iMario Platform Help
iMario (imario.ai) is a synthetic-research and audience-intelligence platform that calls itself
"the human layer of AI." Instead of a one-shot study tool, its unit is a reusable Synthetic
Individual — a constrained cognitive model (not plain LLM roleplay) with a Deep Identity
narrative, Expert Reflection panels (demographer / psychologist / economist), Knowledge
Boundaries, and a three-layer memory (working / episodic / semantic, with Ebbinghaus decay) that
persists across sessions. You build a cohort three ways — a plain-English brief, a LinkedIn
profile, or a personality assessment ("synthetic twin") — and run tasks against them on a visual
Canvas (a node editor that replaced the old funnel flow), grounded in your own files via a
Knowledge Base (RAG). The same individual can be reused across six jobs: Discover (research),
Validate (concept/product), Launch (sales outreach & content testing), Optimize (CX/journey), Scale
(sales/service enablement), and Build (AI-agent personality via API).
Its signal is directional, not demand: synthetic individuals model existing/public/training data,
so they skew agreeable, generic, and Western-biased and can't surface a genuinely new unmet need.
The 90%+ "human parity" figure is a vendor claim — treat any synthetic result as a hypothesis to
disconfirm with real behavior, not a green light.
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated platform knowledge.
Ask only what you can't infer:
- What do you want from iMario?
- A) Build a Synthetic Individual / cohort — pick the input (brief / LinkedIn / personality twin)
- B) Set up a Canvas task — research, concept test, content test, journey, or sales rehearsal
- C) Ground it in your own data (Knowledge Base / RAG upload) for specific answers
- D) Interpret a synthetic report, distribution, or the 90%-parity claim you already have
- E) Reuse one persona across multiple jobs, or automate via the Pro-gated API / production agent
- F) Decide whether to trust it — is this a valid stand-in for real research? - What's the question and who's the audience? A sharp brief + Knowledge Base yields usable signal;
a vague one yields generic filler.
Skip-ahead: if the user wants to compare synthetic-research/persona/idea tools across the market, or
the validate-before-building method, that's a /sales-idea-validation question — route in Step 2.
Step 2 — Route or answer directly
| If the user's question is about… | Route to |
|---|---|
| Comparing synthetic-research/persona/idea tools, or the validate-before-building method | /sales-idea-validation {question} |
| The pure-play synthetic study tool with a documented public REST API (Bearer, SDKs, SSE) | /sales-syntheticusers {question} |
| A data-grounded persona you chat with built from your GA4/CRM/social | /sales-delve or /sales-marketing-mary {question} |
| Running a real demand test (smoke-test page, waitlist, pre-sale) after synthetic signal | /sales-idea-validation or /sales-funnel {question} |
| Analyzing real-customer NPS/CSAT/VoC feedback (post-launch) | /sales-customer-feedback {question} |
When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"
Otherwise, answer iMario-specific questions using Step 3.
Step 3 — iMario platform reference
Read references/platform-guide.md for the full reference — the Synthetic Individual model
(Deep Identity, Expert Reflection, Knowledge Boundaries, three-layer memory), the three cohort inputs,
the Canvas node editor and six jobs, Knowledge Base / RAG grounding, the API/webhook/UI-only tag on each
module, best-effort credit-based pricing and the Pro API gate, the data model (Synthetic Individual /
Canvas / Task / Cohort JSON shapes), and quick-start recipes.
For the API surface (Pro-gated, no public developer docs at research time), read
references/imario-api-reference.md.
Answer using only the relevant section — don't dump the full reference.
Step 4 — Actionable guidance
You no longer need the platform guide — focus on the user's specific situation.
- A synthetic "yes" is not demand — say so every time. Whatever the user asks, make explicit that
Synthetic Individuals model existing/public/training data, so they run agreeable, generic, and
Western-biased and can be confidently wrong. Frame every result as a hypothesis to disconfirm
with a real behavior test (smoke-test click, reply, pre-sale) — keep the objections, angles, and
language it surfaces (its real value), take the go/no-go from real strangers, and route the real test
to/sales-idea-validation. - Treat the "90%+ human parity" figure as a vendor claim, not proof. When the user cites it, note it
is self-reported (the site itself pegs quantitative agreement near ~89% and admits real survey retest
agreement is only ~93%), varies sharply by question type (weak on behavioral/emotional/cultural), and
is not a validity verdict — don't let it substitute for a real behavior test. - Play iMario's actual edge: reuse + memory. Its differentiator over one-shot tools is that the
same Synthetic Individual persists across sessions and jobs — build a cohort once, then reuse it
across Discover → Validate → Launch → rehearsal on the Canvas. Point the user here when they want
continuity, not a fresh throwaway panel each time. - Ground it in a Knowledge Base and sharpen the input — output tracks input. A thin brief yields
generic filler ("garbage in, garbage out"). Tell the user to upload real data (interviews,
tickets, segment defs) to the Knowledge Base and write a specific brief, or anchor to a LinkedIn
profile / personality assessment for a sharper individual. Note Knowledge Base file limits are
plan-gated (Free: 1 KB / 1 file). - Present pricing and the API gate as best-effort. It's credit-based (Free 500 one-time credits;
Starter/Pro monthly credits; PAYG packs) and API access is Pro-tier-and-above with no public
developer docs found — say figures are best-effort and confirm at imario.ai/pricing before relying
on them; for API specifics, tell the user to request docs from iMario. - For the "Build" / production-agent use case, set expectations. The API pipes a Synthetic
Individual's personality into a production agent, but it's Pro-gated and undocumented publicly —
scope any integration as "confirm auth + endpoints with iMario first," and don't invent endpoint
shapes. If the user needs a documented public API today, point them to/sales-syntheticusers
as the alternative.
