Verslay is an AI agent platform that gives business owners access to 98 pre-built AI agents for marketing, sales, operations, finance, and more — all accessible through claude.ai via a single MCP server connection. No coding, no infrastructure, no setup.

How does Verslay work with Claude AI?

Verslay plugs into claude.ai as an MCP (Model Context Protocol) server. Once connected, your Claude AI gains access to all your enabled agents and your connected business tools — so you can run automation by simply describing what you need in plain language.

How much does Verslay cost?

Verslay has a free plan with core agents. Paid plans start at ₹999/month (Starter) and ₹3,499/month (Pro with 5 seats). Enterprise and custom pricing is available for larger teams.

Do I need technical skills or coding to use Verslay?

No. Verslay is built for business owners, not developers. You connect your tools (like HubSpot, Shopify, Slack, or Stripe) once, choose which use-cases to activate, and then run them through natural language in claude.ai. Zero code required.

What tools and integrations does Verslay support?

Verslay integrates with 30+ business tools including HubSpot, Shopify, Slack, Stripe, Google Workspace, Notion, ClickUp, Meta Ads, LinkedIn, Razorpay, Zoho, Zendesk, and many more. New integrations are added regularly.

Is Verslay suitable for small businesses and startups?

Yes. Verslay is designed specifically for small and medium businesses who want enterprise-grade AI automation without an engineering team. The free plan lets you start immediately, and paid plans scale with your needs.

All Use Cases

Customer Success

Knowledge Base Auto-Builder

Turn recurring support tickets into self-service answers.

Automatically identify your top support questions and generate help articles that deflect tickets before they reach your inbox. Reduce inbound volume by 30-50% without hiring more support staff.

Best forEcommerceProfessional ServicesSaaS

Agents7 required

Duration5-10 minutes

Clusters tickets by topic, identifies gaps in existing KB, and generates structured articles with SEO titles.

How it runs

Multi-agent orchestration — here's the flow, step by step.

Call verslay_recall to retrieve prior KB article catalog, topic coverage gaps, and article quality benchmarks stored in memory. Pull all Zendesk tickets from the past 30 days: extract ticket subject, resolution notes, category, product area, and resolution time. Cluster tickets by recurring topic and identify the top 15 most frequent unresolved or repeated issues that lack a KB article. Produce a KB gap manifest as Phase 1 output.

support scanner

Consume Phase 1 KB gap manifest. For each gap topic, classify the article type needed: how-to guide, troubleshooting steps, FAQ, or policy explanation. Assign a priority score based on ticket frequency and average resolution time. Produce a prioritized KB article brief with title, article type, and key questions to answer per topic.

ticket classifier

In parallel with ticket-classifier, call verslay_web_search to find existing documentation, community Q&A threads, and vendor support pages that cover each KB gap topic. Call verslay_youtube_search for product tutorial videos relevant to the most complex troubleshooting topics. Produce a reference source bundle per topic.

web researcher

Consume Phase 2 article briefs and reference source bundles. Write complete KB articles for the top 10 gap topics: clear title, 1-paragraph overview, numbered step-by-step instructions or FAQ entries, troubleshooting tips, and related article suggestions. Produce a set of publication-ready KB articles.

kb generator

Consume Phase 3 KB articles. Format each article to Zendesk Help Center standards: section assignment, SEO-friendly URL slug, meta description, and tagging. Stage articles for review in the Zendesk draft queue. Produce a publication manifest with Zendesk draft IDs.

cms publisher

For any KB articles that should also be published on the WordPress help center or public documentation site, consume Phase 3 articles and Phase 4 formatting. Publish formatted articles to the configured WordPress site. Produce WordPress post IDs as confirmation.

wordpress content operations agent

Receive Zendesk draft IDs and WordPress post IDs from Phases 4 and 5. Notify the support lead of staged articles ready for final review. Deliver a KB build summary to the CS operations team: articles created, topics covered, estimated ticket deflection impact. Call verslay_memorize to store the updated KB catalog and gap analysis in memory. Confirm all deliveries.

distributor

Required Agents

support-scanner
ticket-classifier
web-researcher
kb-generator
cms-publisher
wordpress-content-operations-agent
distributor

Connections

Required

wordpresszendesk

What it does

Ticket cluster analysis
Gap identification
Structured article generation
SEO-optimized titles
Optional CMS publishing

Example prompt

How many recurring questions should I cover (5, 10, or 15), what is the source (support tickets, help desk, email threads), and what format (step-by-step, FAQ, troubleshooting flows)? I will draft KB articles with screenshot placeholders and related links.

Ready to deploy Knowledge Base Auto-Builder?

Start free. One click, full agent orchestration.

Get Started Free →

All Use Cases

Customer Success

Knowledge Base Auto-Builder

Turn recurring support tickets into self-service answers.

Automatically identify your top support questions and generate help articles that deflect tickets before they reach your inbox. Reduce inbound volume by 30-50% without hiring more support staff.

Best forEcommerceProfessional ServicesSaaS

Agents7 required

Duration5-10 minutes

Clusters tickets by topic, identifies gaps in existing KB, and generates structured articles with SEO titles.

How it runs

Multi-agent orchestration — here's the flow, step by step.

