Lang.ai

Visibility25

Vibe92

AI Visibility & Sentiment

Lang.ai

Lang.ai is an AI-powered platform that automates the processing of unstructured data, transforming customer interactions and feedback into actionable business insights. The platform integrates with data warehouses like Snowflake to provide comprehensive analytics that help organizations make data-driven decisions and improve their products.

Active Monitoring

lang.ai

Software

AI Visibility Score

25/100

Low

Sentiment Score

92/100

AI Perception

Summary

Lang.ai has successfully carved out a niche as a preferred tool for technical practitioners, yet it remains effectively invisible to the high-level CX executives who command enterprise budgets. While the brand shows impressive traction within technical and product-led personas, it is currently being drowned out by legacy giants like Zendesk and Snowflake in broad category-trust and strategic-insight queries.

Value Proposition

Automate the transformation of unstructured customer data into actionable insights that drive product decisions and revenue growth

Overview

Mission

Empowering organizations to unlock the value hidden in their unstructured customer data through intelligent automation

Products & Services

Unstructured data processing automationCustomer interaction analyticsProduct feedback analysisSnowflake integrationAI-powered insights platform

Agent Breakdown

AI Platforms

How often do different AI platforms reference Lang.ai?

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Conversation Analysis

Topics

What conversations is Lang.ai included in — or excluded from?

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Buyer Personas

Personas

Who does each AI platform recommend Lang.ai to, and when?

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Programmatic Testing

Sample Conversations

We programmatically analyze questions that real customers are asking to AI agents and chatbots, extract brand mentions and sentiment, analyze every response, and synthesize the data into an action plan to increase AI visibility.

ChatGPT

Claude

Gemini

AI Overviews

Scaling Product Feedback & Tagging(3 queries)

“how can i automate tagging thousands of support tickets every week”

1/4 platforms mentioned

ChatGPT

1.Zendesk

2.Freshdesk

3.Intercom

4.ServiceNow

5.Freddy AI

+11 more

Claude

1.AWS Comprehend

2.Google Natural Language API

3.Hugging Face

4.BERT

5.RoBERTa

+16 more

Gemini

1.Zendesk

2.Salesforce

3.Freshdesk

4.Lang.ai

5.MonkeyLearn

+18 more

AI Overviews

1.Zendesk AI

2.Freshdesk Freddy AI

3.Salesforce Service Cloud

4.Einstein

5.Canary Mail

+6 more

“help me find a way to turn product feedback into a roadmap without reading every single comment manually”

0/4 platforms mentioned

ChatGPT

1.Qualtrics XM

2.Stats iQ

3.Text iQ

4.Medallia Athena AI

5.Productboard

+20 more

Claude

1.Thematic

2.Viable

3.Kapiche

4.Medallia

5.Athena AI

+5 more

Gemini

1.Zendesk

2.Gong

3.Medallia

4.Slack

5.Enterpret

+6 more

AI Overviews

1.Productboard

2.Slack

3.Zendesk

4.InsightLab

5.Enterpret

+9 more

“what are the best tools for product feedback analysis at scale”

0/4 platforms mentioned

ChatGPT

1.Qualtrics XM

2.ProductXM

3.XM Discover

4.Salesforce

5.Snowflake

+11 more

Claude

1.Medallia

2.Qualtrics XM

3.Chattermill

4.Medallia Zingle

5.Sprinklr

+6 more

Gemini

1.Thematic

2.Chattermill

3.Dovetail

4.Productboard

5.Salesforce

+9 more

AI Overviews

1.Chattermill

2.Zendesk

3.Salesforce

4.Unwrap

5.Thematic

+9 more

Enterprise Data Warehouse Integration(2 queries)

“best tools for analyzing unstructured customer data that's already in snowflake”

0/4 platforms mentioned

ChatGPT

1.Snowflake

2.Snowflake Cortex AI

3.SQL

4.Snowpark

5.Python

+19 more

Claude

1.Snowflake

2.Snowflake Cortex

3.Snowpark

4.Sigma Computing

5.ThoughtSpot

+14 more

Gemini

1.Snowflake

2.Snowflake Cortex

3.Snowflake Document AI

4.Arctic-TILT

5.Snowpark

+18 more

AI Overviews

1.Snowflake

2.Cortex AI Functions

3.SNOWFLAKE.CORTEX.SENTIMENT

4.SNOWFLAKE.CORTEX.SUMMARIZE

5.SNOWFLAKE.CORTEX.CLASSIFY

+12 more

“how do enterprise teams process unstructured data automation within their existing data stack”

