Case study

OptiBlend: Precision Engineering for Chemical & Fertilizer Optimization

Executive summary

OptiBlend is a high-performance SaaS platform that utilizes linear programming to optimize chemical compositions, minimizing material costs while strictly adhering to industrial quality standards.

The problem

Manual calculation inefficiency

Traditional methods for determining fertilizer and chemical mixes often rely on spreadsheets or manual trial-and-error, leading to significant material waste.

Cost volatility

Fluctuating prices of raw materials make it difficult for manufacturers to identify the most cost-effective recipe that still meets specific chemical requirements.

Scaling complexity

Managing hundreds of different formulations across various client accounts requires a robust, multi-tenant architecture that can handle complex mathematical processing in real-time.

The solution

Linear equation solver

Implementation of an advanced optimization engine that processes chemical constraints (e.g., Nitrogen, Phosphorus, Potassium levels) to calculate the least-cost formula.

Multi-tenant SaaS framework

A secure, isolated environment allowing multiple organizations to manage their unique inventories and formulations within a single, scalable application.

Real-time inventory integration

A dynamic system where material price updates immediately reflect in the optimization suggestions, ensuring maximum profitability.

Cloud-native reliability

Built on a resilient AWS architecture, ensuring high availability and data integrity for industrial clients who rely on these calculations for daily production.

Technical deep-dive (impact)

From prototype to production. We took the initial concept and built a production-grade system using Angular for a responsive frontend and NestJS for a high-performance backend.

Optimized data layer. We leveraged PostgreSQL for relational data integrity and Redis for high-speed caching, ensuring that complex optimization queries return results with minimal latency.

Infrastructure as code. We transitioned the deployment process to an automated, Terraform-based system on AWS, allowing for rapid provisioning of new client instances and consistent environment management.

Business impact. By automating the optimization process, OptiBlend has enabled users to reduce raw material expenditure by significant margins while maintaining 100% compliance with target chemical specifications.

Impact snapshot

Spec compliance

100%

Target chemical requirements met

Price-driven updates

Real-time

Inventory-linked optimization

Client isolation

Multi-tenant

Secure per-organization data

Operations model

AWS + IaC

Terraform-managed environments

Platform performance

Illustrative scores aligned with solver reliability, data layer speed, and industrial readiness.

Optimization throughput trend (conceptual)

Technical stack

AngularNestJSPostgreSQLRedisAWSTerraform

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