Three-tier system topology
From raw marketplace event to verified execution.
Every layer has isolated responsibilities, cryptographic validation, and an observable execution trace. Human-in-the-loop approval gates sit directly between LLM reasoning and marketplace dispatch.
Ingestion & Event Gateway
Marketplace Webhooks (Shopee/TikTok/Lazada) · REST APIs · Factory BOM PDFs · High-res Product Photos · Supplier CSVs
Idempotency key registry
Kafka / Redis event streaming
normalized events
Multi-Agent Reasoning Core Claude 5.5 Engine
Tiered agent orchestration: Claude 5.5 Sonnet (Vision, OCR & Multilingual Localization) + Claude 5.5 Haiku (Sentiment & Flash-Sale Velocity) with Anthropic Prompt Caching
Multimodal vision extraction
Strict JSON schema tool calling
validated task payloads
Dispatch & Synchronization Bus
Deterministic Redis queues · Worker pool execution · Rate-limit aware marketplace adapters · Margin-floor validators
Two-way catalog mutations
Dead-letter queue & exponential retries
Anthropic SDK Integration
How CenSeller harnesses the Claude 5.5 API.
We leverage Anthropic's prompt caching to store massive marketplace taxonomies (50,000+ category attribute nodes) directly in context, reducing latency by 82% and token overhead by 90%.
import anthropic from censeller.guardrails import verify_margin_floor, validate_shopee_schema client = anthropic.Anthropic() # Cached system prompt holding the complete Southeast Asian marketplace taxonomy response = client.messages.create( model="claude-5.5-sonnet", max_tokens=4096, temperature=0.1, system=[ {"type": "text", "text": "You are CenSeller's Omnichannel Catalog Reasoning Agent."}, { "type": "text", "text": SHOPEE_TIKTOK_TAXONOMY_SCHEMA, # ~120k tokens cached "cache_control": {"type": "ephemeral"} } ], tools=[GENERATE_STOREFRONT_LISTING_TOOL, MARGIN_FLOOR_PROTECTION_TOOL], messages=[ { "role": "user", "content": [ {"type": "image", "source": {"type": "base64", "media_type": "image/jpeg", "data": factory_b64}}, {"type": "text", "text": f"Normalize SKU {master_sku} for Shopee VN and TikTok Shop SEA with min 45% margin floor."} ] } ] )
Multimodal Vision
Claude 5.5 Sonnet Vision
Directly ingests factory sample photos, supplier spec sheets, and competitor packaging images to extract precise fabric compositions, certifications, and dimensions without manual data entry.
- Factory BOM table and barcode parsing
- Attribute extraction from product photography
- Automated compliance verification
Real-Time Routing
Claude 5.5 Haiku Engine
Performs sub-100ms competitor sentiment analysis and price-velocity calculations, streaming micro-adjustments to worker queues during high-traffic flash-sale campaigns.
- Sub-100ms inference response time
- Negative review flaw cluster classification
- High-frequency inventory buffer rebalancing
Efficiency & Scale
Anthropic Prompt Caching
By caching platform taxonomy structures and localized search dictionaries in memory, CenSeller achieves sustained 50,000+ SKU reasoning capacity with 90% lower token cost.
- Up to 200k cached tokens per tenant
- Instant schema validation across channels
- Predictable enterprise cost predictability
Safety & Compliance
Deterministic Guardrails
Every tool call generated by Claude passes through deterministic Python validation: price changes cannot breach operator margin floors, and catalog dispatches require human sign-off.
- Cryptographic HMAC verification
- Hard code-level margin floor protection
- Audit trails replayable via OpenTelemetry
Deploy CenSeller into your commerce stack.
Connect your first Shopee, TikTok Shop, or Amazon storefront with our solution engineers.