0/4 platforms mentioned

ChatGPT

1.Salesforce

2.HubSpot

3.Zendesk

4.ServiceNow

5.Qualtrics

+36 more

Claude

1.Snowflake

2.Redshift

3.BigQuery

4.Salesforce

5.Zendesk

+9 more

Gemini

1.Snowflake

2.Databricks

3.Salesforce

4.Gainsight

5.Fivetran

+18 more

AI Overviews

1.Dimension Labs

2.SharePoint

3.Amazon S3

4.Kafka

5.Informatica

+5 more

Category Trust & Vendor Selection(3 queries)

“who are the most trusted providers for ai powered insights platforms right now”

0/4 platforms mentioned

ChatGPT

1.Gartner

2.Forrester

3.IDC

4.Azure AI

5.Microsoft Fabric

+37 more

Claude

1.Salesforce Einstein

2.Microsoft Power BI

3.Copilot

4.Tableau

5.Einstein AI

+13 more

Gemini

1.Microsoft Power BI

2.Copilot

3.Microsoft 365 Copilot

4.Salesforce

5.Tableau

+22 more

AI Overviews

1.Forrester

2.Gartner

3.Microsoft Power BI

4.Copilot

5.Salesforce

+14 more

“what software options are there for unstructured data processing besides monkeylearn or thematic”

0/4 platforms mentioned

ChatGPT

1.MonkeyLearn

2.Thematic

3.Qualtrics

4.Medallia

5.Clarabridge

+18 more

Claude

1.MonkeyLearn

2.Thematic

3.Medallia

4.Qualtrics XM

5.Lexalytics

+17 more

Gemini

1.Medallia

2.Qualtrics

3.MonkeyLearn

4.Thematic

5.Stratifyd

+6 more

AI Overviews

1.MonkeyLearn

2.Thematic

3.SentiSum

4.Chattermill

5.Idiomatic

+12 more

“best reviewed customer interaction analytics tools for enterprise teams”

0/4 platforms mentioned

ChatGPT

1.NICE CXone

2.CXone Mpower

3.Enlighten AI

4.Genesys Cloud CX

5.Verint Open Platform

+14 more

Claude

1.Medallia

2.Qualtrics

3.Aglio AI

4.Thoma Bravo

5.Qualtrics XM

+8 more

Gemini

1.Snowflake

2.BigQuery

3.NICE Enlighten AI

4.Verint Da Vinci AI

5.CallMiner Eureka

+6 more

AI Overviews

1.Qualtrics XM

2.Medallia

3.Gartner

4.AmplifAI

5.Level AI

+10 more

Improving Customer Retention Insights(2 queries)

“i need to find the main reasons for customer churn from our chat logs, what software should i use”

0/4 platforms mentioned

ChatGPT

1.Qualtrics XM Discover

2.Clarabridge

3.Medallia

4.Chattermill

5.MonkeyLearn

+15 more

Claude

1.MonkeyLearn

2.Medallia

3.Qualtrics XM

4.Chattermill

5.LangChain

+10 more

Gemini

1.Chattermill

2.Thematic

3.Viable

4.GPT-4

5.MonkeyLearn

+18 more

AI Overviews

1.Relative Insight

2.SentiSum

3.Zendesk AI

4.Chattermill

5.Lyra AI

+3 more

“how to use ai to find trends in customer support interactions”

0/4 platforms mentioned

ChatGPT

1.Salesforce

2.Zendesk

3.ServiceNow

4.Intercom

5.LivePerson

+34 more

Claude

1.Medallia

2.Qualtrics XM

3.Intercom Fin AI

4.Zendesk AI

5.Salesforce Einstein

+2 more

Gemini

1.Medallia

2.Experience Cloud

3.Qualtrics

4.XM Discover

5.Clarabridge

+7 more

AI Overviews

1.Crescendo.ai

2.Level AI

3.Intercom

4.Topics Explorer

5.SentiSum

+2 more

Analysis

Key Insights

What AI visibility analysis reveals about this brand

Strength

Strong resonance with Technical Data Architects (60% mention rate) and Product Growth Leads (57% mention rate).

Strength

Superior ranking performance on Gemini (average position 6.3) compared to other LLMs.

Strength

High relevance in functional queries related to 'scaling product feedback' and 'ticket tagging' automation.

Gap

Total lack of visibility (0%) for the Strategic CX Executive persona, a critical buyer segment.

Gap

Zero footprint in AI Overviews across all tested queries, missing the top-of-funnel Google AI experience.

Gap

Consistent absence from 'Category Trust & Vendor Selection' queries, where competitors like Medallia and Zendesk dominate.

Opportunity

Pivot content strategy to address high-level business outcomes like 'customer retention' and 'churn reduction' to capture CX leadership.

