sales-skills/sales-inodash

Inodash Platform Help

Inodash (inodash.com) is an AI product-validation and innovation platform built to help teams reach product-market fit faster. Its free Startup Idea Validator — describe an idea → an instant market/audience/competitor read plus a saved report (Target Audience, Market Analysis, Competitors, Revenue Models, Validation Methods, GTM, and "Critical Investor Questions") — is the front door to a broader workspace: Smart Boards (AI-generated business canvases), a Persona Maker, an Idea Generator, a Competitor Analyzer, a Financial Forecast Builder, Deck Evaluators (founder and investor views), a team progress dashboard, and — on paid tiers — custom RAG model training on your own data. Work is metered by AI tokens per project, and the whole thing is team-first (workspaces, roles, collaboration). It's a fast structured second opinion and a place to organize early-stage work — not a substitute for real demand validation — and it has no public API (UI tool).

Step 1 — Gather context

If references/learnings.md exists, read it first for accumulated platform knowledge.

Ask only what you can't infer:

1. What do you want from Inodash?
   • A) Run an idea through the validator and interpret the report (market, audience, competitors, "Critical Investor Questions")
   • B) Use one of the other tools — Persona Maker, Idea Generator, Competitor Analyzer, Financial Forecast Builder, Deck Evaluator, Smart Boards
   • C) Understand the pricing (AI tokens per project, workspace/project limits, what's plan-gated — dashboard, data export, RAG training)
   • D) Collaborate with a team, or export/automate programmatically (API reality)
2. What's the real question — "is this idea worth building?" or "how do I use this tool?" If it's the go/no-go decision, that's /sales-idea-validation (a score is not demand) — route in Step 2.
3. Solo or team? Inodash is workspace/collaboration-first; if they're a solo founder wanting a one-shot report, note the free tier is very thin (see Step 4) and cover cheaper single-shot peers.

Skip-ahead: if the user wants the validate-before-building method or to compare validators across the market, route to /sales-idea-validation immediately.

Step 2 — Route or answer directly

| If the user's question is about… | Route to | |---|---| | The validate-before-building method, or the go/no-go decision itself | /sales-idea-validation {question} | | Comparing Inodash against other validators (Validator AI, IdeaCheck, WorthBuild, VenturusAI…) | /sales-idea-validation {question} | | Building the smoke-test / fake-door landing page to test real demand | /sales-funnel {question} | | Growing a pre-launch waitlist / capturing real demand | /sales-audience-growth {question} | | Turning the report's market/audience sections into a real content program | /sales-content {question} |

When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"

Otherwise, answer Inodash-specific questions using Step 3.

Step 3 — Inodash platform reference

Read references/platform-guide.md for the full reference — the module inventory (validator report anatomy, Persona Maker, Idea Generator, Competitor Analyzer, Financial Forecast Builder, Deck Evaluators, Smart Boards, RAG training), the AI-token-per-project metering and the four tiers (Free/Starter/ Business/Enterprise) with their workspace/project/token limits and plan gates (dashboard, data export, RAG), why the free tier is effectively a demo, why an AI score reads directional, and the no-public-API automation reality.

Answer using only the relevant section — don't dump the full reference.