Call verslay_recall to retrieve prior KB article catalog, topic coverage gaps, and article quality benchmarks stored in memory. Pull all Zendesk tickets from the past 30 days: extract ticket subject, resolution notes, category, product area, and resolution time. Cluster tickets by recurring topic and identify the top 15 most frequent unresolved or repeated issues that lack a KB article. Produce a KB gap manifest as Phase 1 output.

support scanner

Consume Phase 1 KB gap manifest. For each gap topic, classify the article type needed: how-to guide, troubleshooting steps, FAQ, or policy explanation. Assign a priority score based on ticket frequency and average resolution time. Produce a prioritized KB article brief with title, article type, and key questions to answer per topic.

ticket classifier

In parallel with ticket-classifier, call verslay_web_search to find existing documentation, community Q&A threads, and vendor support pages that cover each KB gap topic. Call verslay_youtube_search for product tutorial videos relevant to the most complex troubleshooting topics. Produce a reference source bundle per topic.

web researcher

Consume Phase 2 article briefs and reference source bundles. Write complete KB articles for the top 10 gap topics: clear title, 1-paragraph overview, numbered step-by-step instructions or FAQ entries, troubleshooting tips, and related article suggestions. Produce a set of publication-ready KB articles.

kb generator

Consume Phase 3 KB articles. Format each article to Zendesk Help Center standards: section assignment, SEO-friendly URL slug, meta description, and tagging. Stage articles for review in the Zendesk draft queue. Produce a publication manifest with Zendesk draft IDs.

cms publisher

For any KB articles that should also be published on the WordPress help center or public documentation site, consume Phase 3 articles and Phase 4 formatting. Publish formatted articles to the configured WordPress site. Produce WordPress post IDs as confirmation.

wordpress content operations agent

Receive Zendesk draft IDs and WordPress post IDs from Phases 4 and 5. Notify the support lead of staged articles ready for final review. Deliver a KB build summary to the CS operations team: articles created, topics covered, estimated ticket deflection impact. Call verslay_memorize to store the updated KB catalog and gap analysis in memory. Confirm all deliveries.

distributor

Required Agents

support-scanner
ticket-classifier
web-researcher
kb-generator
cms-publisher
wordpress-content-operations-agent
distributor

Connections

Required

wordpresszendesk

What it does

Ticket cluster analysis
Gap identification
Structured article generation
SEO-optimized titles
Optional CMS publishing

Example prompt

How many recurring questions should I cover (5, 10, or 15), what is the source (support tickets, help desk, email threads), and what format (step-by-step, FAQ, troubleshooting flows)? I will draft KB articles with screenshot placeholders and related links.

Ready to deploy Knowledge Base Auto-Builder?

Start free. One click, full agent orchestration.

Get Started Free →

All Use Cases

Customer Success

Knowledge Base Auto-Builder

Turn recurring support tickets into self-service answers.

Automatically identify your top support questions and generate help articles that deflect tickets before they reach your inbox. Reduce inbound volume by 30-50% without hiring more support staff.

Best forEcommerceProfessional ServicesSaaS

Agents7 required

Duration5-10 minutes

Clusters tickets by topic, identifies gaps in existing KB, and generates structured articles with SEO titles.

How it runs

Multi-agent orchestration — here's the flow, step by step.

Call verslay_recall to retrieve prior KB article catalog, topic coverage gaps, and article quality benchmarks stored in memory. Pull all Zendesk tickets from the past 30 days: extract ticket subject, resolution notes, category, product area, and resolution time. Cluster tickets by recurring topic and identify the top 15 most frequent unresolved or repeated issues that lack a KB article. Produce a KB gap manifest as Phase 1 output.

support scanner

Consume Phase 1 KB gap manifest. For each gap topic, classify the article type needed: how-to guide, troubleshooting steps, FAQ, or policy explanation. Assign a priority score based on ticket frequency and average resolution time. Produce a prioritized KB article brief with title, article type, and key questions to answer per topic.

ticket classifier

In parallel with ticket-classifier, call verslay_web_search to find existing documentation, community Q&A threads, and vendor support pages that cover each KB gap topic. Call verslay_youtube_search for product tutorial videos relevant to the most complex troubleshooting topics. Produce a reference source bundle per topic.

web researcher

Consume Phase 2 article briefs and reference source bundles. Write complete KB articles for the top 10 gap topics: clear title, 1-paragraph overview, numbered step-by-step instructions or FAQ entries, troubleshooting tips, and related article suggestions. Produce a set of publication-ready KB articles.

kb generator

Consume Phase 3 KB articles. Format each article to Zendesk Help Center standards: section assignment, SEO-friendly URL slug, meta description, and tagging. Stage articles for review in the Zendesk draft queue. Produce a publication manifest with Zendesk draft IDs.

cms publisher

For any KB articles that should also be published on the WordPress help center or public documentation site, consume Phase 3 articles and Phase 4 formatting. Publish formatted articles to the configured WordPress site. Produce WordPress post IDs as confirmation.

wordpress content operations agent

Receive Zendesk draft IDs and WordPress post IDs from Phases 4 and 5. Notify the support lead of staged articles ready for final review. Deliver a KB build summary to the CS operations team: articles created, topics covered, estimated ticket deflection impact. Call verslay_memorize to store the updated KB catalog and gap analysis in memory. Confirm all deliveries.

distributor

Required Agents

support-scanner
ticket-classifier
web-researcher
kb-generator
cms-publisher
wordpress-content-operations-agent
distributor

Connections

Required

wordpresszendesk

What it does

Ticket cluster analysis
Gap identification
Structured article generation
SEO-optimized titles
Optional CMS publishing

Example prompt

How many recurring questions should I cover (5, 10, or 15), what is the source (support tickets, help desk, email threads), and what format (step-by-step, FAQ, troubleshooting flows)? I will draft KB articles with screenshot placeholders and related links.

Ready to deploy Knowledge Base Auto-Builder?

Start free. One click, full agent orchestration.

Get Started Free →