Research-to-opportunity workspace
Turns saved links, notes, files, and rough evidence into a searchable library, then helps turn recurring pain points into evaluated opportunity briefs. Thin evidence points back to research before any idea gets promoted.
Useful clues about real problems get scattered across saved links, notes, and posts. The pile keeps growing without a clear view of what's worth building or pursuing.
A private research-to-opportunity workspace. Capture links, notes, and posts, add small files, and use a Chrome extension to grab sources in context. The library keeps the raw material searchable. The Forge helps pull out recurring pain points, and the Vault keeps the briefs that are worth revisiting.
SignalFoundry runs as a live private preview that stays gated while I keep refining the core workflow. This case study is the public version; the app itself remains invitation-only.
The app stays small on purpose. You add material, review it in the Library, and use The Forge to decide which patterns deserve a brief.
Add links, text notes, and small files; capture from the browser in context.
Search, filter by topic, and review everything you've captured.
Group evidence into pain points and draft opportunity briefs.
Revisit saved briefs with their evidence and decision history.
Cache-first reruns keep LLM cost and latency down. The Forge checks source strength before a weak summary becomes a build recommendation.
Links, notes, and X posts arrive through the app or Chrome extension.
Extraction and source metadata turn rough input into reviewable evidence.
Every source remains searchable with tags, titles, URLs, and summaries.
Evidence becomes candidate pain points, with weak signal clearly marked.
Selected points generate briefs through the opportunity queue contract.
Saved briefs keep confidence, uncertainty, and source history attached.
Thin inputs prompt more research before a brief is generated.
Repeated inputs reuse prior extraction and summaries, so reruns stay cheap and fast.
A Chrome extension with enriched X-post extraction keeps evidence capture close to the moment of discovery.
Provider abstraction, schema-validated outputs, caching, and explicit retry states keep model-backed stages inspectable and recoverable.
These screenshots were captured from the working SignalFoundry UI with route-mocked synthetic data. They don't include private research, customer data, API keys, or real opportunity briefs.
01 · Capture
Links, text notes, and files become explicit entries instead of disappearing into hidden parsing rules.
02 · Review
Captured material stays searchable by title, URL, and tags, with topic filters and source context visible in the review list.
03 · Synthesize
Candidate pain points preserve confidence and uncertainty; weak evidence is visible before briefs are generated.
04 · Revisit
Saved briefs keep confidence, next steps, risks, and evidence counts intact.
SignalFoundry fits research-heavy work where saved material needs to become a decision: product discovery, market research, content operations, deal sourcing, trend mining, or consulting.
Raw capture flows into evaluated opportunity briefs without leaving the workspace.
Weak inputs stay visible before anyone commits to a brief.
A real Next.js product with a browser capture extension and stable data contracts.
SignalFoundry and Contract Hunter use the same pattern on different inputs. Contract Hunter sorts job and contract postings; SignalFoundry organizes research.
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Need research capture, evidence review, or opportunity workflows turned into a usable product?