How to Build an Enterprise Data Foundation for Reliable Analytics and AI
Build & manage all your data assets for AI from one agentic platform
Keep full control and ownership of your data, context & governance
Make AI responses transparent, traceable and auditable
Get reliable answers in natural language, backed by your data warehouse, pipelines & business context
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Attend live for a chance to win a $100 gift card.
Why You Should Attend
Only 1 out of 10 companies successfully scale AI agents to production. The difference is often the data foundation behind them. (McKinsey, State of AI 2025)
The right foundation provides a secure way for AI to discover and access a company's data, its meaning, business context, and other relevant assets.
Centerprise AI helps build that foundation by bringing together structured systems and unstructured sources.
The platform models the data into warehouse and RAG data stores, add business context via skills and MCPs, and provide an access layer with a central catalog.
Join Jay Mishra, CPTO at Astera, as he introduces an enterprise data foundation for analytics and AI. The webinar includes a live demo of Centerprise AI and how its generates reliable analysis backed by warehouse, data pipelines, and business context.
Build and manage all your data assets for AI without directly exposing data to LLMs
Centerprise AI provides an access layer with a central catalog containing data models, data pipelines, structured metadata, RAG-ready data stores, APIs, MCPs & more. The catalog features security, governance and discovery capabilities.
Jay Mishra
CPTO at Astera | Advisor at Docspire | AI & Data Leader
A data architect and product leader with 20+ years building enterprise AI, GenAI, and automation platforms. Jay specializes in agentic AI for large-scale data integration and warehouse automation, helping enterprise teams turn disconnected source data into governed, query-ready warehouses faster. He has partnered with Fortune 500 organizations and been featured on Unite.AI and EM360.
In This Webinar, You'll Learn How To:
Build a dimensional warehouse from requirements file and source systems
Connect data from multiple sources into a single data model that supports reporting, dashboards & conversational analytics
Use skill files to provide analytics agent with data definition, business context, KPIs, sample queries & chain-of-thoughts.
Ask questions using business language and receive charts, reports & written summaries without writing SQL.
Trace every graph to its source of truth so teams can understand where numbers come from and how they were calculated.
Who Should Attend
This webinar is ideal for:
Data and BI Leaders
who need faster dashboards, reports, and insights built on a reliable data foundation.
CIOs and Technology Leaders
who are evaluating practical, governed AI use cases for enterprise analytics.
Data Engineering Teams
who want to automate repetitive schema analysis, modeling, pipeline generation, and warehouse build work.
Business Analysts and Operations Teams
who want faster answers without depending on SQL, manual reporting cycles, or fragmented tools.
Jay Mishra
CPTO at Astera | Advisor at Docspire | AI & Data Leader
A data architect and product leader with 20+ years building enterprise AI, GenAI, and automation platforms. Jay specializes in agentic AI for large-scale data integration and warehouse automation, helping enterprise teams turn disconnected source data into governed, query-ready warehouses faster. He has partnered with Fortune 500 organizations and been featured on Unite.AI and EM360.
Build a Data Foundation for Analytics and Agentic AI
See how Astera helps teams unify information, generate warehouse infrastructure with AI agents, and deliver reliable analytics through one connected platform.