SignalForge is an audience-intent processing engine for operators like Eli Abdeen who receive a constant stream of unstructured inbound signals (DMs, replies, emails) but struggle to systematically extract product ideas and patterns. On r/SaaS and HN, builders repeatedly mention tons of anecdotal input but no rigorous funnel from “people keep asking me about X” to “validated product spec.” SignalForge connects to X, email, and form tools and transforms qualitative demand into a prioritized, quantifiable backlog. Value props:

Intent clustering: automatically groups inbound messages around recurring themes (e.g., “how do I validate?”, “how to price a SaaS?”) with frequency and persona breakdowns.
Monetization mapping: for each cluster, suggests the most fitting format (template pack, micro-SaaS, workshop, cohort) based on ticket size norms and examples pulled from creators and small SaaS benchmarks.
Confidence scoring: combines message volume, engagement metrics, and external search trends for the same phrases to rank which ideas justify a build sprint.
Feedback-to-spec pipeline: turns the highest-scoring cluster into a structured spec: personas, JTBDs, must-have features, and launch checklist that a small dev team could execute within 6–12 weeks. Existing tools like CRMs and analytics tags don’t close the loop between loose expert inbound and concrete product decisions; SignalForge is built specifically for experts sitting on underutilized demand like Eli.