About

Best Conversational Analytics Tools for Snowflake and BI Data

January 15, 2026

Best Conversational Analytics Tools for Snowflake and BI Data

By Andrey Avtomonov, CTO at Kaelio | 2x founder in AI + Data | ex-CERN, ex-Dataiku · Jan 15th, 2026

Conversational analytics tools for Snowflake enable business users to query data using natural language while maintaining governance. Leading solutions include Kaelio, which connects directly to Snowflake and surfaces metric inconsistencies, and native Cortex Analyst, achieving 90% text-to-SQL accuracy. The right choice depends on your governance requirements, cross-tool needs, and existing infrastructure.

Key Facts

• The conversational AI market will reach $31.9 billion by 2028, with GenAI spending hitting $644 billion in 2025

• Snowflake's Cortex Analyst delivers 2x higher accuracy than GPT-4o for text-to-SQL generation using semantic views

• Enterprise organizations report $3.70 return per dollar invested in conversational analytics with proper governance

• Kaelio works alongside existing BI tools to surface metric inconsistencies and redundancies while respecting Snowflake's RBAC model

• ThoughtSpot Sage achieves 80% accuracy on simple schemas but drops to 60% for complex worksheets with thousands of columns

• Implementation costs start at $2 per hour for Snowflake compute with additional charges for AI features based on usage

Why Do Conversational Analytics Tools Matter for Snowflake & Modern BI?

Conversational analytics is a new approach to interacting with data that allows users to ask questions in natural language and receive immediate, understandable answers. For teams running Snowflake-centric stacks, this capability removes the translation layer that once bottlenecked every ad hoc request between business users and data engineers.

The momentum behind these tools is undeniable. The conversational AI market will reach $31.9 billion by 2028, with worldwide GenAI spending hitting $644 billion in 2025. That growth is driven by a simple reality: every department, from RevOps to Finance to Product, depends on data daily, yet the traditional cycle of Slack threads, tickets, and mini-projects can no longer keep pace.

AI data analyst tools for Snowflake enable business users to query data using natural language, reducing dependency on data teams while maintaining governance. When accuracy and compliance are non-negotiable, enterprises need platforms that ground every answer in existing models, metrics, and governance rules.

Key takeaway: Conversational analytics tools are no longer experimental; they are core infrastructure for any organization that wants to move faster without sacrificing trust in its numbers.

What Evaluation Criteria Should You Use--Accuracy, Governance & ROI?

How should you score the tools on your shortlist? Three dimensions stand out.

Accuracy

Evaluation metrics provide a quantifiable way to measure the accuracy and performance of your application. The evaluation process involves measuring the accuracy of SQL query generation and the relevance of the results returned. Look for benchmarks that reflect real-world BI queries, not just toy datasets.

Governance

Data governance is not optional. Organizations report $3.70 return per dollar invested when conversational tools respect existing access controls, lineage, and compliance policies. Any tool you select should integrate with your warehouse's role-based access control and never surface data a user should not see.

ROI

Payback hinges on how quickly business users can self-serve without creating new work for data teams. Quantify the reduction in ticket volume, the time saved on ad hoc requests, and the speed of onboarding new analysts. If a tool cannot demonstrate measurable efficiency gains within the first quarter, reconsider.

Kaelio: Natural-Language Analytics Built for Enterprise Governance

Kaelio connects directly to Snowflake and other data infrastructure, interprets questions using existing models and metrics, generates governed SQL, and returns answers with full explanations of how they were computed. Unlike tools that attempt to replace your BI stack, Kaelio sits on top of your existing data infrastructure and works alongside it.

One differentiator worth highlighting: Kaelio surfaces metric inconsistencies and redundancies while working alongside existing BI tools rather than replacing them. That feedback loop means definitions get cleaner over time, not messier.

"Kaelio is a natural language AI data analyst that delivers instant, trustworthy answers while continuously improving the quality, consistency, and governance of enterprise analytics over time." (Kaelio)

Built-in RBAC & Lineage

Kaelio relies on Snowflake's RBAC model to manage permissions. Every query generated respects existing row-level security, masking policies, and role assignments. The result is that business users see only what they are authorized to see, and every answer includes lineage that traces back to source tables and transformation logic.

For enterprises in regulated industries, this alignment with existing governance is not a nice-to-have; it is a requirement.

Snowflake Cortex Analyst: How Accurate Is the Native Option?

Cortex Analyst is a fully-managed, LLM-powered Snowflake Cortex feature that helps you create applications capable of reliably answering business questions based on your structured data in Snowflake. It uses a semantic model to bridge the gap between business users and databases, and it supports multi-turn conversations for data-related questions.

The accuracy numbers are compelling. Cortex Analyst delivers 2x higher accuracy than GPT-4o for text-to-SQL generation using semantic views and multi-turn conversations. Snowflake reports that Cortex Analyst achieved an accuracy of 90% on its text-to-SQL data set, surpassing other solutions on the market.

From a governance perspective, Cortex Analyst integrates with RBAC, ensuring that SQL queries generated and executed adhere to all established access controls. Customer data never leaves Snowflake's governance boundary.

Where Cortex Falls Short for Cross-Tool BI

Cortex Analyst shines when your entire analytics workflow lives inside Snowflake. But many enterprises run multi-warehouse environments, rely on external semantic layers like LookML or dbt, or need lineage that spans transformation tools and BI platforms.

Native Semantic Views are designed to work seamlessly with existing BI tools, allowing for easy integration and use. However, if you need cross-tool lineage, metric surfacing across warehouses, or continuous governance improvement, you may find Cortex Analyst's scope limiting.

