SCIENTIFIC EVIDENCE SYNTHESIS
Multimodal RAG and evidence synthesis at Synthesa AI
My venture work: an LLM platform for pharmaceutical and biotech evidence synthesis, with multimodal retrieval and parallel agent workflows.
The challenge
Coordinate retrieval and reasoning across scientific documents, tables, and images with predictable, traceable execution.
My contribution
Designed the cloud-native LLM platform using Django, Docker, GCP, distributed queues, KV caching, and vLLM. Built parallel language and vision-language agent workflows with vector search, reranking, and policy filters.
The outcome
Contributed the ML architecture behind a platform whose published validation screened 270,626 abstracts, with 100% sensitivity, 99.4% specificity, and 91.7% less manual-review workload.
Areas of work
- Founding ML architect
- Multimodal RAG
- vLLM