AI-powered expert network matching professionals with research clients
proSapient operates an expert-networking platform connecting consultants and private equity firms with domain specialists for research calls and surveys. The tech stack—Elixir + Phoenix backend, Python + LangSmith + PromptLayer for AI, Kafka + Elasticsearch for data flow, and Kubernetes for orchestration—reveals a product heavily weighted toward matching algorithms and AI-driven content extraction. Active projects around recommendation engines and LLM-based data extraction, paired with pain points on expert recommendation and workflow automation, signal the core problem: surfacing the right expert for high-volume, niche client briefs at scale.
Notable leadership hires: Project Lead
proSapient is a UK-founded expert network and primary research platform launched in 2017. The company facilitates connections between professionals and institutional clients—consultancies and private equity firms—through structured expert calls, online surveys, and longer-term engagements. With 300+ employees across London, Lisbon, Raleigh, and Toronto, proSapient handles high-volume client research requests and maintains ISO 27001 accreditation. The engineering org is actively scaling Kubernetes infrastructure, building recommendation and AI extraction capabilities, and improving CI/CD and observability systems to handle increased throughput and reliability demands.
Backend: Elixir + Phoenix. Data/ML: Python, FastAPI, Django, LangSmith, PromptLayer, pandas, spaCy. Infrastructure: Kubernetes, Terraform, AWS. Message queue: Kafka, RabbitMQ. Search: Elasticsearch. Monitoring: Datadog.
Backend scaling and Kubernetes infrastructure, AI/LLM-based data extraction, recommendation engines, CI/CD pipeline improvements, and observability enhancements to handle high-volume client research requests.
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