Managed vector database by Pinecone for real-time semantic search and similarity matching at scale.
Use Cases16
Companies14
Industries7
AI Use Cases with Pinecone
1
How Terminal X Uses Pinecone to Cut Retrieval Latency by 35%
Terminal X · Research & Development
0.68 to 0.91
F1 retrieval accuracy improvement
0.68 to 0.91F1 retrieval accuracy improvement
2
How Aquant Uses Pinecone to Cut Service Resolution Time 49%
Aquant · Operations
98%+
Retrieval accuracy
98%+Retrieval accuracy
3
How InpharmD Uses Pinecone & RAG to Boost Clinical Query Accuracy by 70%
InpharmD · Operations
80%
Data Storage Cost Savings
80%Data Storage Cost Savings
4
How Chipper Cash Uses Pinecone Vector Search to Stop Fraud in Real-Time
Chipper Cash · Software Engineering
95%+
Selfie verification accuracy
95%+Selfie verification accuracy
5
How ZoomInfo Uses Pinecone to Deliver Real-Time Contact Recommendations at Scale
ZoomInfo · Sales
>50%
Increase in user engagement
>50%Increase in user engagement
6
How CustomGPT.ai Uses Pinecone to Serve 10,000+ Customers with Sub-20ms RAG
CustomGPT.ai · Software Engineering
>400M
Vectors stored
>400MVectors stored
7
How Allspice Uses Pinecone to Achieve 97% Ingredient Matching Accuracy
Allspice · Product Development
20% → 97%
Ingredient matching accuracy
20% → 97%Ingredient matching accuracy
8
How TaskUs Reduces Handle Time 20% with Pinecone-Powered TaskGPT
TaskUs · Customer Service
20%
Average handle time reduction
20%Average handle time reduction
9
How Allspice Improved Ingredient Matching from 20% to 97% with Pinecone
Allspice · Product Development
20% → 97%
Ingredient matching accuracy
20% → 97%Ingredient matching accuracy
10
How Melange Uses Pinecone to Power 600M-Vector Patent Search
Melange · Software Engineering
>600M
Vectors stored in production
>600MVectors stored in production
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Models Used With
Gemini 3.5 Flash
Google's fast reasoning model with a 1M-token context for text, image, video, audio, and document inputs.
Often Used With
AWS
Amazon's cloud computing platform providing on-demand infrastructure, storage, and managed services at global scale.
Amazon Bedrock
Fully managed service for accessing foundation models from leading AI companies via AWS.
Canopy
Open-source RAG framework by Pinecone Systems for building production-grade retrieval pipelines.
Sherlock
AI clinical assistant by InpharmD that answers drug information queries using evidence-based sources.
Typesense
Open-source search engine with typo tolerance, faceting, and vector search capabilities for building fast, relevant search experiences.
Google Cloud Run
Serverless container platform by Google Cloud for deploying containerized apps without infrastructure management.
OpenAI text-embedding-3-large
High-performance text embedding model optimized for semantic search and retrieval tasks with large-scale document collections.
Google Cloud Firestore
Serverless NoSQL document database for storing and syncing app data in real time with offline support and automatic scaling.
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