Kantata Launches Expertise Insights for Generative Business Intelligence in Services Firms

Kantata Inc. announced the launch of Expertise Insights today, integrating generative business intelligence into its existing Expertise Engine platform. This new feature enables users within professional services firms to query their operational data using natural language rather than complex technical commands or predefined report structures.

According to SiliconANGLE, the software responds to plain-English inquiries—such as identifying where margin pressure is occurring—by generating interactive charts, specific calculations, or executive summaries. This capability aims to reduce the time required for services firms to extract actionable answers from their internal data repositories, bypassing traditional bottlenecks in the reporting process.

Speed and Semantic Translation

Kantata states that traditional requests for business intelligence often require intervention from analysts or engagement teams, resulting in wait times that can extend to a week. Sarah Edwards, Kantata’s chief product and strategy officer, noted that the value of an insight depends heavily on how quickly organizations can act on it, arguing that standard reports frequently arrive after the critical moment has passed.

To address terminology barriers, Kantata built a semantic layer on top of Amazon Web Services Inc.’s Amazon QuickSight. This layer translates technical database field names into the specific vocabulary used by staff at individual firms. The system accounts for nuanced distinctions, such as the difference between “chargeable utilization” and “billable utilization,” ensuring that AI-generated responses align with internal operational definitions.

Dashboards and Data Relationships

The product ships with four pre-configured dashboards targeting finance, delivery, time, and resourcing teams. The finance dashboard displays trends in margin, revenue per head, and cost leakage, while the delivery dashboard breaks down project health by schedule, scope, budget, and client status. These tools are designed to provide immediate visibility into key performance indicators without requiring custom configuration.

For needs not covered by standard views, users can utilize the “Ask Insights” feature to request new analysis on demand. Kantata claims that complete board decks can be assembled in minutes using this method. To prevent dashboard sprawl, saved analyses and filtered views are stored in Bookmarks and Pinboards, allowing users to retain specific queries without duplicating master dashboards. The software also links capacity, margin, delivery risk, and financial performance, relationships that might otherwise require multiple separate reports.

What should you do?

Security and technology professionals should evaluate how generative AI tools handle sensitive business data within their organizations. Review the data governance policies of vendors offering natural-language querying features to ensure that proprietary metrics like margin and utilization rates are not exposed to unauthorized AI models. Monitor access controls for any new analytics platforms that allow broad data querying, ensuring that only authorized personnel can generate executive summaries or financial reports.

Background: Generative AI

Generative AI examples include text completion, image synthesis and code generation. These systems predict the next likely token based on vast training datasets. Understanding the underlying mechanics helps you identify risks like data leakage and hallucination in your infrastructure.

Read the full guide: Generative AI Examples: Mechanisms, Risks and Control

What to do and how to stay safe: Kantata

• Audit the data access permissions for any new generative AI or business intelligence tools integrated into your professional services automation stack.
• Verify that the vendor’s semantic layer and AI processing occur within a secure, compliant environment that isolates your firm’s specific data from other tenants.
• Test the accuracy of AI-generated insights against known historical data to ensure that the translation of technical fields into business terms is reliable.
• Establish clear guidelines for employees on what types of sensitive financial or operational data can be queried through natural-language interfaces.

Step-by-step guide: Mobile Device Security: How to Protect Data Beyond Passwords

General security guidance from the Threat Times newsroom. It is not confirmed advice from the organisations named in this story.

Frequently asked questions

What is Kantata’s Expertise Insights?

It is a generative business intelligence feature added to Kantata’s Expertise Engine platform that allows users to ask business questions in plain English.

How does the software handle specific industry terminology?

It uses a semantic layer built on Amazon QuickSight to translate database field names into the specific vocabulary used by staff at each firm.

What dashboards are included with the launch?

The product includes four ready-made dashboards for finance, delivery, time, and resourcing, covering metrics like margin, revenue per head, and project health.