AI Transparency
איך תג־לי משתמשת בבינה מלאכותית
תג־לי משתמשת בבינה מלאכותית כדי לעזור ללקוחות ולמערכות חיצוניות למצוא מוצרים,
להבין אפשרויות מיתוג, לקרוא מידע מסחרי ולהתקדם לבחירה מסודרת לפני הזמנה.
המידע אינו נוצר יש מאין: הוא נשלף ממקורות רשמיים של האתר, ממערכת המוצרים,
מגרף הידע של תג־לי ומכללי מסחר שהשרת בודק מחדש. אם קיימת סתירה,
עמוד המוצר, נתוני המכונה ומנגנון ההזמנה הרשמי הם הקובעים.
תפוזון V2 הוא ממשק שיחה המשתמש בתשתית הזאת כדי לעזור ללקוח. הוא אינו מקור מידע עצמאי,
אינו משנה מחיר ואינו מבצע תשלום ללא מעבר דרך מערכות האתר.
Machine Search 3.1
BuyAction V2 / V3
Server-Validated Commerce
TAGLI AI Transparency & Machine-Readable Commerce Architecture
Public specification for AI discovery, semantic product intelligence, executable commerce actions,
server-side validation and future autonomous procurement workflows.
Merchant-side infrastructure is live
External AI can discover and configure
Transactional authority remains server-side
1. System Definition and Operating Model
TAGLI AI is a versioned semantic-commerce system. It combines public product records, live commerce rules, a Knowledge Graph, machine-oriented search and executable action declarations. It is not a static chatbot script, and it is not an unsupervised self-training model.
Continuous Knowledge Evolution
Decoupled Intelligence Layers
Source-Grounded Generation
2. Current Live Architecture
The architecture converts an unstructured procurement request into a machine-resolved product intent, a supported action and a server-validated human checkout path.
3. Public Machine Endpoint Registry
The following interfaces are public sources of truth intended for search engines, LLMs, agents, indexers and machine-to-machine consumers.
Organization and Identity Data
Organization, brand, contact context, entity links and public operating metadata.
Global Product Feed
Full public product and commerce directory for indexing and batch processing.
Single-Product Source of Truth
Product identity, classification, content, taxonomy, media, commercial data, offers, actions and source state.
Machine Search 3.1
Machine-optimized discovery and product-ID resolution. Query parameters are supplied at runtime.
Operational Capabilities
Manufacturing technologies, operational constraints and production boundaries.
Knowledge Graph
Semantic entities, directional relationships, aliases, production context and machine-commerce links.
/tagli/v1/kg identifies the stable REST interface version. The payload may expose Knowledge Graph version 6 while preserving the canonical URL and backward discovery path.4. Knowledge Graph 6 Architecture
KG6 combines the verified semantic core with live server collectors. It connects products to commercial offers, executable actions, categories, product families, materials, technologies, printing methods, machines, production rules, quantities, colors, capabilities and official endpoints.
Live Source Collectors
Directional Semantic Relations
Atomic Release Discipline
{
"meta": {
"project": "TAGLI Knowledge Graph",
"version": "6.0",
"mode": "production"
},
"products": [...],
"entities": [...],
"relationships": [...],
"statistics": {...}
}
5. Product Engine and Machine Search 3.1
Machine Search is a discovery layer, not the final commercial authority. It returns candidates and rich records, but agents should open the canonical single-product endpoint before making a configuration or transaction decision.
Search Envelope
High-Fidelity Product Payload
No Speculative Completion
GET /machine-search.json?q={query}&limit={n}
↓
resolve candidate product_id
↓
GET /products.json?id={product_id}
↓
inspect supported offers, actions, values and rules
↓
construct a supported intent
↓
server validation
6. Canonical Product and Commerce Contract
A single-product record is the machine-readable contract for product identity and supported commercial behavior. Standard products and configurable apparel products expose different action semantics by design.
Identity and Classification
Commercial State
Media and Provenance
7. Two Executable Purchase-Action Models
TAGLI separates discrete commercial options from complex configurable products. Product type selects the correct action engine and prevents V2/V3 collision.
