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Executive Summary

Many SMBs, customer-support and account teams struggle with fragmented customer records split across ERP systems (orders, invoices, inventory) and CRM tools (contacts, cases, opportunities), which leads to slower support, missed renewals and revenue leakage; globally there are roughly 30 million SMBs representing a $110B CRM+ERP spend potential at an average ACV of $3,667. The problem is most acute where transactional context—shipment status, invoice disputes, payment history—is not surfaced to front-line agents, so decisions are manual, inconsistent and slow. You could build a unified platform that synchronizes ERP and CRM data near-real-time using API-first connectors, canonicalizes transaction-level events, and sits an AI layer on top that produces concise summaries, embeddings-enabled search and prescriptive next-action recommendations for agents and account managers. The product would include pre-built connectors for major ERP/CRM vendors, low-code mapping for different taxonomies, role-based views (support, collections, sales), and workflows that translate AI suggestions into automated case creation or escalation. This is an attractive moment because LLMs and embeddings now make reliable summarization and pattern detection feasible at scale, modern ERPs expose richer APIs that cut integration time, and SMB digitization pressures mean buyers are motivated to consolidate systems to save cost and retain customers; the TAM of $110B and 30M potential SMB customers suggest meaningful upside. Competition is medium—established CRMs, middleware vendors and vertical ERPs exist—but few focus on transactional intelligence that directly ties to support and revenue outcomes. To stand out you’ll need to prove measurable ROI (reduced time-to-resolution, lower churn, faster collections), invest in privacy-first embedding strategies and certifications, and ship high-quality, industry-specific templates to reduce onboarding friction; these are realistic differentiators but require careful engineering and partner sales. Be honest that major challenges are data quality across heterogeneous systems, change management within SMBs, and the need for a strong go-to-market partner strategy to scale.

Executive Summary

Fragmented customer data — unify ERP + CRM with AI to improve relationships

Executive Summary

Fragmented customer data — unify ERP + CRM with AI to improve relationships

Executive Summary

Market Validation

Market Opportunity

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Slow self‑serve support — AI chat that answers from your website & docs

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After-install care for window‑furnishing businesses — AI triage & field service

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