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

Sales

Deal Win/Loss Analyzer

Find out why you are losing deals — and fix it.

Discover the exact patterns killing your close rate with data-driven win/loss analysis across rep, stage, deal size, and vertical. Make targeted improvements that compound over every quarter.

Best forEcommerceConsultingFinancial ServicesProfessional ServicesSaaS

Agents7 required

Duration3-5 minutes

Pulls deal history, segments by outcome, identifies win/loss patterns, and recommends tactical improvements.

How it runs

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

Call verslay_recall to load prior win-rate benchmarks, losing competitor patterns, and deal stage definitions from memory. Scan HubSpot via the connected integration to pull all deals closed (won and lost) within the specified date range: deal name, company, value, stage duration, close reason, and competitor mentioned in notes. Produce a raw deal dataset as Phase 1 output.

crm scanner

Consume Phase 1 deal dataset. Calculate win rate by segment (deal size, industry, rep, competitor), average sales cycle length for wins vs losses, and stage-by-stage drop-off rates. Identify the top 3 win patterns and top 3 loss patterns. Pass the analysis to Phase 3.

deal analyzer

In parallel with deal-analyzer, call verslay_news_search targeting the top 3 competitors identified in Phase 1 loss reasons to surface recent product announcements, pricing changes, and competitive campaigns that may have influenced deal outcomes. Call verslay_web_search for buyer intent signals and industry analyst commentary on the competitive landscape. Pass findings to competitive-intel.

web researcher

Consume Phase 2 competitor news and Phase 2 loss patterns. Call verslay_exclusive_run_actor with actor_id 'yin/g2-reviews-scraper' and the competitor product names to scrape current G2 reviews — capturing what buyers praise and criticize about each competitor. Cross-reference review themes against your own deal loss reasons. Produce a competitive gap analysis with ranked buyer objection themes.

competitive intel

Consume Phase 2 win-loss analysis and Phase 3 competitive gap analysis. Calculate win-rate deltas by competitor and segment. Call verslay_chart_create to produce a win-rate-by-competitor bar chart and a deal-stage drop-off funnel chart. Assemble a synthesis data package for Phase 5.

data analyst

Consume Phase 4 charts, Phase 3 competitive gap analysis, and Phase 2 deal patterns. Write a win-loss executive brief: overall win rate, top win drivers, top loss drivers, competitive vulnerability map, and 5 recommended sales playbook adjustments. Call verslay_memorize to store updated win-rate benchmarks and competitor objection themes in memory.

executive briefing writer

Receive the executive brief from executive-briefing-writer. Format it as a structured board-ready deliverable: summary scorecard, win-rate-by-competitor chart, deal-stage funnel chart, competitive gap table, and ranked playbook recommendations. Return the final formatted report to the user.

report formatter

Required Agents

crm-scanner
deal-analyzer
web-researcher
competitive-intel
data-analyst
executive-briefing-writer
report-formatter

Connections

Required

hubspotverslay_exclusive

What it does

Win rate by dimension
Pipeline bottleneck identification
Lost deal reason ranking
Rep performance comparison
Forecast-ready summaries

Example prompt

What time period should I analyze (last quarter, last 6 months, this year) and how should I break it down (deal size, sales rep, industry, lead source)? I will identify the top 3 reasons we win and lose, with recommendations.

Ready to deploy Deal Win/Loss Analyzer?

Start free. One click, full agent orchestration.

Get Started Free →

All Use Cases

Sales

Deal Win/Loss Analyzer

Find out why you are losing deals — and fix it.

Discover the exact patterns killing your close rate with data-driven win/loss analysis across rep, stage, deal size, and vertical. Make targeted improvements that compound over every quarter.

Best forEcommerceConsultingFinancial ServicesProfessional ServicesSaaS

Agents7 required

Duration3-5 minutes

Pulls deal history, segments by outcome, identifies win/loss patterns, and recommends tactical improvements.

How it runs

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

Call verslay_recall to load prior win-rate benchmarks, losing competitor patterns, and deal stage definitions from memory. Scan HubSpot via the connected integration to pull all deals closed (won and lost) within the specified date range: deal name, company, value, stage duration, close reason, and competitor mentioned in notes. Produce a raw deal dataset as Phase 1 output.

crm scanner

Consume Phase 1 deal dataset. Calculate win rate by segment (deal size, industry, rep, competitor), average sales cycle length for wins vs losses, and stage-by-stage drop-off rates. Identify the top 3 win patterns and top 3 loss patterns. Pass the analysis to Phase 3.

deal analyzer

In parallel with deal-analyzer, call verslay_news_search targeting the top 3 competitors identified in Phase 1 loss reasons to surface recent product announcements, pricing changes, and competitive campaigns that may have influenced deal outcomes. Call verslay_web_search for buyer intent signals and industry analyst commentary on the competitive landscape. Pass findings to competitive-intel.

web researcher

Consume Phase 2 competitor news and Phase 2 loss patterns. Call verslay_exclusive_run_actor with actor_id 'yin/g2-reviews-scraper' and the competitor product names to scrape current G2 reviews — capturing what buyers praise and criticize about each competitor. Cross-reference review themes against your own deal loss reasons. Produce a competitive gap analysis with ranked buyer objection themes.

