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

Finance

Payment Reconciliation

Close your books without the manual reconciliation work.

Automatically cross-reference every payment against every invoice with a 3-pass matching algorithm that flags discrepancies, ages balances, and identifies write-off candidates. Cut month-end close time in half.

Best forEcommerceConsultingFinancial ServicesProfessional ServicesSaaS

Agents7 required

Duration5-10 minutes

Runs 3-pass matching across payment and invoice records.

How it runs

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

Call verslay_recall to retrieve prior reconciliation run baselines, known CRM-to-payment gap patterns, and reconciliation thresholds from memory. Connect to HubSpot to pull all closed-won deals and their expected payment amounts, payment dates, and associated contact/company IDs for the specified period. Produce a CRM expected-revenue ledger as Phase 1 output.

crm scanner

Connect to Stripe to pull all successful charges, refunds, and disputes for the same period as Phase 1 crm-scanner: charge IDs, amounts, customer IDs, and metadata. Cross-reference Stripe customer IDs and metadata against HubSpot deal contact IDs to begin matching. Produce a raw payment dataset to pair with the CRM ledger.

payment scanner

Consume Phase 1 CRM expected-revenue ledger and Phase 1 Stripe payment dataset. Perform systematic matching: for each HubSpot deal, find the corresponding Stripe charge(s). Flag unmatched deals (CRM deal with no payment), unmatched payments (Stripe charge with no CRM deal), amount mismatches (deal value ≠ charged amount), and timing gaps (payment date > deal close date by >30 days). Produce a categorized discrepancy report for Phase 3.

reconciliation checker

In parallel with reconciliation-checker, call verslay_web_search for 'HubSpot Stripe reconciliation best practices 2026' and 'CRM to payment gateway matching standards' to surface tooling and process benchmarks. Call verslay_news_search for any HubSpot or Stripe API change announcements that may explain systematic matching failures. Produce a reconciliation standards package for Phase 4.

web researcher

Consume Phase 2 discrepancy report and Phase 2 reconciliation standards. Aggregate discrepancies by type (unmatched deal, unmatched payment, amount mismatch, timing gap) and calculate total at-risk revenue. Call verslay_chart_create to generate a discrepancy-by-type bar chart and a reconciliation-accuracy trend chart (this period vs prior periods from memory). Produce a synthesis package for Phase 5.

data analyst

Consume Phase 3 charts and synthesis, Phase 2 discrepancy report, and Phase 2 reconciliation standards. Write a payment reconciliation brief: match rate summary, discrepancy breakdown by type, total at-risk revenue, root cause analysis for top discrepancy patterns, and recommended remediation actions (CRM hygiene fixes, Stripe metadata tagging, manual review items). Call verslay_memorize to store the current period's match rate, discrepancy totals, and top gap patterns. Pass brief to distributor.

executive briefing writer

Receive the reconciliation brief from executive-briefing-writer. Distribute to the configured finance team email or Slack channel. Confirm delivery and log the send timestamp.

distributor

Required Agents

crm-scanner
payment-scanner
reconciliation-checker
web-researcher
data-analyst
executive-briefing-writer
distributor

Connections

Required

hubspotstripe

What it does

3-pass matching algorithm
Discrepancy classification
Aging buckets through 90+ days
Write-off candidate flagging
Fuzzy match confirmation queue

Example prompt

Which time period should I reconcile (last month or specific date range)? I will flag unmatched payments, partial payments, duplicates, and missing invoices, group discrepancies by client/amount/age, and produce an action-item report.

Ready to deploy Payment Reconciliation?

Start free. One click, full agent orchestration.

Get Started Free →

All Use Cases

Finance

Payment Reconciliation

Close your books without the manual reconciliation work.

Best forEcommerceConsultingFinancial ServicesProfessional ServicesSaaS

Agents7 required

Duration5-10 minutes

Runs 3-pass matching across payment and invoice records.

How it runs

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

Call verslay_recall to retrieve prior reconciliation run baselines, known CRM-to-payment gap patterns, and reconciliation thresholds from memory. Connect to HubSpot to pull all closed-won deals and their expected payment amounts, payment dates, and associated contact/company IDs for the specified period. Produce a CRM expected-revenue ledger as Phase 1 output.

crm scanner

Connect to Stripe to pull all successful charges, refunds, and disputes for the same period as Phase 1 crm-scanner: charge IDs, amounts, customer IDs, and metadata. Cross-reference Stripe customer IDs and metadata against HubSpot deal contact IDs to begin matching. Produce a raw payment dataset to pair with the CRM ledger.

payment scanner

Consume Phase 1 CRM expected-revenue ledger and Phase 1 Stripe payment dataset. Perform systematic matching: for each HubSpot deal, find the corresponding Stripe charge(s). Flag unmatched deals (CRM deal with no payment), unmatched payments (Stripe charge with no CRM deal), amount mismatches (deal value ≠ charged amount), and timing gaps (payment date > deal close date by >30 days). Produce a categorized discrepancy report for Phase 3.

reconciliation checker

In parallel with reconciliation-checker, call verslay_web_search for 'HubSpot Stripe reconciliation best practices 2026' and 'CRM to payment gateway matching standards' to surface tooling and process benchmarks. Call verslay_news_search for any HubSpot or Stripe API change announcements that may explain systematic matching failures. Produce a reconciliation standards package for Phase 4.

