Bring Your Own AI · Optional
Use models for assistance, not commercial authority.
Connect a customer-approved provider to summarize, classify, draft, and detect risk while the underlying RFQ, product, cost, quote, and payment records remain deterministic.
Private Implementation Program · Selected engagements
Provider architecture
One governed boundary for cloud, private, and local models.
Provider availability is an architectural target, not a claim that every connector has already passed production validation.
OpenAIAnthropicGoogle GeminiAzure OpenAIDeepSeekMistralOpenRouterAWS Bedrocklocal OllamavLLMprivate OpenAI-compatible endpoints
Candidate capabilities
Reduce review effort where judgment still belongs to people.
Every capability is enabled separately with a documented input policy, output status, and approval path.
lead classification
urgency detection
duplicate suggestions
product and MPN extraction
supplier suggestions
missing-data detection
quote drafting
customer-response drafting
next-action suggestions
follow-up reminders
risk and margin warnings
lost-reason classification
pipeline summaries
multilingual correspondence
management briefings
Hard controls
Safe defaults are part of the commercial design.
- 01The core workflow operates fully without AI.
- 02AI is never the system of record.
- 03Exact MPN identity remains deterministic.
- 04Pricing, supplier, compliance, quote terms, and outbound communication require controlled approval.
- 05Customer data is sent only after explicit provider and data-policy configuration.
- 06Provider keys stay encrypted, isolated, and absent from browser bundles and logs.
Revenue operations assessment
Define the data boundary before choosing a model.
Document the current RFQ path, identify where demand disappears, and define a controlled implementation with measurable acceptance criteria.