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Fri, April 30Data & Intelligent SystemsAI-Native Software
An AI system can retrieve relevant data and still produce an indefensible answer. The source may be stale, outside the user’s entitlement, derived through an unknown transformation, or inconsistent with the system of record. Retrieval quality alone cannot establish whether evidence is safe to use.
In this session, you will explore a vendor-neutral method for deciding whether enterprise data is ready to support AI reasoning and action. Starting with a failed decision caused by stale or mis-scoped information, you will trace the controls required across ingestion, integration, lineage, freshness, data contracts, master data, purpose-based access, and retrieval. You will examine how ownership and transformation history travel with data, how freshness is evaluated against the decision being made, and how conflicting sources can be identified before they enter model context. Implementation examples may draw on warehouse, lakehouse, data-cloud, and graph-retrieval technologies, with the evaluation mechanism taking priority.
What You Will Learn
How to evaluate data authority, lineage, freshness, and permitted purpose before data enters AI context
How to use data contracts and observability to detect schema, transformation, and freshness failures
How to determine when an AI workflow has sufficient evidence to proceed, restrict its answer, or stop
Who Should Attend
Data Architects, Data and AI Engineers, Platform Architects, Governance Leads, and Developers building RAG or agent systems. Familiarity with enterprise data pipelines, data governance, and retrieval-augmented generation is recommended.
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Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