web researcher

Consume Phase 2 discrepancy report and Phase 2 reconciliation standards. Aggregate discrepancies by type (unmatched deal, unmatched payment, amount mismatch, timing gap) and calculate total at-risk revenue. Call verslay_chart_create to generate a discrepancy-by-type bar chart and a reconciliation-accuracy trend chart (this period vs prior periods from memory). Produce a synthesis package for Phase 5.

data analyst

Consume Phase 3 charts and synthesis, Phase 2 discrepancy report, and Phase 2 reconciliation standards. Write a payment reconciliation brief: match rate summary, discrepancy breakdown by type, total at-risk revenue, root cause analysis for top discrepancy patterns, and recommended remediation actions (CRM hygiene fixes, Stripe metadata tagging, manual review items). Call verslay_memorize to store the current period's match rate, discrepancy totals, and top gap patterns. Pass brief to distributor.

executive briefing writer

Receive the reconciliation brief from executive-briefing-writer. Distribute to the configured finance team email or Slack channel. Confirm delivery and log the send timestamp.

distributor

Required Agents

crm-scanner
payment-scanner
reconciliation-checker
web-researcher
data-analyst
executive-briefing-writer
distributor

Connections

Required

hubspotstripe

What it does

3-pass matching algorithm
Discrepancy classification
Aging buckets through 90+ days
Write-off candidate flagging
Fuzzy match confirmation queue

Example prompt

Which time period should I reconcile (last month or specific date range)? I will flag unmatched payments, partial payments, duplicates, and missing invoices, group discrepancies by client/amount/age, and produce an action-item report.

Ready to deploy Payment Reconciliation?

Start free. One click, full agent orchestration.

Get Started Free →

All Use Cases

Finance

Payment Reconciliation

Close your books without the manual reconciliation work.

Best forEcommerceConsultingFinancial ServicesProfessional ServicesSaaS

Agents7 required

Duration5-10 minutes

Runs 3-pass matching across payment and invoice records.

How it runs

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

Call verslay_recall to retrieve prior reconciliation run baselines, known CRM-to-payment gap patterns, and reconciliation thresholds from memory. Connect to HubSpot to pull all closed-won deals and their expected payment amounts, payment dates, and associated contact/company IDs for the specified period. Produce a CRM expected-revenue ledger as Phase 1 output.

crm scanner

Connect to Stripe to pull all successful charges, refunds, and disputes for the same period as Phase 1 crm-scanner: charge IDs, amounts, customer IDs, and metadata. Cross-reference Stripe customer IDs and metadata against HubSpot deal contact IDs to begin matching. Produce a raw payment dataset to pair with the CRM ledger.

payment scanner

Consume Phase 1 CRM expected-revenue ledger and Phase 1 Stripe payment dataset. Perform systematic matching: for each HubSpot deal, find the corresponding Stripe charge(s). Flag unmatched deals (CRM deal with no payment), unmatched payments (Stripe charge with no CRM deal), amount mismatches (deal value ≠ charged amount), and timing gaps (payment date > deal close date by >30 days). Produce a categorized discrepancy report for Phase 3.

reconciliation checker

In parallel with reconciliation-checker, call verslay_web_search for 'HubSpot Stripe reconciliation best practices 2026' and 'CRM to payment gateway matching standards' to surface tooling and process benchmarks. Call verslay_news_search for any HubSpot or Stripe API change announcements that may explain systematic matching failures. Produce a reconciliation standards package for Phase 4.

web researcher

Consume Phase 2 discrepancy report and Phase 2 reconciliation standards. Aggregate discrepancies by type (unmatched deal, unmatched payment, amount mismatch, timing gap) and calculate total at-risk revenue. Call verslay_chart_create to generate a discrepancy-by-type bar chart and a reconciliation-accuracy trend chart (this period vs prior periods from memory). Produce a synthesis package for Phase 5.

data analyst

Consume Phase 3 charts and synthesis, Phase 2 discrepancy report, and Phase 2 reconciliation standards. Write a payment reconciliation brief: match rate summary, discrepancy breakdown by type, total at-risk revenue, root cause analysis for top discrepancy patterns, and recommended remediation actions (CRM hygiene fixes, Stripe metadata tagging, manual review items). Call verslay_memorize to store the current period's match rate, discrepancy totals, and top gap patterns. Pass brief to distributor.

executive briefing writer

Receive the reconciliation brief from executive-briefing-writer. Distribute to the configured finance team email or Slack channel. Confirm delivery and log the send timestamp.

distributor

Required Agents

crm-scanner
payment-scanner
reconciliation-checker
web-researcher
data-analyst
executive-briefing-writer
distributor

Connections

Required

hubspotstripe

What it does

3-pass matching algorithm
Discrepancy classification
Aging buckets through 90+ days
Write-off candidate flagging
Fuzzy match confirmation queue

Example prompt

Which time period should I reconcile (last month or specific date range)? I will flag unmatched payments, partial payments, duplicates, and missing invoices, group discrepancies by client/amount/age, and produce an action-item report.

Ready to deploy Payment Reconciliation?

Start free. One click, full agent orchestration.

Get Started Free →