Tradeics AI support concentrates where B2B trade generates high decision load. Plan integrations around these capability areas.
Sourcing & procurement
- Ranking or shortlisting suppliers based on category fit, history, and network signals
- Helping teams draft or refine RFX content and evaluation criteria
- Highlighting spend anomalies once invoice and PO history are connected
Integration prep: sync rich supplier attributes and historical PO outcomes; keep category mappings current.
Sales & marketplace
- Prioritizing inbound RFQs / public projects for seller response teams
- Assisting catalog enrichment (attributes, categorization) for better discovery
- Surfacing buyers or opportunities aligned to a supplier’s strengths
Integration prep: keep catalog completeness high; push response SLAs and win/loss outcomes back when available.
Operations & risk
- Flagging unusual payment or wallet patterns for review (with Finance)
- Assisting contract clause review workflows before signature
- Summarizing status across multi-party transactions for operators
Integration prep: expose clear state machines and audit trails in your middleware so AI and humans share one timeline.
Guardrails for your build
- Log who accepted or overrode an AI suggestion.
- Do not auto-post ERP journals from unverified AI output.
- Expect localized and industry-specific behavior — do not assume one global ranking model for every market.
Calling models from your stack
When you need your own prompts (not only in-product assists), use the Tradeics LLM proxy:
curl https://llm.tradeics.example/v1/chat/completions \
-H "Authorization: Bearer $TRADEICS_LLM_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "<model_id>",
"messages": [
{"role": "system", "content": "You assist Tradeics procurement users."},
{"role": "user", "content": "Propose evaluation criteria for this RFX."}
]
}'Full examples and OpenAI SDK setup: Call the LLM.