Detecting scope creep in software-agency projects via AI

Scope creep—undocumented feature additions, shifting acceptance criteria, and informal change requests—erodes margins and predictability for software agencies and internal product teams, especially those operating under fixed-scope or mixed contracts. The addressable audience is roughly 1,000,000 development teams and agencies, equating to a $3.0B opportunity at an indicative $3,000 ACV per team per year. You could build an AI-first platform that semantically ingests contracts, tickets, commit messages, and Slack threads via APIs to flag deviations from agreed scope, quantify likely revenue impact, and auto-generate change requests and client-facing summaries. Core capabilities would include contract-aware LLM analysis, real-time integrations with Jira/ClickUp/Trello/Slack, and privacy-sensitive deployment options for enterprise customers. The timing is favorable: market score 92/100 and revenue potential 88/100 reflect strong tailwinds from LLMs enabling semantic understanding and the prevalence of API-first PM tools. Competition is medium—existing products focus on time tracking, velocity analytics, or expense management, but few combine contract semantics with proactive remediation, which is a clear differentiation point. Strengths are measurable ROI and workflow automation; challenges are data access, integration complexity, and controlling false positives, so validate with a 10–20 agency pilot measuring reductions in unbilled work and increase in approved change orders before scaling.