INTL
Freelancer
어려움
외주
원격 가능
AI-Driven Tally Stock Reports
예산
$12,500~$37,500 INR
예상 기간
3~4개월
난이도
어려움
기술 스택
Python
AI Development
Machine Learning
Data Integration
Software Architecture
Tally ERP Integration
REST API
ODBC
TensorFlow
PyTorch
Pandas
AI 분석 요약
Tally 환경에서 작동하는 AI 모듈을 개발하여, 원시 데이터를 기반으로 실시간 재고 수준, 공급망 지표(재주문 시점, 재고 회전일수, 운송 중 재고), 그리고 가중평균법을 사용한 재고 평가 보고서를 생성하고, 이를 Tally에 자동 입력하는 프로젝트입니다. AI/ML 개발, Tally ERP 데이터 통합, 파이썬 스크립팅, 그리고 재무/재고 관리 지식 역량이 필요합니다.
프로젝트 원문 설명
I need a small AI module that plugs into my existing Tally environment, pulls raw purchase, sales and stock-movement data, and turns it into a daily report that is pushed straight back into Tally as a ledger or voucher entry I can open like any other report.
The module has to do three concrete things for every run:
• Calculate current inventory levels for each SKU in real time.
• Work out key supply-chain metrics such as reorder point, days of cover and in-transit quantities.
• Produce an accurate stock valuation that respects my weighted-average method already configured in Tally.
I do not mind whether you build the model in TensorFlow, PyTorch or another modern framework—use whatever lets you finish quickly and keep maintenance simple. A neat Python script with an .exe wrapper, or a light web service that Tally can call through ODBC or REST, would both be fine as long as the end result lands in Tally every day without manual intervention.
Acceptance criteria
• A single-click (or scheduled) job that fetches data from Tally, runs the calculations and writes the finished report back.
• Clear mapping documentation so I can see which Tally fields feed each metric.
• Source code, brief setup guide and a quick Loom/Zoom walkthrough showing the process working on my machine.
If you can demonstrate something similar you’ve automated for accounting software before, that will speed up my decision.
The module has to do three concrete things for every run:
• Calculate current inventory levels for each SKU in real time.
• Work out key supply-chain metrics such as reorder point, days of cover and in-transit quantities.
• Produce an accurate stock valuation that respects my weighted-average method already configured in Tally.
I do not mind whether you build the model in TensorFlow, PyTorch or another modern framework—use whatever lets you finish quickly and keep maintenance simple. A neat Python script with an .exe wrapper, or a light web service that Tally can call through ODBC or REST, would both be fine as long as the end result lands in Tally every day without manual intervention.
Acceptance criteria
• A single-click (or scheduled) job that fetches data from Tally, runs the calculations and writes the finished report back.
• Clear mapping documentation so I can see which Tally fields feed each metric.
• Source code, brief setup guide and a quick Loom/Zoom walkthrough showing the process working on my machine.
If you can demonstrate something similar you’ve automated for accounting software before, that will speed up my decision.
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