Building Trusted AI Analytics for Enterprise JavaScript Applications

Artificial intelligence is transforming how organizations explore data, generate reports, and uncover business insights. While AI-powered analytics can dramatically improve accessibility, enterprise adoption requires more than intelligent models. Organizations must also ensure consistency, governance, transparency, and compliance across every interaction with business data.

At JS Days 2026, Stephen Ball, Presales Director, and Montana Mendy, Solution Architect at Yellowfin, will explore how JavaScript developers can build AI-powered analytics experiences that deliver both innovation and enterprise trust.

Session Overview

Title: Making AI Analytics Safe and Simple for Enterprise JavaScript Developers
Speakers: Stephen Ball and Montana Mendy
Company: Yellowfin
Format: Pre-Recorded Presentation

This session examines how enterprise analytics platforms combine artificial intelligence with governed data models to produce reliable, explainable insights. Rather than focusing solely on AI capabilities, the presentation highlights the architectural principles that enable organizations to deploy AI analytics responsibly at scale.

The Enterprise Challenge

AI has made it easier than ever for users to ask questions in natural language and receive instant insights. However, without proper governance, organizations may encounter inconsistent responses, conflicting business definitions, and increased compliance risks.

For enterprise software developers, the challenge is not simply embedding AI into an application – it is ensuring that every insight is based on trusted data and that every interaction remains transparent and auditable.

Building AI-powered analytics therefore requires balancing intelligent automation with strong governance and operational control.

Establishing a Trusted Data Foundation

A central theme of the session is the importance of a governed semantic layer.

By providing consistent business definitions across reports, dashboards, and AI-generated responses, a semantic layer ensures that every user is working from the same interpretation of organizational data.

This approach reduces ambiguity, improves consistency across teams, and helps organizations maintain confidence in AI-generated insights.

Combining AI with Enterprise Analytics

The presentation demonstrates how AI can complement – not replace – traditional analytics capabilities.

Attendees will explore how modern analytics platforms bring together:

• AI-assisted data exploration
• Interactive dashboards
• Enterprise reporting
• Data storytelling
• Governed business metrics
• Audit and usage tracking

When these capabilities operate on a shared semantic foundation, organizations can provide intelligent analytics while maintaining consistency across the business.

Governance, Transparency, and Compliance

Enterprise AI initiatives increasingly require visibility into how information is generated and accessed.

This session explores how governance features such as auditing, access controls, and standardized business definitions help organizations meet internal policies and regulatory requirements while improving confidence in AI-powered decision-making.

For developers building enterprise applications, these architectural considerations are becoming just as important as the AI models themselves.

What You’ll Learn

During this session, attendees will gain insights into:

• Building trusted AI-powered analytics experiences
• Understanding the role of semantic layers in enterprise reporting
• Maintaining consistent business definitions across applications
• Combining AI with dashboards, reporting, and data storytelling
• Improving governance through auditing and transparency
• Designing analytics solutions that support enterprise compliance
• Integrating AI analytics into JavaScript applications responsibly

Who Should Attend

This session is ideal for:

• JavaScript developers
• Enterprise application developers
• Analytics platform developers
• Software architects
• Data engineers
• Technical leaders
• Teams building AI-enabled business applications

Why Attend

As organizations expand their use of AI, the quality of analytics increasingly depends on the governance surrounding the data – not just the intelligence of the models themselves.

This session provides a practical look at how enterprise analytics platforms combine AI with trusted business data, enabling developers to build applications that deliver accurate insights while supporting governance, compliance, and transparency.

Whether you’re developing dashboards, reporting systems, business intelligence applications, or AI-powered enterprise software, you’ll gain valuable insight into the architectural patterns that help transform AI from a productivity tool into a trusted component of enterprise decision-making.

Join Stephen Ball and Montana Mendy at JS Days 2026 to discover how enterprise JavaScript applications can deliver AI-powered analytics that are both intelligent and trustworthy.