Packaging enquiries are unstructured:

Feasibility decisions happen late:

Pricing logic is often manually applied:

Decisions are fragmented across teams:

Technical Context

A structured system is required to formalize these workflows into defined operational layers.

Buyer requirements are often described in general terms without standardized structural parameters. These inputs require interpretation before feasibility or costing can begin.

Structural compatibility and production constraints are typically evaluated after initial design discussions, leading to avoidable iteration cycles.

Cost calculations are frequently handled through spreadsheets or isolated systems, requiring internal coordination before reliable outputs can be generated.

Sales, design, and factory planning teams often operate sequentially, resulting in delayed alignment and extended pre-production timelines.

System Architecture Overview

Presentation Layer

Structured capture and normalization of buyer requirements.

Pricing Engine Layer

Production Ready Output Layer

Decision Gate Layer

Deterministic pricing logic with isolated manufacturer rule control.

Cost range, production baseline, and decision workflow trigger

Enforcement of packaging feasibility and structural guardrails.

AI never controls pricing. All pricing is executed through deterministic backend logic.

Cloud Deployment Model

• Containerized Node.js backend

• Deployed on Google Cloud Run

• Stateless compute architecture

• Scalable request handling

• Separation between conversational interface and Pricing engine

• Designed for scalable containerized deployment on Google Cloud Run with structured observability.

Stateless compute processes each request independently, eliminating dependency on persistent session state and enabling predictable horizontal scalability. Tenant-level logical isolation ensures each manufacturer operates within a fully segregated pricing environment, with no cross-tenant access to proprietary cost logic. This architecture supports scalable deployment while preserving strict operational confidentiality.

Multi-Tenant Isolation

Each manufacturer operates within a fully isolated pricing environment where cost structures, material configurations, and margin logic are independently controlled. Pricing rules are never shared across tenants, and no manufacturer has visibility into another’s configuration. Buyer interactions are limited to production ready outputs, with no exposure of internal calculation logic or rule parameters. System-level governance boundaries enforce strict separation between buyer access and manufacturer-controlled decision logic, preserving confidentiality while enabling scalable multi-tenant deployment.

• Tenant-level pricing rule control

• Logical environment separation

• Controlled output exposure

• Configurable per production facility

No manufacturer has visibility into another manufacturer’s cost structure.

Data Governance & Control

Structured input normalization:

• Tenant-level pricing rule control

• Logical environment separation

• Controlled output exposure

• Configurable per production facility

• Independent configuration per manufacturer

• Isolated pricing parameter management

• No cross-tenant data visibility

• Role-based access boundaries

• Segregated rule execution environments

• Deployment-ready tenant provisioning

• Configurable margin and cost structures

• Environment-level governance control

Deterministic rule enforcement:

Mandatory human approval before finalization:

Controlled output formatting:

Buyer requirements are converted into defined structural parameters before decision processing begins. Unstructured descriptions are mapped into controlled decision inputs. This reduces ambiguity and improves consistency across enquiries.

Production feasibility and pricing rules are applied within predefined system boundaries. Rule execution does not depend on conversational variability. Outputs remain consistent for identical structured inputs.

System responses are generated as structured decision artifacts. Outputs include cost ranges and production baselines rather than raw calculations. Internal pricing logic is not exposed in user-facing responses.

System responses are generated as structured decision artifacts. Outputs include cost ranges and production baselines rather than raw calculations. Internal pricing logic is not exposed in user-facing responses.

Security & Operational Governance

• Cloud infrastructure deployed on Google Cloud

• Role-based access controls

• Tenant-level logical isolation

• Structured audit logging during pilot

• Controlled configuration management

Infrastructure Stack

• Node.js containerized backend

• Google Cloud Run (serverless compute)

• Structured data persistence layer

• REST-based API architecture

• Observability-enabled deployment

Scalability Roadmap

Phase 1 – Pre-Production Decision Intelligence

Phase 2 – Production Planning Integration

Phase 3 – Operational Intelligence

structured feasibility decisioning before design initiation
Deterministic pricing logic applied within isolated manufacturer environments.
Human-in-the-loop approval enforced before production confirmation.

Extension of structured decision data into production monitoring environments.
Alignment with machine-level quality standard systems under governed access.
Controlled integration of operational signals into structured decision feedback loops.

Integration of structured decision outputs with material dependency modeling.
Lead-time sequencing and vendor-based input alignment within controlled parameters.
Support for capacity-aware scheduling logic under defined operational guardrails.