Documentation Index
Fetch the complete documentation index at: https://help.1nspect.app/llms.txt
Use this file to discover all available pages before exploring further.
IT Tokens — The AI Currency
IT (Inspection Tokens) are the metered currency for every AI operation on 1nspecT. Every AI call — narrative generation, vision analysis, schema extraction, polish, SPO synthesis — deducts IT from your tenant’s balance. When the balance hits zero, AI calls are blocked until you top up; non-AI operations keep working.
This article is the canonical reference: what costs what, where the balance lives, how to top up, and how to economize.
Why a metered currency?
AI operations call cloud LLMs (Google Gemini, Vertex AI) that cost real money per request. The IT token system means:
- You pay only for what you use — no flat AI subscription baked into the platform price
- You can plan AI spend — a typical inspection uses 30–80 IT depending on Vision usage
- High-cost operations are gated — Vision (8 IT) and Voice DNA (50 IT) pre-flight-check the balance
- Free operations stay free — FREE Library chips, repair-request generation, and several utilities cost 0 IT
The bucket is tenant-wide, not per-user. All inspectors share the balance.
Where the balance lives
The IT balance is visible only on the web admin — there is intentionally no balance display on the mobile app. To check:
- Sign in to the web admin as Owner
- Navigate to Settings → Subscription & Tokens
- The current balance and recent usage history appear
Mobile inspectors see token data only via the Insufficient IT Tokens error when a call is blocked.
Complete operation cost reference
The authoritative table.
Inspector-facing operations (mobile)
| Operation | Codename | Cost | Where |
|---|
| AI Generate (text-only) | generate-narrative | 2 IT | Capture Screen → ✦ AI Generate (Vision OFF) |
| Vision Analysis | vision-analyze | 8 IT | Capture Screen → ✦ AI Generate (Vision ON) |
| Library Search 🪄 | semantic-search | 1 IT | Capture Screen → 🪄 button |
| FREE Library chips | (local) | 0 IT | Capture Screen — automatic on caption typing |
| Save to Narrative Library | provision-library-entry | 1 IT | Capture Screen → Save to Library |
| System Info Tag (photo) | extract-metadata-photo | 3 IT | Capture Screen → ℹ️ Sys Info (with label) |
| System Info Tag (text) | extract-metadata-text | 1 IT | Capture Screen → ℹ️ Sys Info (text-only) |
Admin-facing operations (web)
| Operation | Codename | Cost | Where |
|---|
| AI Draft (per finding) | generate-narrative | 2 IT | Report Workspace → AI Draft tab |
| Polish Narrative | polish-narrative | 2 IT | Inspection Reviewer → narrative editor → Polish |
| Polish Report | polish-report | 10 IT | Inspection Reviewer → Polish Report action |
| System Performance Opinion | generate-spo | 10 IT | Ratings Screen / Reviewer → SPO card |
| Bundle Findings | bundle-findings | 2 IT | Reviewer — automatic at finding consolidation |
| Voice DNA — extract persona | extract-persona | 50 IT | Onboarding — one-time per inspector |
| Schema extraction (OCR) | extract-structured-ocr | 3 IT | Templates → PDF upload → AI extract |
Free operations (0 IT)
| Operation | Codename |
|---|
| Repair Request generation | repair-request |
| Property Baseline | property-baseline |
| PDF schema extraction (no OCR) | extract-pdf-schema |
| Structured text extraction | extract-structured-text |
Typical inspection cost
| Activity | Per-instance | Typical count | Total IT |
|---|
| Photos + ratings (no AI) | 0 | 30–80 findings | 0 |
| FREE Library chip selections | 0 | 15–30 selections | 0 |
| AI Generate (text-only) | 2 | 5–15 findings | 10–30 |
| Vision Analysis | 8 | 0–5 findings (selective) | 0–40 |
| Save to Library | 1 | 2–5 saves | 2–5 |
| Sys Info on equipment | 3 | 2–4 labels | 6–12 |
| Operator: AI Draft | 2 | 2–8 findings | 4–16 |
| Operator: SPO per system | 10 | 5 systems | 50 |
| Total typical | | | 80–155 IT |
How balance updates work
- Pre-flight check (Vision): before sending the photo to the model, the backend verifies balance ≥ 8 IT
- Deduct on success: most operations deduct after a successful AI call. Failed calls don’t deduct.
- Atomic: the deduction is part of the same Firestore transaction as the result
- Fire-and-forget for fast operations: some 1-IT operations deduct asynchronously to avoid latency
Topping up
- Owner signs into web admin
- Settings → Subscription & Tokens
- Purchase Top-Up — choose a pack size
- Stripe checkout — pay with the platform’s payment processor
- Balance updates within seconds
Pack sizes typically range from small (~500 IT) to bulk (~25,000 IT). Larger packs have a lower per-IT cost.
Subscription vs top-ups
| Mode | How it works | When |
|---|
| Subscription bundle | Your monthly subscription includes a baseline IT allotment | High-volume tenants (50+ inspections/month) |
| Top-up packs | Bought ad-hoc | Low-volume or seasonal tenants |
Economy tips
- Build the narrative library. Every saved narrative becomes a future FREE chip. After 3–6 months of library investment, FREE chips cover 60–80% of common findings.
- Use Vision selectively. Save it for findings where the photo really tells the story.
- Polish only once. Each Polish Narrative call costs 2 IT — don’t run repeatedly.
- SPO generation late. Wait until all findings are in before generating SPOs.
- Sys Info only when age matters. For obviously-new equipment, skip the AI call.
When balance is exhausted
| Operation tried | What happens |
|---|
| Vision Analysis | Blocked with the “Insufficient IT Tokens” alert |
| AI Generate | Falls back to a template CAR narrative (free) |
| Library Search | Error toast; FREE chips continue working |
| Sys Info | Error toast; informational fields can be filled manually |
Audit trail
Every IT deduction is logged on aiUsage for the inspection. Review per-inspection AI spend in Inspection Details → History. Cross-inspection AI spend lives in Reports → Inspector Productivity.
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