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Entity Resolution
4 posts about Entity Resolution. Every summary links to the original.
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How AI Agents Get Trusted Customer Context with Data 360 Data Graphs
Salesforce’s AI Engineering team uses Data 360 data graphs to close the context gap that prevents agents from reliably personalizing customer interactions. The graphs join, aggregate, and apply business logic across fragmented identities, accounts, products, contracts, orders, cases, services, and entitlements, while partitioned data spaces provide a filtered customer-success view. The team designs smaller graphs or multi-graphs around agent access patterns, adds indices, supports semantic or keyword search, and curates context so agents can traverse extensible many-to-many relationships without receiving unnecessary data. Reusable deployment automation and validation practices helped deliver five major releases in six months, with integrations spanning Postman, Apex, Agentforce, and low-code or no-code workflows. Live monitoring later showed P50 performance below 200 milliseconds, compared with an earlier benchmark of about 400 milliseconds.
Engineering Real-Time Mobile Personalization Across iOS, Android, React Native, and Flutter
Building real-time mobile personalization across iOS, Android, React Native, and Flutter required one architecture to handle different rendering models, lifecycles, identity flows, consent requirements, and release cycles without disrupting native app experiences. The team standardized schemas, event semantics, identity behavior, fallback handling, and SDK APIs, using bridge layers so React Native and Flutter could access native iOS and Android capabilities. Developers instrument apps once with constrained content zones and approved native components, while marketers configure templates, targeting, and content through Salesforce UI; metadata is published via a global CDN and rendered dynamically by the SDK. Data 360 performs server-side identity resolution and decisioning, limiting unnecessary raw profile storage on devices. An early customer implemented the system in two months and generated more than 150 million decisions within three weeks, while QR-code previews enabled testing against live profiles without app recompilation.
Databricks for Good and Virtue Foundation: Partnering to Connect Medical Volunteers to Critical Health Services in 72 Countries
Virtue Foundation’s VF Match platform connects medical professionals with volunteer opportunities across 72 low and low-middle income countries, but scaling its initial LLM proof of concept into production required a robust data pipeline. The Databricks-based Foundational Data Refresh combines Overture Maps and Bright Data, processes more than 25 million web pages with targeted GPT extraction steps, and uses Spark, Photon, and Lakeflow Jobs to orchestrate checkpointed, modular workloads. Splink resolves duplicate facilities and nonprofits across messy sources; Photon reduced the slowest entity-resolution partition from 30 minutes to approximately two minutes, a 15x improvement. A prototype VF Agent adds natural-language access through LangGraph, Databricks Model Serving, AI Search, and Genie, while the resulting system provides an up-to-date global view of healthcare infrastructure and volunteer needs.
The Rosetta stone of CPS: Claroty’s AI-powered library
CPS asset identification is difficult because 88% of CPS assets do not transmit an exact product code and 76% use product codes that differ from the vendor's official records. Claroty's AI-Powered CPS Library addresses this entity-resolution problem with a hybrid architecture that combines classic matching, statistical inference, generative AI, NLP, reasoning agents, and human-in-the-loop review to reconcile protocol data, vendor records, manuals, and vulnerability information. Its Databricks-based lakehouse uses Delta Lake, Unity Catalog, Spark pipelines, Model Serving, MLflow evaluations, Lakebase, and Databricks Apps to maintain governed, auditable mappings across a catalog of more than 17 million assets. The post reports 25% improved vulnerability-attribution accuracy and says early tests gave 56% of analyzed devices new or updated recommendations for outdated firmware, while low-confidence mappings remain subject to expert review.
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