Agentic CPQ
Procurement agent returned a quote. Product ops found three constraint violations the assistant invented. Mercura agent endpoints apply your rules before any price leaves the system.
The challenge
Procurement agent returned a quote. Product ops found three constraint violations the assistant invented.
A maker of UV curing and LED drying systems for label and flexographic printing started receiving quote requests from enterprise procurement platforms where buyer-side agents assemble lamp module kits on behalf of plant managers. Sales pasted one agent output into Mercura admin and found incompatible power supply wattage, a reflector option blocked for the chosen arc length, and a price below the approved floor for that account.
The prototype chat layer called a generic catalog API and guessed compatible modules. Agents could not wait for a human sales engineer. Deals routed to vendors whose bots returned instant numbers, even when those numbers were wrong. Product and compliance teams refused to connect unconstrained models directly to list price tables.
MACH-aligned CPQ passes enterprise architecture questionnaires. API-first CPQ documents REST parity between admin and integration code. Headless CPQ runs engine logic behind your own UI. Composable CPQ swaps layers on separate timelines. The CPQ SDK removes auth boilerplate. Agentic CPQ is different: Mercura exposes configure, price, and quote operations on agent-oriented endpoints that validate every selection through the same constraint and pricing rules as human configurators, enforce brand guardrails, route approvals, and log each request with buyer and agent attribution.
Inquiry to config to price to approval to order should not treat procurement agents as a special case that bypasses the rules your reps already operate under.
How it works
How Mercura agentic CPQ works
Procurement platforms, copilots, or internal bots call Mercura agent endpoints with typed or natural-language quote requests. Each proposed configuration runs through the rules engine: option filtering, dependency checks, and margin validation match what the admin UI enforces. Customer-specific rates and discount caps apply before a quote returns. Quotes above threshold enter the same approval workflow as rep-submitted lines. Responses include only catalog-backed options and prices, not model guesses. OpenAPI and MCP integration paths document how agents authenticate and which scopes they may use. Your team defines allowlists, approval thresholds, and logging retention. Mercura does not replace agent orchestration design or procurement platform contracts.
What's included
What agentic CPQ covers
- Agent endpoints for configure, price, and quote with schema-valid responses
- Same constraint engine for agent and human configuration flows
- Discount caps, margin floors, and product allowlists for agent clients
- Approval routing when agent quotes exceed policy thresholds
- Audit log with agent identity, buyer account, and rule outcomes
- Customer-specific pricing applied before quote return
- OpenAPI and MCP paths for agent platform integration
- Invalid configurations rejected with explicit constraint messages
The difference
Agent quoting before and after governed CPQ endpoints
- Agents return incompatible modules and off-policy prices
- No shared rules surface between bots and sales configurators
- Compliance cannot trace which agent sent which quote
- Human engineers rework every agent request manually
- Buyers choose faster bots over accurate vendor responses
- Agents receive only rule-valid configurations and prices
- Same engine governs rep screens and agent endpoints
- Guardrails block sub-floor pricing before quote send
- Audit trail satisfies procurement and internal review
- Agent traffic converts without bypassing product policy
Real-world application
Example workflow: lamp module quote from procurement platform agent
A UV curing OEM connected a buyer procurement agent to Mercura agent endpoints after a chatbot pilot invented incompatible lamp and power supply pairs. Agents now request module configurations through validated API calls, receive priced lines that pass wattage and reflector rules, and trigger approval when discount exceeds account policy. Product ops review agent audit entries instead of re-keying every request. Sales engineers handle exceptions only when agents hit genuine edge cases.
Business impact
Why agentic CPQ is governed agent access, not an unconstrained chat layer
Agentic CPQ treats procurement agents as a buyer channel that must obey the same configuration intelligence as your team. It complements conversational interfaces, AI solvers, API-first parity, and headless deployment. Mercura does not replace your LLM vendor, agent framework, or procurement contract negotiations. Someone must define scopes, test adversarial prompts, and monitor audit logs. If the pain is "agents quote fast but product ops keeps finding invented violations", agentic CPQ aligns inquiry, configuration, price, approval, and order with rules you already trust for human sellers.
See a procurement agent receive a rule-valid lamp module quote with audit attribution
Book a demo and walk agent endpoints until constraint rejection, approval routing, and priced return match the guardrails your product team sets today.
Let’s build together.
We empower manufacturers to master product modeling, streamline quoting process, reduce errors, and ultimately deliver the tailored solutions that customers demand.