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) — credit pricing, plan gates, the Pro API surface, and the
"parity" figures move; verify at imario.ai and imario.ai/pricing.
- Sycophancy / agreeableness bias. Synthetic Individuals tend to please — shallow, overly
favorable feedback that can approve a concept real users would reject. Never read a positive synthetic
reaction as validation. - It can't surface a NEW unmet need. It models existing/public data, so it's strongest at
pre-testing a hypothesis you already have and weakest at discovery. Don't use it to "find the problem." - The 90%+ parity claim is vendor-reported and question-dependent. It's strongest on structured
attitudinal questions and weak on behavioral, emotional, and culturally specific ones. Don't treat it
as a validity guarantee. - Western/geographic and identity bias. Outputs skew toward Western, majority perspectives and can
flatten identity groups — be cautious generalizing across markets/segments. - Garbage in, garbage out. A thin brief or empty Knowledge Base yields generic filler. Ground the
cohort and write a specific brief before trusting any theme. - API is Pro-gated and undocumented publicly. API access unlocks only on Pro and above, and no
public developer docs were found — don't assume endpoints/auth; request docs from iMario and confirm
before building. Free tier is heavily limited (10 SIs/mo, 1 LinkedIn profile, view-only report).
Related skills
/sales-idea-validation— The tool-agnostic validate-before-building method + the full synthetic-research/persona/validator tool landscape (use this to actually decide build-or-not; a synthetic "yes" is not demand)/sales-syntheticusers— Synthetic Users platform help (the pure-play synthetic study tool — single-workflow AI-moderated interviews, but the cluster-rare one with a real documented public REST API [Bearer, Python/TS SDKs, SSE, PDF export]; iMario's closest peer, trading iMario's reusable-persona breadth for a documented API)/sales-delve— Delve AI platform help (data-grounded personas + Digital Twins + Synthetic Research built from your real GA4/CRM/social data — the persona-you-chat-with counterpart; paid, gated API)/sales-marketing-mary— Marketing Mary platform help (interactive buyer personas you converse with, grounded in real CRM/GA4 data; UI-only, no public API)/sales-customer-feedback— Real-customer NPS/CSAT/VoC strategy across tools (use once you have live customers; synthetic research is pre-launch only)/sales-funnel— Build the smoke-test / fake-door landing page that turns a synthetic hypothesis into a real demand test/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: "The synthetic panel loved my concept — should I build it?"
User says: "I ran a concept test on iMario and 9 of 10 Synthetic Individuals said they'd buy. It says 90%+ human parity — green light?"
Skill does: Explains Synthetic Individuals model existing/training data and skew agreeable, so a
near-unanimous "yes" is a directional signal, not demand, and the 90%+ parity is a vendor claim
that's weakest exactly on behavioral/purchase questions. Tells the user to mine the responses for
objections and language (the real value) and take the go/no-go from a real behavior test — a
smoke-test click or pre-sale — routed via /sales-idea-validation.
Result: The founder keeps the angles, runs a real fake-door test before writing code.
Example 2: Reusing one Synthetic Individual across research and sales rehearsal (references/platform-guide.md)
User says: "Can I build a buyer persona once and reuse it for both discovery interviews and to rehearse my pitch?"
Skill does: Says yes — iMario's edge is that a Synthetic Individual persists across sessions and
jobs via its three-layer memory, so you build the cohort once (brief / LinkedIn / personality twin),
ground it in a Knowledge Base, and reuse it across Discover (research) and Launch/Scale (sales
outreach & rehearsal) on the Canvas. Notes output tracks input — sharpen the brief and upload real
data — and that each result is still a hypothesis to test with real buyers.
Result: One grounded persona reused across jobs instead of a throwaway panel per task.
Example 3: Piping a Synthetic Individual into a production AI agent via the API (developer/automation)
User says: "I want to give my support-bot a real buyer's personality using iMario's API. How do I wire it in?"
Skill does: Explains the Build use case — the API embeds a Synthetic Individual's personality
into a production agent — but flags that API access is Pro-tier-and-above and no public developer
docs were found at research time, so it won't invent endpoints or auth. Advises scoping the
integration as "request API docs from iMario, confirm auth + endpoints, then build," and points to
references/imario-api-reference.md for what is known and its gaps.
Result: The user upgrades to Pro, gets the real docs, and integrates without relying on guessed shapes.
Troubleshooting
"The Synthetic Individuals agreed with everything — is that real?"
Symptom: Tasks return uniformly positive, agreeable feedback that feels too good.
Cause: LLM-based individuals exhibit sycophancy — they model plausible agreement and skew favorable.
Solution: Discard the "verdict," keep the objections and language surfaced, and validate the
concept with real behavior (smoke test, pre-sale). Ground the cohort in a Knowledge Base and sharpen
the brief to reduce generic agreement. Cross-check via /sales-idea-validation.
Results feel generic / could describe anyone
Symptom: Themes are vague and not specific to your product or buyer.
Cause: Thin brief and no Knowledge Base grounding — "garbage in, garbage out."
Solution: Write a specific brief and upload your own data (interviews, tickets, segment defs)
to the Knowledge Base, or anchor the cohort to a LinkedIn profile / personality assessment. Note
Knowledge Base file limits are plan-gated (Free: 1 KB, 1 file). Re-run with a focused task.
"I can't find the API — how do I automate iMario?"
Symptom: You want to pull results or embed a persona but there's no API key or docs in the UI.
Cause: API access is gated to Pro and above, and iMario publishes no public developer docs.
Solution: Upgrade to Pro to unlock API access, then request the developer docs from iMario
(support/sales) — don't assume endpoints or auth from other tools. See references/imario-api-reference.md
for the known surface and its gaps; for a tool with a documented public REST API today, consider
/sales-syntheticusers.
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