Step 4 — Actionable guidance

• Treat every score and number as a directional gut check, not demand. The validator report — the market analysis, revenue models, competitor set, and any score — is an LLM opinion generated from a short description; the market-size and financial-forecast figures are AI estimates, not measured demand. Tell the user to keep the structured outputs (competitor map, target audience, revenue models, the "Critical Investor Questions") to sharpen the pitch, and take the go/no-go from real behavior — a smoke test or pre-sale — via /sales-idea-validation, not from the report.
• Frame it as a team workspace + tool suite, not a one-shot report — and flag the stingy free tier. Inodash's edge over solo one-shot validators is team collaboration, multiple bundled tools (personas, competitor analysis, financial forecasts, deck evaluation), Smart Boards, and reusable RAG context on paid tiers. Its trade-off: the free tier is effectively a demo (best-effort at research: 1 workspace, 1 project, ~3 AI tokens total) — say so plainly. If the user is a solo founder who just wants one cheap report, point them (via /sales-idea-validation) to cheaper single-shot peers; if they're a team organizing validation across projects, Inodash fits.
• Explain the AI-token-per-project metering and what's plan-gated. Work is metered by AI tokens per project, and tokens reset/scale per project, not per account (best-effort: Free ~3 total, Starter ~50/project, Business ~100/project, Enterprise ~500/project). The insights dashboard, data export, and advanced data masking are Business+, and custom RAG model training is Enterprise-gated. Always flag pricing/token numbers as best-effort and tell the user to confirm current tiers on inodash.com — they move — and note yearly billing is marketed at ~50% off.
• A "bundled suite" is broad, not deep — judge each tool on its own. One platform doing six jobs (validate + personas + competitors + financials + decks + boards) rarely goes as deep as a specialist on any one. Treat the persona, competitor, and financial-forecast outputs as editable first drafts to verify, not finished analysis — especially the financial forecast (invented assumptions for an untested idea). Use the good-enough pieces to move fast; redo anything you'd stake a decision on.
• There's no public API — don't plan an integration around it. If asked to automate, batch, or pipe reports elsewhere, say plainly there's no documented public API, no webhooks, and no Zapier/Make/MCP. Data export exists only as a Business+ UI feature (in-app export), not a programmatic endpoint — the only way to get data out is from the browser. The thing worth automating is the real signal (landing-page conversions), not the generated report — route that to /sales-idea-validation and /sales-funnel.

If you discover a gotcha or tip not in references/learnings.md, append it there with today's date.

Gotchas

Best-effort from research (2026-07) — Inodash's pricing, AI-token limits, plan gates, and module set move; verify at inodash.com.

• The validator report is an AI opinion, not demand. A market analysis, revenue models, and any score generated from a short description validate nothing on their own — follow with a real-behavior test (smoke test / pre-sale).
• Free tier is effectively a demo. Best-effort: 1 workspace, 1 project, ~3 AI tokens total — enough to try one idea, not to run real work. Real use needs a paid tier; don't assume "free plan, full access."
• Metered by AI tokens per project. Tokens scale by tier per project (Free ~3 total → Enterprise ~500/project) — running the validator, personas, forecasts, etc. all spend tokens; budget accordingly.
• Dashboard, data export, and RAG are plan-gated. The insights dashboard + data export are Business+; custom RAG model training is Enterprise. The free/Starter tiers can't export or train on your data.
• Financial forecasts and market sizes are AI estimates. The Financial Forecast Builder invents assumptions for an untested idea — verify every figure against primary sources before quoting it.
• Bundled breadth ≠ depth. Six tools in one workspace is convenient, but each is a broad first draft; a specialist tool will go deeper on personas, competitor analysis, or financials.
• No public API, no webhooks, no Zapier/Make/MCP. It's a UI tool; export is a Business+ in-app feature, not a programmatic path — there's no supported way to script or batch.
• Enterprise-clientele framing, but genuinely self-serve at the bottom. Marketing highlights large innovation-team clients; the free/Starter tiers are still self-serve for solo founders — weigh the enterprise positioning against your actual use.

Related skills

• /sales-idea-validation — The tool-agnostic validate-before-building method + the full validator landscape (use this to actually decide build-or-not; a score is not demand)
• /sales-venturusai — VenturusAI platform help (a comparable framework-driven validator + business-plan/persona/forecast bundle; contrast its SWOT/PESTEL framing against Inodash's team-workspace + Smart Boards approach)
• /sales-founderpal — FounderPal platform help (a solopreneur marketing suite with a free idea validator; the solo-tool counterpart to Inodash's team workspace)
• /sales-funnel — Build the smoke-test / fake-door landing page the real demand test runs on
• /sales-audience-growth — Grow a pre-launch waitlist and capture real demand
• /sales-content — Turn the report's market/audience sections into a real content/ad program
• /sales-do — Not sure which skill to use? The router matches any sales objective to the right skill. Install: npx skills add sales-skills/sales --skill sales-do -a claude-code

Examples

Example 1: "Inodash validated my idea and gave a big market size — should I build?"