Opportunity

Leverage existing technical authority to dominate 'Enterprise Data Warehouse Integration' queries where current mentions are inconsistent.

Opportunity

Convert 'mixed' sentiment on Claude and Gemini into 'positive' by addressing common industry comparisons and highlighting unique enterprise security features.

Technical Health

Site Health for AI Visibility

How well Lang.ai's website is optimized for AI agent discovery and comprehension.

86/100

16 passed 3 warnings 2 issues

Audited 2/27/2026

Crawlability100

Can AI bots find your pages?

Technical96

SSL, mobile, doctype basics

On-Page SEO71

Titles, descriptions, headings

Content Quality60

Word count, depth, freshness

Schema Markup85

Structured data for AI comprehension

Social & OG100

Open Graph, Twitter cards

AI Readability60

How well AI can parse your content

Critical Issues

Page has no H1 heading

Add a single H1 tag as the main page heading.

Content is too thin

Expand your content to at least 300-500 words with valuable information.

Warnings

1 render-blocking resource(s) detected

Consider deferring or async-loading non-critical scripts and stylesheets.

Title is too short (16 characters)

Expand the title to 50-60 characters with descriptive keywords.

Meta description is too short (21 characters)

Expand the description to 150-160 characters with a clear value proposition.

Few headings on page

Add more H2 and H3 headings to organize content into sections.

Want a full technical audit with AI-specific recommendations?

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Brand Identity

Brand Voice & Style

How AI perceives Lang.ai's communication style and personality

Lang.ai communicates with a sophisticated yet accessible tone that balances technical credibility with practical business value. The brand voice is confident and forward-thinking, positioning the company as an innovative leader in AI analytics while remaining grounded in real-world outcomes. Content emphasizes data-driven insights and measurable results, speaking to both technical and business stakeholders with clarity and precision.

Core Tone Traits

Data-Driven & Analytical

Emphasizes measurable outcomes, insights, and evidence-based decision making

Innovative & Forward-Thinking

Positions AI automation as the future of customer understanding

Professional & Credible

Speaks with authority on complex technical topics while maintaining accessibility

Results-Oriented

Focuses on practical business value and actionable outcomes

Competitive Landscape

Related Ecosystem

Related products and services that AI mentions in conversations alongside or instead of Lang.ai

Zendesk89 mentions

Snowflake82 mentions

Medallia65 mentions

Thematic51 mentions

Lang.ai48 mentions

Salesforce45 mentions

Intercom44 mentions

MonkeyLearn44 mentions

spaCy41 mentions

Chattermill40 mentions

Enterpret37 mentions

Source Intelligence

Citations

Sources that AI assistants cite. Getting featured here improves visibility.

How to Categorize Support Tickets Using LLMs - Fivetran

https://www.fivetran.com/blog/how-to-categorize-support-tickets-using-llms

Referenced in 1 query

Review

6 Ways to Use AI Ticket Tags to Optimise Customer Service - SentiSum

https://www.sentisum.com/library/ai-ticket-tags

Referenced in 1 query

Review

A practical guide to AI powered tagging for Zendesk tickets in 2026

https://www.eesel.ai/blog/ai-powered-tagging-zendesk-tickets

Referenced in 1 query

Review

Best Automated Ticket Tools for 2026 - Canary Mail Blog

https://canarymail.io/blog/best-automated-ticket-tools

Referenced in 1 query

Review

Best AI Ticketing Systems for 2026: Complete Guide - Pylon

https://www.usepylon.com/blog/best-ai-ticketing-systems-for-customer-support-2026

Referenced in 1 query

Review

Best support ticketing systems: 7 top solutions for 2026 - Pylon

https://www.usepylon.com/blog/best-support-ticket-systems

Referenced in 1 query

Review

12 best automated ticketing systems of 2026: A complete guide

https://www.zendesk.com/service/ticketing-system/automated-ticketing-system/

Referenced in 1 query

Review

The Ultimate Support Tagging Taxonomy Guide by Prodsight

https://www.prodsight.ai/resources/the-ultimate-support-tagging-taxonomy-guide/

Referenced in 1 query

Review

What are you using to automate ticket categorization ... - Reddit

https://www.reddit.com/r/AiForSmallBusiness/comments/1qj2jcs/what_are_you_using_to_automate_ticket/

Referenced in 1 query

Join Discussion

AI-tagged support tickets - Zapier

https://zapier.com/automation/use-case/using-ai-streamline-support-request-processing-and-management

Referenced in 1 query

Review

28 Best AI Helpdesk Software Reviewed in 2026 - The CX Lead

https://thecxlead.com/tools/best-ai-helpdesk-software/

Referenced in 1 query

Review

How to Build an AI Agents for Auto-Tagging Support Tickets ...

https://www.youtube.com/watch?v=uuIWePdvqRQ

Referenced in 1 query

Pitch Story

Content Engineering

Goals & Content Ideas

Ideas to help AI agents better understand the business and be more likely to use Lang.ai's resources to help users.

