional player in Government, 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 "Decoupled Knowledge & Low-Cost Inference", Global AI DAO integrated the following capability stack into a single solution:
- Multi-agent —— Wired into the critical business path across ingestion, inference and human-in-the-loop collaboration.
- Speech / ASR-TTS —— 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 |
|---|---|---|---|
| answer rate | 100% | 121% | +21pp |
| average call duration | 100% | 67% | -33% |
Source metric: +21pp answer rate, -33% average call duration.
5. Specs & Fit
| Architecture base | DeepSeek decoupled architecture |
| Backbone size | 7B / 32B / 70B tiers |
| Inference cost | -40% to -60% vs dense baselines |
| Knowledge injection | Continued training / LoRA / expert adapters |