competitive intel

Consume Phase 2 win-loss analysis and Phase 3 competitive gap analysis. Calculate win-rate deltas by competitor and segment. Call verslay_chart_create to produce a win-rate-by-competitor bar chart and a deal-stage drop-off funnel chart. Assemble a synthesis data package for Phase 5.

data analyst

Consume Phase 4 charts, Phase 3 competitive gap analysis, and Phase 2 deal patterns. Write a win-loss executive brief: overall win rate, top win drivers, top loss drivers, competitive vulnerability map, and 5 recommended sales playbook adjustments. Call verslay_memorize to store updated win-rate benchmarks and competitor objection themes in memory.

executive briefing writer

Receive the executive brief from executive-briefing-writer. Format it as a structured board-ready deliverable: summary scorecard, win-rate-by-competitor chart, deal-stage funnel chart, competitive gap table, and ranked playbook recommendations. Return the final formatted report to the user.

report formatter

Required Agents

crm-scanner
deal-analyzer
web-researcher
competitive-intel
data-analyst
executive-briefing-writer
report-formatter

Connections

Required

hubspotverslay_exclusive

What it does

Win rate by dimension
Pipeline bottleneck identification
Lost deal reason ranking
Rep performance comparison
Forecast-ready summaries

Example prompt

What time period should I analyze (last quarter, last 6 months, this year) and how should I break it down (deal size, sales rep, industry, lead source)? I will identify the top 3 reasons we win and lose, with recommendations.

Ready to deploy Deal Win/Loss Analyzer?

Start free. One click, full agent orchestration.

Get Started Free →

All Use Cases

Sales

Deal Win/Loss Analyzer

Find out why you are losing deals — and fix it.

Discover the exact patterns killing your close rate with data-driven win/loss analysis across rep, stage, deal size, and vertical. Make targeted improvements that compound over every quarter.

Best forEcommerceConsultingFinancial ServicesProfessional ServicesSaaS

Agents7 required

Duration3-5 minutes

Pulls deal history, segments by outcome, identifies win/loss patterns, and recommends tactical improvements.

How it runs

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

Call verslay_recall to load prior win-rate benchmarks, losing competitor patterns, and deal stage definitions from memory. Scan HubSpot via the connected integration to pull all deals closed (won and lost) within the specified date range: deal name, company, value, stage duration, close reason, and competitor mentioned in notes. Produce a raw deal dataset as Phase 1 output.

crm scanner

Consume Phase 1 deal dataset. Calculate win rate by segment (deal size, industry, rep, competitor), average sales cycle length for wins vs losses, and stage-by-stage drop-off rates. Identify the top 3 win patterns and top 3 loss patterns. Pass the analysis to Phase 3.

deal analyzer

In parallel with deal-analyzer, call verslay_news_search targeting the top 3 competitors identified in Phase 1 loss reasons to surface recent product announcements, pricing changes, and competitive campaigns that may have influenced deal outcomes. Call verslay_web_search for buyer intent signals and industry analyst commentary on the competitive landscape. Pass findings to competitive-intel.

web researcher

Consume Phase 2 competitor news and Phase 2 loss patterns. Call verslay_exclusive_run_actor with actor_id 'yin/g2-reviews-scraper' and the competitor product names to scrape current G2 reviews — capturing what buyers praise and criticize about each competitor. Cross-reference review themes against your own deal loss reasons. Produce a competitive gap analysis with ranked buyer objection themes.

competitive intel

Consume Phase 2 win-loss analysis and Phase 3 competitive gap analysis. Calculate win-rate deltas by competitor and segment. Call verslay_chart_create to produce a win-rate-by-competitor bar chart and a deal-stage drop-off funnel chart. Assemble a synthesis data package for Phase 5.

data analyst

Consume Phase 4 charts, Phase 3 competitive gap analysis, and Phase 2 deal patterns. Write a win-loss executive brief: overall win rate, top win drivers, top loss drivers, competitive vulnerability map, and 5 recommended sales playbook adjustments. Call verslay_memorize to store updated win-rate benchmarks and competitor objection themes in memory.

executive briefing writer

Receive the executive brief from executive-briefing-writer. Format it as a structured board-ready deliverable: summary scorecard, win-rate-by-competitor chart, deal-stage funnel chart, competitive gap table, and ranked playbook recommendations. Return the final formatted report to the user.

report formatter

Required Agents

crm-scanner
deal-analyzer
web-researcher
competitive-intel
data-analyst
executive-briefing-writer
report-formatter

Connections

Required

hubspotverslay_exclusive

What it does

Win rate by dimension
Pipeline bottleneck identification
Lost deal reason ranking
Rep performance comparison
Forecast-ready summaries

Example prompt

What time period should I analyze (last quarter, last 6 months, this year) and how should I break it down (deal size, sales rep, industry, lead source)? I will identify the top 3 reasons we win and lose, with recommendations.

Ready to deploy Deal Win/Loss Analyzer?

Start free. One click, full agent orchestration.

Get Started Free →