Pinecone

Chipper Cash, a fintech serving over five million customers across Africa, deployed a Pinecone-powered facial similarity search system to detect and block fraudulent duplicate sign-ups in real time. The solution slashed identity verification latency from up to 20 minutes down to under 2 seconds, and reduced fraudulent sign-ups by 10x across all markets.

1up, a sales knowledge automation platform, integrated Pinecone's vector database to power a RAG-based system that delivers real-time, highly accurate answers to complex sales queries. The solution replaced a slow, home-grown embedding system and achieved 10x faster response generation for RFPs and compliance questionnaires. Sales reps can now handle high volumes of queries with confidence, reducing reliance on colleagues and accelerating the go-to-market process.

InpharmD's AI assistant, Sherlock, leverages Pinecone's vector database to deliver fast, accurate drug information to healthcare professionals. By embedding 30 million medical documents into a RAG pipeline, InpharmD achieved 70% better query accuracy, 95x faster first response times, and 80% cost savings on data storage.

Assembled is a workforce management and customer support optimization platform serving enterprises like Stripe, Etsy, and DoorDash. To power Assembled Assist, the company built a hybrid RAG pipeline combining Pinecone vector search with Algolia keyword retrieval and LLMs from OpenAI and Anthropic. Support tasks that previously took 40 minutes now complete in 2 minutes—a 95% reduction in handling time.

Gong is a revenue intelligence platform that analyzes billions of customer interactions to help sales teams improve performance. To power Smart Trackers—its patented AI system for detecting and classifying concepts in sales conversations—Gong adopted Pinecone as its core vector database, storing billions of sentence-level embeddings across real conversations. Migrating to Pinecone Serverless delivered a 10x reduction in infrastructure costs while sustaining peak search performance across a massive corpus.

Delphi is an AI platform that enables coaches, creators, and experts to deploy interactive “Digital Minds”—always-on conversational agents trained on their unique content. Scaling from proof of concept to a commercial platform with thousands of customers required a vector database that could support millions of isolated namespaces, billions of vectors, and sub-second retrieval under variable load. Delphi selected Pinecone, achieving P95 query latency of 100ms and keeping retrieval under 30% of total response time—freeing the engineering team to build product rather than manage infrastructure.

TaskUs is a leading outsourced digital services company providing next-generation customer experience (CX) for innovative global brands. To move beyond flat-file embedding storage and scaling limitations, TaskUs built TaskGPT—a proprietary GenAI platform—with Pinecone as the core vector database for semantic search, RAG-based knowledge retrieval, and client-specific recommendations. The result: a 20% reduction in average handle time and a 5% increase in customer satisfaction across client deployments.