Modular ERP
Case Study . 2023
cloud-ready ERP platform engineered for modern, fast-moving companies and extended with deeply integrated AI agents.
01
What is it exactly?
The mission is to tame the traditional complexity of ERPs without sacrificing depth. Deliver a system that is:
. Flexible enough for real-world edge cases
. Structured enough to stay reliable at scale
. Intelligent enought o automate repetitive work with AI
DISEEC ERP is a comprehensive platform with finance, sales, HR, manufacturing, and AI support.
ERP systems generally exist on a spectrum: on one end, there are complex, powerful solutions that are inflexible and challenging to implement; on the other, there are simpler tools that are user-friendly but often fail to support growth or provide robust process management.
Build a full that can run a serious business end to end, but behaves like a flexible application platform
Low code customization for non technical admins
Server & client scriptingfor deeper logic
Unified API layer across all modules
Role based security and multi-company capabilities by design
02
Take talent hiring as an example
Hiring is messy and multi-channel, We wanted DISEEC ERP to turn this chaos into a single, intelligent hiring pipeline.
Candidates email resumes, DM on social platforms, submit via forms, or call.
HR manually copies data into an ATS or spreadsheet.
So...
Each open position will be backed by an AI Hiring Agent that:
- Collects candidates from various sources like email parsing and web forms.
- Identifies relevant keywords and categorizes candidates by role fit.
- Summarizes candidate replies into a brief for HR.
- Ranks candidates based on key criteria, highlighting potential fits and routing them to hiring managers with next steps.
Then...
Each open position will be backed by an AI Hiring Agent that:
- Collects candidates from various sources like email parsing and web forms.
- Identifies relevant keywords and categorizes candidates by role fit.
- Summarizes candidate replies into a brief for HR.
- Ranks candidates based on key criteria, highlighting potential fits and routing them to hiring managers with next steps.
tadaaa
Each open position will be backed by an AI Hiring Agent that
- Collects candidates from various sources like email parsing and web forms.
- Identifies relevant keywords and categorizes candidates by role fit.
- Summarizes candidate replies into a brief for HR.
- Ranks candidates based on key criteria, highlighting potential fits and routing them to hiring managers with next steps.
03
Technical Architecture & Scalability
The Financial Insight Copilot allows users to make natural language inquiries, such as asking for the top 10 customers by margin for the current quarter. It also features anomaly detection to identify suspicious transactions and unusual trends in expenses.
Project & Delivery Intelligence predicts potential delays by analyzing task completion rates and historical trends, ensuring that managers are alerted in advance if deadlines are at risk of slipping.
Global Search and Knowledge Summaries enable semantic searching through various sources such as documents, projects, tickets, and emails. For instance, you can request a summary of all activities related to Client X over the past year.
Financial Insight Copilot
Project & Delivery Intelligence
Global Search & Knowledge Summaries
The Financial Insight Copilot allows users to make natural language inquiries, such as asking for the top 10 customers by margin for the current quarter. It also features anomaly detection to identify suspicious transactions and unusual trends in expenses.
Project & Delivery Intelligence predicts potential delays by analyzing task completion rates and historical trends, ensuring that managers are alerted in advance if deadlines are at risk of slipping.
Global Search and Knowledge Summaries enable semantic searching through various sources such as documents, projects, tickets, and emails. For instance, you can request a summary of all activities related to Client X over the past year.
Seach
Assistance
Consulting
Summarizing
Prediction
Guidance
Navigation
Analyzing
04
Build
Backend
Modular service architecture (accounts, HR, projects, etc.) built around a shared document engine.
Frontend
Modern web stack with a component-based UI, responsive design, and progressive enhancement.
Database
Relational database with strong referential integrity and indexing strategies for high-volume transactional data.
Background Jobs
Task queues for heavy processing: payroll runs, AI model calls, report generation.
Extensibility
Because we bring more than visuals. We bring outcomes.
