My Skeptiq web app connects to Supabase Auth and Realtime.
My Skeptiq background worker connects to PostgreSQL / Supabase.
My Skeptiq web app provides a public landing page and magic-link authentication.
My Skeptiq web app provides an authenticated overview and new-simulation workflow.
My Skeptiq web app includes a simulation archive, persona explorer, reports, and settings.
My Skeptiq web app has a live job page driven by Supabase Realtime updates.
My Skeptiq web app supports public report sharing using an exact share token checked server-side.
My Skeptiq web app provides worker health, queue state, and wake endpoints for hosts that sleep idle services.
My Skeptiq database stores ideas, simulation jobs, clusters, personas, dialogue turns, reports, and cross-examinations.
My Skeptiq database uses owner-scoped row-level security for browser access.
My Skeptiq database configures Realtime publication for job and dialogue updates.
My Skeptiq database performs atomic simulation creation through a database function.
My Skeptiq validation and contracts use Zod and a shared workspace package.
My Skeptiq repository layout includes apps/web/ for the Next.js 15 App Router UI, auth, API routes, exports, and live updates.
My Skeptiq repository layout includes worker/ for queue polling, multi-agent pipeline, health server, and notifications.
My Skeptiq repository layout includes shared/ for Zod schemas and TypeScript contracts shared by web and worker.
My Skeptiq repository layout includes migrations/ for PostgreSQL schema, indexes, RLS policies, Realtime, and job RPCs.
My Skeptiq web stack is Next.js 15, React 19, TypeScript, Tailwind CSS 4.
My Skeptiq authentication and realtime stack is Supabase Auth, Supabase Realtime.
My Skeptiq database stack is PostgreSQL via Supabase, pg, SQL migrations.
My Skeptiq inference stack is Groq SDK with optional OpenRouter fallback.
My Skeptiq embeddings and clustering use @xenova/transformers and ml-kmeans, run in the worker.
My Skeptiq worker claims queued jobs from PostgreSQL and advances them through the pipeline.
My Skeptiq inference router uses Groq first and can fall back to free OpenRouter routes when configured.
For Skeptiq deployment, model identifiers and free-tier availability can change, so treat the constants in apps/worker/src/ai/groq.ts as deployment configuration that should be rechecked periodically.
My Skeptiq web app supports branch/pivot creation and post-run persona cross-examination.
My Skeptiq database has status constraints shared conceptually with packages/shared/src/status.ts.
The worker and server routes use a privileged PostgreSQL connection, so their authorization checks remain security-critical even when RLS is enabled for browser clients.
My Skeptiq worker exposes GET /health (and /) for liveness and current-job state.
My Skeptiq worker exposes GET /metrics for worker metrics.
My Skeptiq worker exposes POST /chat (and /api/chat) for persona follow-up inference used by the web server.
I host the Skeptiq repository on my GitHub account, @AdityaBansal-code.
I started the Skeptiq repository in 2026-09.
I am building Skeptiq, a working-name product for stress-testing product and business ideas with AI-generated personas before investing heavily. Its reports are synthetic decision-support, not evidence of measured market demand; I use them to form hypotheses and plan real-world interviews or experiments, not as a substitute for customer evidence.
Skeptiq is an AI-assisted market-validation platform for stress-testing a product or business idea before investing heavily in it.
The participants in Skeptiq's simulations are AI-generated personas.
Adoption ranges, segments, quotes, and pricing outputs are simulated decision-support signals—not measured market demand.
I use the report to form hypotheses and design interviews or experiments, not as a substitute for evidence from real customers.
Skeptiq runs either a segmentation simulation to discover distinct audience positions or a consensus simulation to examine convergence and unresolved disagreement.
Skeptiq supports panels from 3 to 30 personas and quick, standard, or exhaustive deliberation depths.
Skeptiq targets general consumers, B2B SaaS buyers, Gen Z creators, small-business owners, developers, or healthcare audiences.
Skeptiq performs source-aware market reconnaissance and handles novel ideas without inventing direct competitors.
Skeptiq captures each persona's independent reaction before group discussion to reduce immediate group influence.
Skeptiq embeds reactions locally and clusters them with k-means; the worker can select the cluster count using silhouette scoring.
Skeptiq simulates cross-talk between opposing audience segments and rejects truncated or instruction-leaking model responses before storage.
Skeptiq produces an executive report with audience segments, objections, conditional adoption ranges, price sensitivity, supporting dialogue, and a next-step validation experiment.
Authenticated users can monitor runs in real time, browse archives, inspect personas and dialogue, export Markdown or JSON, and cross-examine a persona after a run.
Skeptiq supports public report links and branch simulations for testing a revised proposition against the original persona cohort.
Skeptiq optionally sends completion email notifications and signed, SSRF-guarded webhooks.
Skeptiq's repository contains a Next.js application, a long-running simulation worker, shared TypeScript contracts, and a Supabase/PostgreSQL schema.
Skeptiq's name is provisional and can be changed without altering the core architecture.
Skeptiq supports an optional deterministic seed passed through supported generation steps.
Skeptiq lets a user reuse a completed run's cohort to test a pivot.
Skeptiq supports automatic segment selection or a requested segment count from 2–6.
Skeptiq asks four-point price questions as part of its simulation process.
The run proceeds through market reconnaissance; persona generation or parent-cohort cloning for a branch; independent reactions and price questions; local embeddings and opinion clustering; adversarial cross-talk and Delphi-style deliberation; structured synthesis with an evidence map and action plan; and report delivery with export, sharing, follow-up Q&A, and notifications. Each stage is checkpointed. The worker records heartbeats, retries transient failures after cleaning partial stage artifacts, tracks token use, checks for cancellation, and has a stale-job reaper to reclaim interrupted work after restart.
Skeptiq supports panels of 3 to 30 personas.
The default Skeptiq panel size is 6 personas.
Quick deliberation in Skeptiq runs for 5 turns.
Standard deliberation in Skeptiq runs for 12 turns.
Exhaustive deliberation in Skeptiq runs for 24 turns.
The README leaves important implementation and evaluation details open: it does not specify reconnaissance sources, the embedding model, LLM providers, or how silhouette scoring is implemented. It also does not define how conditional adoption ranges or price-sensitivity outputs are calculated, or document webhook payloads, signing algorithms, SSRF defenses, notification providers, and public-link access controls. It provides no measured accuracy or validation results against real customer demand.