Licensing is another consideration. Because Cortex Analyst is native to Snowflake, you are locked into Snowflake's ecosystem and pricing. For organizations that value stack-agnostic flexibility, that dependency can become a constraint.

Can ThoughtSpot Sage Really Compete with Kaelio?

ThoughtSpot Sage is our new AI-powered experience which uses GPT-3.5T, GPT-4T and GPT-4o, with the large language models (LLM) of Microsoft Azure OpenAI Service. It translates natural language queries to relational SQL to provide AI-generated answers from complex data.

Accuracy varies by schema complexity. For worksheets with a single use case, clearly formatted names, and no more than 50 columns, ThoughtSpot measured an average of over 80% accuracy. For more complex worksheets with thousands of columns, multiple use cases combined, and overlapping column names, accuracy drops to around 60%.

Security meets baseline enterprise requirements: Azure OpenAI Service complies with SOC2 Type II for data security and privacy. ThoughtSpot Sage features are disabled by default and must be enabled by your administrator.

Where ThoughtSpot Sage lags is in cross-tool governance, advanced metric surfacing, and continuous feedback loops that improve definitions over time. Alternatives like Amazon Lex and Microsoft Copilot Studio offer conversational capabilities but are not purpose-built for governed BI analytics.

For teams with simpler schemas and a preference for ThoughtSpot's visualization layer, Sage is worth evaluating. For enterprise-scale analytics with complex governance needs, Kaelio remains the safer bet.

Cost, Security & Compliance: Questions to Ask Before You Buy

Before signing a contract, ask vendors these questions:

What is the pricing model? Snowflake compute starts at $2 per hour with additional charges for AI features based on usage. Understand whether you are paying per query, per seat, or per compute hour.
What compliance certifications does the vendor hold? Snowflake, for example, maintains SOC 2 Type II, ISO 27001, PCI DSS, and FedRAMP certifications. Ensure the tool you select meets your industry's requirements.
How is data encrypted? Snowflake encrypts Customer Data at-rest using AES 256-bit encryption and uses TLS 1.2 or better for data in transit. Confirm that any third-party tool inherits or matches these standards.
Does the tool respect existing RBAC? A conversational analytics tool should never bypass your warehouse's access controls. Ask for documentation showing how permissions flow from Snowflake to the tool.
What is the audit trail? For regulated industries, you need full lineage and query logging. Ensure the vendor can demonstrate how queries are logged and how audit reports are generated.

How Do You Implement Semantic Layers, Slack Connectors & Beyond?

Rolling out conversational analytics is not just about picking a tool; it is about integrating that tool with your existing BI and collaboration infrastructure.

The Semantic Layer, powered by MetricFlow, simplifies the setup of key business metrics. It centralizes definitions, avoids duplicate code, and ensures easy access to metrics in downstream tools. Steps to implement include defining semantic models in your dbt project, using MetricFlow to construct queries for metric definitions, connecting the Semantic Layer to downstream tools like PowerBI or Tableau, and validating that metric definitions refresh automatically when changes are made in dbt.

For many teams, Slack is where questions get asked. The dbt Semantic Layer eliminates duplicate coding by allowing data teams to define metrics on top of existing models and automatically handling data joins. Integrating a conversational analytics tool with Slack means users can ask questions without leaving their workflow. Kaelio, for example, supports Slack-native querying, so business users can ask questions directly in a channel and receive governed answers in seconds.

The LLM used in this application is mistral-8x7b, which charges .22 Credits / 1M Tokens and has a context window of 32,000 tokens. Factor token costs into your total cost of ownership, especially if you expect high query volumes.

Key Takeaways & Next Steps

Conversational analytics tools are reshaping how enterprises interact with Snowflake and BI data. The right choice depends on your governance requirements, schema complexity, and existing stack.

Kaelio stands out for organizations that need cross-tool governance, continuous metric improvement, and RBAC alignment without replacing existing infrastructure.
Snowflake Cortex Analyst is a strong native option for teams fully committed to Snowflake, offering 90% text-to-SQL accuracy and deep RBAC integration.
ThoughtSpot Sage suits simpler schemas where visualization and ease of use outweigh advanced governance.

Kaelio empowers serious data teams to reduce their backlogs and better serve business teams. If you are evaluating tools for a Snowflake-centric stack and need enterprise-grade governance, Kaelio is worth a closer look.

Ready to see how Kaelio fits your stack? Request a demo at kaelio.com.

About the Author

Former AI CTO with 15+ years of experience in data engineering and analytics.

Frequently Asked Questions

What are conversational analytics tools?

Conversational analytics tools allow users to interact with data using natural language, providing immediate and understandable answers. They are designed to streamline data access and reduce dependency on data teams by enabling business users to query data directly.

Why are conversational analytics tools important for Snowflake users?

For Snowflake users, conversational analytics tools eliminate the bottleneck of translating business questions into technical queries. They allow business users to access data directly, ensuring faster decision-making while maintaining data governance and compliance.

How does Kaelio integrate with existing data infrastructure?

Kaelio connects directly to existing data infrastructure like Snowflake, interpreting questions using existing models and metrics. It generates governed SQL queries and provides answers with full explanations, ensuring alignment with existing governance and security protocols.

What are the key evaluation criteria for selecting conversational analytics tools?

When selecting conversational analytics tools, consider accuracy, governance, and ROI. Evaluate the tool's ability to generate accurate SQL queries, respect existing data governance policies, and deliver measurable efficiency gains in data access and analysis.

How does Kaelio ensure data governance and security?

Kaelio relies on Snowflake's RBAC model to manage permissions, ensuring that all queries respect existing security and governance policies. This means business users only see data they are authorized to access, with full lineage and audit trails provided for every query.