Establish CX Executive Thought Leadership Authority

Address the critical 0% visibility for CX Executive personas by creating strategic thought leadership content that positions Lang.ai as a trusted advisor for high-level business strategy. This involves publishing executive-focused insights on AI-driven customer experience transformation, ensuring content is indexed and discoverable by AI assistants when executives research CX solutions. Social media will amplify these insights through LinkedIn executive engagement and industry conversation participation.

The Hidden Cost of Ignoring Unstructured Customer Data: A CX Leader's Guide to Revenue Leakage

How Top CX Executives Are Using AI Analytics to Predict Customer Churn Before It Happens

5 Strategic Questions Every CX Leader Should Ask Before Investing in Data Analytics

From Feedback to Foresight: Building a Data-Driven CX Strategy That Boards Actually Understand

Why 73% of Customer Insights Never Reach the Boardroom—And How to Fix It

Dominate AI Overviews With Comparison Content

Combat 0% visibility in AI Overviews by creating structured, comparison-style content optimized for how modern AI search interfaces present information. This means developing comprehensive guides, feature comparisons, and decision frameworks for unstructured data processing that AI systems can easily parse and cite. Social content will drive traffic to these resources while reinforcing key differentiators in easily digestible formats.

Unstructured Data Processing Tools Compared: What Enterprise Teams Need to Know in 2026

The Complete Buyer's Guide to AI-Powered Customer Feedback Analytics

Manual vs. Automated: The True Cost of Processing Customer Data at Scale

How to Evaluate Unstructured Data Platforms: 10 Questions for Your Shortlist

Data Warehouse Integration Showdown: What Works Best for Customer Analytics

Strengthen Claude Sentiment and Premium Positioning

Improve the mixed sentiment on Claude despite strong 46% mention rates by launching targeted content that reinforces Lang.ai's premium positioning and addresses any narrative gaps. This strategy focuses on amplifying success stories, technical credibility, and differentiated value through channels that influence AI model training data. Social media will showcase customer wins and technical excellence to shift perception.

Why Enterprise Teams Choose Lang.ai: Real Results from Real Product Leaders

Inside Our AI: How Lang.ai Achieves 95% Accuracy on Unstructured Customer Data

Customer Spotlight: How a Fortune 500 Team Transformed Their Feedback Loop in 30 Days

The Technology Behind the Magic: What Makes Lang.ai Different from Generic Analytics Tools

From Skeptic to Advocate: One Data Analyst's Journey with AI-Powered Insights

Build Category Trust Through Third-Party Validation

Close the credibility gap with competitors like Zendesk and Snowflake by aggressively pursuing third-party mentions, reviews, and analyst recognition that AI models reference when recommending trusted providers. This involves securing placements in industry publications, review aggregators, and analyst reports while encouraging authentic customer reviews. Social proof campaigns will amplify these validations across all channels.

What G2 Reviewers Say About Switching from Manual Tagging to Lang.ai

Lang.ai Named a Leader in Customer Intelligence: What This Means for Our Customers

10 Reasons Analysts Recommend AI-Powered Unstructured Data Processing for 2026

Independent Review: How Lang.ai Stacks Up Against Legacy CX Analytics Tools

Customer Trust Report: Why Teams Stay with Lang.ai Year After Year

Content Engineering

Recommended Actions

Develop and index strategic thought leadership specifically targeting the 'CX Executive' persona.

The current 0% visibility for this persona means the AI models do not associate Lang.ai with high-level business strategy, effectively blocking enterprise-level sales.

Impact: High

Optimize for AI Overviews by creating structured, comparison-style content for unstructured data processing.

With 0% visibility in AI Overviews, Lang.ai is missing out on the primary AI-driven search interface used by modern researchers.

Impact: High

Launch a targeted campaign to improve sentiment and positioning on Claude.

Claude has a high mention rate (46%) but mixed sentiment; improving this narrative will solidify Lang.ai as a premium choice during the evaluation phase.

Impact: Medium

Aggressively target 'Category Trust' keywords through third-party mentions and review aggregation.

Competitors like Zendesk and Snowflake are cited as 'trusted providers' far more frequently, creating a credibility gap that hurts the final stages of the buyer journey.

Impact: Medium

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