You will get Document Intelligence Platform - Multi-Stage Retrieval Engine
Project details
In the modern landscape of high-stakes corporate finance, M&A, and legal due diligence, the primary bottleneck to decision-making is no longer the availability of data, but the velocity of comprehension. Professional analysts are currently buried under "Data Rooms" containing thousands of heterogeneous documents—scanned PDFs, complex Excel tables, legal contracts, and fragmented email chains. VeritasDoc AI is an enterprise-grade Document Intelligence Platform engineered to dismantle this bottleneck.
Traditional search engines find keywords. Standard RAG systems find semantic similarities. VeritasDoc AI finds truth. The platform is designed for environments where a 1% margin of error can result in a multi-million dollar miscalculation. To achieve this, the platform treats documents not as static text files, but as a rich web of entities, financial metrics, and legal obligations. By combining the "intuition" of vector embeddings with the "logic" of a knowledge graph, VeritasDoc AI allows users to ask complex, multi-hop questions that involve relationships across hundreds of different files.
Traditional search engines find keywords. Standard RAG systems find semantic similarities. VeritasDoc AI finds truth. The platform is designed for environments where a 1% margin of error can result in a multi-million dollar miscalculation. To achieve this, the platform treats documents not as static text files, but as a rich web of entities, financial metrics, and legal obligations. By combining the "intuition" of vector embeddings with the "logic" of a knowledge graph, VeritasDoc AI allows users to ask complex, multi-hop questions that involve relationships across hundreds of different files.
Machine Learning Tools
ChatGPT, GPT-3, NLTK, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, TensorFlowWhat's included
| Service Tiers |
Starter
$2,000
|
Standard
$2,500
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 15 days | 20 days | 30 days |
Number of Revisions | 0 | 0 | 0 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code | - | - |
About Ramesh
AI Architect (MLOps | Devops | .NET | AWS | Terraform)
79%
Job Success
Chennai, India - 2:41 am local time
Director | CTO | Chief AI Architect
[Email: rameshrmca2001@gmail.com] | [Phone: 9444856420] | [Location: India]
EXECUTIVE PROFILE
Strategic Technology Leader with over 25 years of experience specializing in Enterprise Architecture, Generative AI (LLMs), and MLOps. Proven expertise in architecting high-volume, business-critical systems across Banking, Retail, and Manufacturing. A hands-on leader who has successfully transitioned legacy infrastructures into modern, AI-driven ecosystems using AWS and Azure. Certified in TOGAF, PMP, and CSM, with a career-long commitment to TDD, Agile methodologies, and scalable distributed systems.
TECHNICAL SKILL MATRIX
Leadership: Strategic Planning, Product Modernization, Capex/Opex, Team Mentorship (20+).
AI/ML & Data: Generative AI (LLMs), PyTorch, TensorFlow, MLOps, Feature Stores, Computer Vision.
Cloud & DevOps: AWS, Azure, Docker, Kubernetes, CI/CD for ML, Jenkins, Terraform.
Architecture: TOGAF 9, Microservices, Event-Driven Architecture (EDA), SOA, DDD, TDD.
Software Stack: .NET Core, Java, Python, Node.js, React, Angular, ASP.NET MVC, WCF.
Databases: SQL Server (2017+), Oracle, MongoDB, Sybase, PL/SQL.
Steps for completing your project
After purchasing the project, send requirements so Ramesh can start the project.
Delivery time starts when Ramesh receives requirements from you.
Ramesh works on your project following the steps below.
Revisions may occur after the delivery date.
Phase 1: The Secure Foundation (Infrastructure & Auth)
Goal: Establish the "hard shell" of the platform. Identity & Access Management (IAM) API Gateway & Backbone Environment Orchestration Database Design
Phase 2: The Ingestion Pipeline (The "Data Factory")
Goal: Transform raw, messy files into structured, clean data. Asynchronous Orchestration Advanced OCR & Layout Object Storage Chunking Strategy