User says: "I ran my idea through Inodash's free validator, it looks positive and shows a large market. Good to go?" Skill does: Reframes the report — market analysis, revenue models, competitor set, any score — as an LLM opinion generated from a short description; the market size and any financial numbers are AI estimates, not demand. Tells the user to keep the structured parts ("Critical Investor Questions", competitor map, target audience) to sharpen the pitch, then route the real go/no-go to /sales-idea-validation — a smoke test or pre-sale where a stranger takes an action — rather than trusting the report. Result: The founder earns a real demand signal before building, using Inodash's structure, not its verdict.

Example 2: How does the free tier / token pricing actually work?

User says: "Inodash says it's free — how much can I actually do, and what do the paid plans add?" Skill does: Explains work is metered by AI tokens per project and that the free tier is effectively a demo (best-effort ~1 workspace / 1 project / ~3 tokens). Paid tiers scale tokens per project (Starter ~50, Business ~100, Enterprise ~500) and gate features: dashboard + data export are Business+, custom RAG training is Enterprise. Flags all numbers as best-effort to confirm on inodash.com and notes yearly billing is ~50% off. Adds that a solo founder wanting one cheap report may prefer a single-shot peer — pointing to /sales-idea-validation. Result: The user sizes the right tier and knows what "free" really covers.

Example 3: Can I export or automate Inodash reports via API? (developer/automation)

User says: "I want to run ideas through Inodash and pull the reports into my own dashboard via API or Zapier." Skill does: States plainly there's no documented public API, no webhooks, and no Zapier/Make/MCP — data export exists only as a Business+ in-app UI feature, not a programmatic endpoint, so the only way to get data out is from the browser. Suggests a tool built for programmatic validation if a pipeline is required, and notes the thing worth automating is a real demand signal (landing-page conversions), not a generated report — pointing to /sales-idea-validation and /sales-funnel. Result: The user avoids building on a non-existent API and picks a workable path.

Troubleshooting

The report looks positive but I'm not sure it means anything

Symptom: A glowing validator report (big market, encouraging revenue models) the founder senses is too easy. Cause: The report is a short-prompt LLM output — it pattern-matches to plausible encouragement and can invent supporting "facts" (market size, demand, financials). Solution: Stop treating the report as the decision. Keep the structured outputs (competitor map, target audience, "Critical Investor Questions", risks) and run a real demand test — smoke test or pre-sale — via /sales-idea-validation. Escalate commitment to a card/pre-order for willingness-to-pay signal.

I ran out of AI tokens / hit a project limit

Symptom: The free plan won't let me run more, or a tool says I'm out of tokens. Cause: Inodash meters by AI tokens per project, and the free tier is ~3 tokens total with 1 workspace / 1 project — it's a demo allotment. Solution: Upgrade to a tier sized to your usage (Starter ~50/project, Business ~100, Enterprise ~500), or finalize each idea's framing before spending tokens so you don't burn them on thin input. Confirm current token limits on inodash.com — they're best-effort here.

I want an API, data export, or a way to automate

Symptom: Want to script Inodash, pull reports into another system, or trigger it from a workflow. Cause: Inodash has no documented public API, webhooks, or iPaaS connectors; data export is a Business+ UI feature, not an endpoint. Solution: There's no supported programmatic path — export from the browser on a Business+ plan, or use a tool intended for programmatic use if you need a pipeline. Automate a real demand signal (landing-page analytics) instead. See /sales-idea-validation.