Executive Summary

Many organizations skip rigorous process mapping and jump straight to automating manual work, which often produces brittle automations, missed exceptions, and negative ROI; this is most acute among mid-market companies, shared-services centers, and automation Centers of Excellence that run hundreds of ad-hoc screens, spreadsheets and cross-application handoffs. Finance, operations, customer service and HR teams — and the IT groups asked to implement bots — bear the cost of failed automations in rework, compliance risk and user mistrust. You could build a pre-automation platform that automatically discovers, maps and validates end-to-end manual processes by combining UI trace capture, system log-based process mining, and LLM-driven translation of traces into readable workflows and candidate automation scripts. The product would include human-in-the-loop annotation, simulated execution against synthetic or replayed data to surface edge cases, and a quantified ROI and risk scorecard that forecasts savings, error reduction, and compliance impact before any production bot is deployed. Packaged connectors to popular RPA/low-code platforms would enable one-click export of validated flows and a governance dashboard to track drift, exceptions and value over time. This is an attractive $60.0B addressable market (5,000,000 businesses x $12K ACV) with a market score of 90/100 and revenue potential 88/100 because AI now makes translating traces to runnable automations feasible, enterprises are instrumenting systems for process-mining, and procurement increasingly demands measurable pre-deployment ROI. To stand out in a medium-competition landscape you must emphasize pre-deployment evidence — accurate discovery, simulated execution, and clear value metrics — rather than selling yet another bot-builder, and tightly integrate with incumbent RPA and process-mining vendors to reduce friction for buyers. Challenges include the need for high-quality instrumentation and labeled traces, long enterprise sales cycles, and convincing organizations to adopt a "map-first" discipline, but if you can reduce failed automation projects even modestly you unlock a large, quantifiable revenue stream.

Market Opportunity

Map broken manual processes before automating to avoid worse outcomes targets a $60.0B = 5,000,000 businesses x $12K ACV (global market for business process automation, low-code/RPA, and process optimization tools) total addressable market with medium saturation and a year-over-year growth rate of 15% CAGR (process automation / low-code / process mining markets).

Key trends driving demand: AI-enabled code and workflow generation -- LLMs can translate process descriptions and UI traces into automation flows, reducing engineering cost.; Process-mining adoption -- organizations increasingly instrument systems with logs, enabling automated discovery and bottleneck detection.; Shift to outcomes and ROI -- procurement now demands measurable cost/time savings from automation projects, favoring solutions that prove impact pre-deployment..

Key competitors include UiPath, Celonis, Microsoft Power Automate, Zapier, Workato.

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Map broken manual processes before automating to avoid worse outcomes

Executive Summary

Market Validation

Market Opportunity

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