Pharma trial-data governance
Trial data, literature and imaging governed together to support AI drug discovery.
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 Government & public sector
- Project duration
- 6–8 weeks
- Tech stack
- Multimodal backbone
- Deployment
- Private deployment
2. Business Context & Pain Points
The customer is a Enterprise / Group player in Government, with the core pain concentrated in "Data & R&D". 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:
- 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 |
|---|---|---|---|
| data-prep time | 100% | 25% | -75% |
Source metric: -75% data-prep time, 3× candidate-compound throughput.
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 |