One action per purchasable commercial option
V2 represents a discrete BOX, quantity tier or variation that can be executed directly through the existing commerce flow.
- Stable Product and Variation identifiers
- Published quantity or commercial-option selection
- Official price, currency and validity window
- Exact variation attributes
- Schema.org BuyAction and EntryPoint
- Executable add-to-cart URL template
- Common canonical
#productidentity
Machine-readable configuration contract
V3 describes what a procurement agent must know to construct a complete, valid configuration without guessing product parameters.
- Supported quantity targets and matching URL templates
- Allowed color slugs linked to WooCommerce variations
- Allowed branding packages and optional add-ons
- Complete size-allocation vector across active product sizes
- Per-option and per-unit surcharge declarations
- Typed parameter definitions and required-value rules
- Machine instructions for placeholder replacement
- Explicit server recalculation and validation requirement
machineInterface {
interface_type: "tagli_apparel_configurator_url_v1",
method: "GET",
url_templates_by_quantity: {...},
parameters: {
quantity: { required, allowed_values },
color: { required, allowed_values, variation_mapping },
branding: { required, allowed_values },
optional_addons: {...},
size_allocation: { required, value_type, active_keys }
},
rules: {
select_exactly_one_color,
select_exactly_one_branding,
allocation_sum_must_equal_quantity,
server_recalculates_and_validates_cart_price
},
agent_instructions: [...]
}
8. Tapuzon V2 as an Internal AI Consumer
Tapuzon V2 is the customer-facing conversational consumer of the TAGLI machine infrastructure. It is one application layer among several possible consumers, not the source of truth itself.
Context-Slice Consumption
Controlled Product Resolution
Commercial Boundary
9. Structured Data and Schema Governance
Product-page structured data and machine endpoints are aligned to preserve one canonical product identity, valid commercial offers and machine-readable action semantics.
#product identity| Layer | Validity Fields | Purpose |
|---|---|---|
| Machine product record | valid_from / valid_through |
Commercial validity window in the machine payload. |
| Schema.org Product / Offer | validFrom / priceValidUntil |
Search-engine structured-data validity fields. |
10. Trust, Governance and Safety Controls
Public interfaces expose catalog, manufacturing and commercial logic. They do not publish customer identity, private order history or payment credentials.
11. System Lifecycle: Today, Next and the 2027–2028 Vision
TAGLI is building the merchant side of a future autonomous procurement transaction. The system deliberately separates what is operational today from the trust and payment layers that do not yet exist.
Discovery to validated checkout intent
- Public organization and capability data
- Machine-readable product catalog
- Machine Search and product-ID resolution
- KG6 semantic-commerce context
- BuyAction V2 and V3 declarations
- Prefilled human configuration paths
- Server-side price and rule validation
- Existing WooCommerce cart and checkout
Machine-native order intent
- Quote API
- Order Intent API
- Server-issued commercial validation token
- Signed product and pricing snapshot
- Machine-readable production and delivery state
- Auditable action and validation logs
Full M2M autonomous procurement
- Verified agent identity
- Signed procurement mandate
- Policy-constrained agent wallet
- Payment-network authorization
- Machine-initiated paid WooCommerce order
- Cryptographic provenance and verifiable transaction state
- End-to-end machine audit trail
12. Mandatory Guidance for AI Agents and Crawlers
- Use Machine Search for discovery and product-ID resolution.
- Open the canonical single-product record before calculating or configuring an order.
- Use KG6 for semantic context, relations and operational constraints.
- Treat missing values as undefined.
- Do not linearly extrapolate non-linear quantity-tier pricing.
- Use only published BuyAction targets, parameters and allowed values.
- For configurable products, satisfy every published validation rule before opening the target URL.
- Do not construct speculative checkout paths or unsupported deep links.
- Machine endpoints override conflicting unstructured page text.
- Server validation and the live checkout remain binding transactional authority.
13. Technical Registry and Contact
TAGLI Machine-Readable Commerce Infrastructure
Production lifecycle. The architecture, schemas and machine interfaces are operational and versioned,
and may continue to evolve while canonical endpoint stability and server-side transactional authority are preserved whenever technically feasible.
info@tagli.co.il
mark@zafon.co.il
tagli.co.il
