AI tools that enable semantic search, vector similarity matching, and retrieval-augmented generation across large document collections.
88
Use Cases
27
Tools
18
Companies
Search & Vector Database Tools
AI-powered search feature by ServiceNow for surfacing relevant knowledge articles and answers instantly.
Search and discovery platform by Algolia offering fast, relevance-tuned search APIs for websites and apps.
Managed search and analytics engine for log analytics, application monitoring, and RAG knowledge bases.
Open-source RAG framework by Pinecone Systems for building production-grade retrieval pipelines.
Natural language search tool by DISCO for querying legal documents using plain-English questions.
Embedding model that converts text and images into vector representations for semantic search and retrieval.
Reranking model by Cohere that improves search relevance by re-scoring retrieved document results.
Convolutional neural network architecture for generating image embeddings used in visual similarity search.
Databricks AI Search enables semantic and hybrid search over enterprise data, allowing teams to compare and link documents and structured records using embedding-based retrieval.
Managed vector search service integrated with Databricks Unity Catalog for storing and querying high-dimensional embeddings at scale.
Managed cloud hosting for the Elastic Stack, enabling search, observability, and security workloads without infrastructure management.
Sparse retrieval model trained on Elasticsearch that generates context-aware token weights for more accurate semantic search without vector embeddings.
Search and analytics engine by Elastic offering full-text, vector, and hybrid search capabilities.
In-house embedding and facial similarity service by Chipper Cash for biometric fraud detection.
Open-source vector search library by Meta for efficient nearest-neighbor searches in embedding space.
Showing 15 of 27 tools
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Use Cases (88)
Allspice is a food technology startup building a kitchen operating system that serves both home cooks and recipe publishers at scale. The company deployed Pinecone’s vector database as a semantic search layer to solve the fundamental problem of matching messy, real-world ingredient language to a structured internal database. Ingredient matching accuracy jumped from roughly 20% to 97%, enabling Allspice to launch its recipe importing feature and unlock new revenue streams for publishers.
HSE is one of Europe’s leading live commerce retailers, reaching over 46 million households across Germany, Austria, and Switzerland through three TV channels, an online shop, and a social commerce app. The company replaced its previous search vendor with Elasticsearch on Elastic Cloud, deploying AI and machine learning features to return more relevant results across a diverse customer base that includes both TV-driven shoppers and digitally native browsers. Within the first six months, HSE saw a 4% increase in search page click-through rates and an 8% improvement in customer satisfaction.
1up is a sales knowledge automation platform that helps revenue teams instantly answer RFPs, compliance questionnaires, and product queries from their own content. By replacing a home-grown embedding system with Pinecone’s vector database, 1up built a RAG-powered knowledge engine that generates accurate responses 10 times faster than before. The platform now enables sales reps to retrieve precise answers in seconds without relying on colleagues or manually searching documentation.
Hexaware is an India-based IT services firm with 30,000 employees and $1.3 billion in revenue, delivering managed services to enterprise clients. The company deployed Elastic AI Assistant and Elastic Observability to transform how junior engineers onboard and how teams monitor client environments. New hires now reach client-ready status in three months instead of a year, and operational efficiency on managed projects has improved by 50%.
The Public Ministry of Rio Grande do Sul (MPRS) in Brazil, serving over 8 million citizens across 497 municipalities, partnered with WideLabs to deploy AI agents built on NVIDIA NIM and NeMo that process the state’s 60,000 annual police inquiries and 39,000 public service requests. Legal procedures that previously took months or years are now resolved in less than a day.
Kantar Worldpanel is a leading international consumer data and market research company serving FMCG manufacturers and retailers worldwide. The company deployed Databricks’ Data Intelligence Platform to fine-tune large language models for linking paper receipt descriptions to product barcodes, automating a historically manual and resource-intensive task. Using GPT-4 for training data generation and a smaller fine-tuned model for production, Kantar automatically generated 120,000 labeled data pairs at 94% accuracy in a matter of hours.
Adidas is one of the world's most recognized sports brands, operating across 150+ countries with a product line that requires constant feedback from a global customer base. The company deployed a RAG-based GenAI solution on Databricks to analyze more than 2 million product reviews, enabling 50+ decision-makers worldwide to extract actionable insights in seconds. The result was a 30-40% improvement in analyst efficiency, a 60% reduction in response latency, and 91.67% cost savings by optimizing LLM usage.
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.
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.
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.
Notion, the connected workspace platform used by millions worldwide, integrated Cohere Rerank into its search pipeline to power Notion AI’s search accuracy across multilingual enterprise workspaces. Every search and Notion AI interaction now routes through Cohere Rerank, delivering dramatically improved relevance while cutting the cost and complexity of embedding-based retrieval for smaller workspaces.
Pure Storage, a Santa Clara-based enterprise data storage company, deployed Glean to unify knowledge access across Jira, GitHub, and internal wikis for teams spanning engineering, legal, and customer support. The AI-powered search platform cuts information-retrieval time by more than 30 minutes per search and enables employees to build custom GenAI applications in as little as 5 minutes, while boosting overall employee satisfaction scores by 39 points.
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.
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.
Vanguard partnered with Pinecone to build Agent Assist, an internal RAG-powered AI chat tool that helps customer support representatives find answers faster and more accurately. By replacing keyword-based search with hybrid vector retrieval, Vanguard achieved 12% more accurate search results and meaningfully reduced call times — even during high-demand periods like tax season.
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.
The United Network for Organ Sharing (UNOS) leverages the ServiceNow AI Platform to coordinate thousands of organ transplants across the U.S. every year. By centralizing case management, enabling self-service portals, and deploying AI-powered IT operations, UNOS has quadrupled its case management capacity while managing nearly 300,000 support cases since 2018. The platform helps UNOS fulfill its 24/7 mission of saving lives with greater speed, accuracy, and efficiency.
Thomson Reuters integrated Claude via Amazon Bedrock into its AI platform, CoCounsel, to make the expertise of 3,000+ subject matter experts and 150 years of authoritative content accessible to legal and tax professionals. The solution combines Retrieval-Augmented Generation (RAG) architecture with multi-model deployment to deliver comprehensive, accurate professional analysis. Early adopters report dramatic efficiency gains, with some estimating task time cut in half or more.
Blue Origin deployed 2,700+ AI agents with 70% company-wide adoption, achieving a 90% reduction in hardware development time using Amazon Bedrock.
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